Dissertations / Theses on the topic 'Agronomic modelling'

Through the re-use of empirical functions and new model development, this study aims at contributing to the development of advanced biofuels in Europe. Four lignocellulosic crops were selected and tested in stand-alone (sunn hemp – Crotalaria juncea L.) and rotation system (sunn hemp, biomass sorghum - Sorghum bicolor x Sorghum sudangrass, kenaf - Hibiscus cannabinus L. and industrial hemp - Cannabis sativa L.) in different European environments. The first Chapter deals with a new model development (SunnGro) to reproduce sunn hemp, an interesting summer crop for advanced biofuels in Europe; in the second Chapter, the same model was used to simulate 20-year sunn hemp productivity across Europe. The SunnGro model reproduces sunn hemp development and growth, while providing a detailed description of leaf/branch size heterogeneity and its evolution during the vegetative season, depending on thermal time accumulation (GDD), sowing time (ST) and density (SD). The model was calibrated and evaluated using 20 sunn hemp field datasets collected in Greece, Spain and Italy. Interesting correlations were found between simulated and measured values of branch and leaf number (0.80<R2<0.92) and biomass accumulation (0.67<R2<0.82). Hence, SunnGro can be a valuable tool for estimating the potentialities of sunn hemp, either as main or intercropping, as feedstock for advanced biofuels across Europe. The third Chapter is dedicated to the in-season growth simulation of first-of-a-kind food/energy crop rotations aimed at providing lignocellulosic feedstock for advanced biofuels without increasing land pressure. The rotations with biomass sorghum, industrial hemp and sunn hemp resulted in the highest biomass yields, whereas kenaf was less productive. The presented models were developed to provide user-friendly tools to estimate the potentialities of the selected lignocellulosic crops across Europe. Even though these models need further ameliorations and extensions, to now, they represent reliable tools for preliminary assessments.

Experiments were conducted: (i) to investigate varietal differences in pea (Pisum sativum L.) root response to mechanical impedance, (ii) to study the effect of mechanical impedance on root growth and morphology and (iii) to predict root growth in soils whose mechanical impedance varied temporally and spatially by adapting the Diggle (1988), ROOTMAP, model. Pea varieties whose root growth rates did not differ under unimpeded conditions had their root growth rates reduced by significantly different proportions in response to mechanical impedance. Highly significant correlations between first order lateral elongation rate and diameter were observed for pea roots grown in moist vermiculite. There was also evidence that regular stimulation of the root tip is required to trigger lateral emergence. An experimental procedure for obtaining ROOTMAP input parameters was devised and the growth and distribution of pea roots grown for 29 days in soil whose mechanical impedance varied with time and depth as a result of soil drying out, was successfully predicted. These findings highlight the potential that exists for selecting and breeding varieties based on root characters that confer insensitivity of response to mechanical impedance and for using ROOTMAP to investigate the growth response of different crop varieties in realistic soil scenarios.

El reg és necessari per tal d'assegurar produccions estables dels cultius d'estiu de zones semiàrides del món, on la precipitació és escassa i irregular. La planificació de l'ús de l'aigua de reg és crucial per a la conservació del recurs i per a la sostenibilitat dels sistemes agrí­coles. En condicions d'aigua de reg limitant, l'adopció d'estratègies de reg deficitari pot augmentar l'eficiéncia en l'ús de l'aigua.<br/>Aquesta tesi es centra en l'estudi de la resposta del panís i el sorgo al reg deficitari. Al capí­tol 2 es presenta l'estudi comparatiu del panís i el sorgo al reg deficitari imposat mitjançant una font lineal d'aspersió. L'objectiu fou l'estudi del sorgo com a possible cultiu alternatiu al paní­s sota condicions limitants d'aigua de reg. Els resultats obtinguts indiquen que en condicions de reg òptim el paní­s és més productiu que el sorgo i que el sorgo pot ser una alternativa viable al panís en condicions de reg limitant, donat que presenta menors reduccions de rendiment.<br/>Al capí­tol 3 es planteja l'estudi de la resposta del paní­s al reg deficitari aplicat per inundació. Els objectius d'aquest treball foren: estudiar l'efecte d'un dèficit hí­dric moderat en diferents fases del cicle del cultiu del paní­s sobre el creixement, el rendiment i els seus components. Els resultats obtinguts han indicat que la fase de floració fou la més sensible al dèficit hí­dric moderat produït per un interval més gran entre regs, amb reduccions significatives de rendimient, í­ndex de collita i components del rendiment. El reg deficitari durant la fase d'ompliment del gra en cap cas va reduir el rendiment i els seus components.<br/>Al capí­tol 4 es presenten els resultats de la modificació, parametrització i validació d'un model de simulació de cultius per a paní­s amb dades obtingudes als assaigs anteriors. L'objectiu fou el de desenvolupar una eina útil per a l'anàlisi posterior de diferents estratègies de reg per a les condicions de la Vall del Ebre a Espanya. El model va predir de manera satisfactòria la fenologí­a, el creixement i el rendiment en condicions d'aigua no limitant i sota diferents tractaments de reg deficitari. Es van identificar i discutir algunes limitacions del model.<br>El riego es necesario para asegurar producciones estables en los cultivos de verano en las zonas semiáridas del mundo, donde la precipitación es escasa e irregular. La planificación del uso del agua de riego es crucial para la conservación del recurso y para la sostenibilidad de los sistemas agrí­colas. En condiciones de agua de riego limitante, la adopción de estrategias de riego deficitario puede aumentar la eficiencia en el uso del agua.<br/>Esta tesis se centra en el estudio de la respuesta del maí­z y el sorgo al riego deficitario. En el capí­tulo 2 se presenta el estudio comparativo del maí­z y el sorgo al riego deficitario impuesto mediante una fuente lineal de aspersión. El objetivo fue el estudio del sorgo como posible cultivo alternativo al maí­z bajo condiciones limitantes de agua de riego. Los resultados obtenidos indican que en condiciones de riego óptimo el maí­z es más productivo que el sorgo y que el sorgo puede ser una alternativa viable al maí­z en condiciones de riego limitante, puesto que presenta menores reducciones de rendimiento.<br/>En el capí­tulo 3 se plantea el estudio de la respuesta del maí­z al riego deficitario aplicado por inundación. Los objetivos de este trabajo fueron: estudiar el efecto de un déficit hí­drico moderado en distintas fases del ciclo del cultivo del maí­z sobre el crecimiento, el rendimiento y sus componentes. Los resultados obtenidos han indicado que la fase de floración fue la más sensible al déficit hídrico moderado producido por un mayor espaciamiento entre riegos, con reducciones significativas de rendimiento, í­ndice de cosecha y componentes del rendimiento. El riego deficitario en la fase de llenado de grano en ningún caso redujo el rendimiento y sus componentes.<br/>En el capí­tulo 4 se presentan los resultados de la adaptación, parametrización y validación de un modelo de simulación de cultivos para maí­z con datos obtenidos en los ensayos anteriores. El objetivo fue desarrollar una herramienta útil para el análisis posterior de distintas estrategias de riego para las condiciones del Valle del Ebro en España. El modelo predijo de forma satisfactoria la fenologí­a, el crecimiento y el rendimiento en condiciones de agua no limitante y bajo distintos tratamientos de riego deficitario. Se identificaron y discutieron algunas limitaciones del modelo.<br>Irrigation is needed to achieve stable yields in the summer crops of the semiarid regions of the world, where rainfall is scarce and irregularly distributed.<br/>Efficient planning of water use for irrigation is crucial for the conservation of the resource and for the sustainability of the agricultural systems. Increase in water use efficiency can be achieved by deficit irrigation practices under water limited conditions.<br/>This thesis focuses on the study of the maize and sorghum responses to deficit irrigation. Chapter 2 presents the comparative study of maize and sorghum to deficit irrigation using the sprinkler line-source technique. The objective was to study sorghum as a possible alternative crop to maize under limited irrigation conditions. The results obtained have shown that maize was more productive than maize under optimum irrigation and that sorghum can be an economically alternative crop to maize if water supply is limited, because of its lower yield reduction under deficit irrigation.<br/>Chapter 3 focuses on the study of maize under deficit flooded irrigation.<br/>The objectives were: to study the effect of a moderate water stress at different stages of crop development on crop growth, yield and its components. The results indicate that flowering was the most sensitive phase to the moderate water deficit caused by a greater spacing of the irrigation events, with significant reductions in yield, harvest index and yield components. Deficit irrigation during the grain filling phase had no effect on yield.<br/>Chapter 4 presents the results of a crop simulation model adaptation, parameterization and validation for maize using data from the previous field experiments. The objective was to develop a tool for exploring the consequences for maize yield of different irrigation strategies in the conditions of the Ebro Valley in Spain. The model simulated satisfactorily phenology, growth and yield under no limiting water conditions and under different deficit irrigation treatments. Some model limitations were identified and discussed.<br>L'irrigation est nécessaire pour garantir des productions stables des cultures d'été dans les zones semi-arides du monde, où la précipitation est insuffisante et irrégulière. La planification de l'utilisation de l'eau d'irrigation est crucial pour la conservation de ce ressource et pour la durabilité des systèmes agricoles. Dans des conditions limitées d'eau d'irrigation, l'adoption de stratégies d'irrigation déficitaire peut augmenter l'efficience dans l'utilisation de l'eau.<br/>Cette thèse se centre dans l'étude de la réponse du maïs et du sorgho a l'irrigation déficitaire. Dans le chapitre 2 se présente l'étude comparative du maïs et du sorgho à l'irrigation déficitaire imposé en utilisant une source linéaire d'aspersion. L'objectif était l'étude du sorgho comme une possible culture alternative au maïs sous des conditions limitantes d'eau d'irrigation. Les résultats obtenus indiquent qu'aux conditions d'irrigation optimale le maïs est plus productif que le sorgho et que le sorgho peut être une alternative viable au maïs en conditions d'irrigation limitée, puis qu'il présente des réductions du rendement plus faibles.<br/>Dans le chapitre 3 s'étudie la réponse du maïs a l'irrigation par inondation déficitaire. Les objectifs de ce travail étaient: étudier l'effet d'un déficit hydrique modéré sur la croissance, le rendement et ses composantes dans des différentes phases du cycle de la culture du maïs. Les résultats obtenus ont indiqué que la phase de la floraison était la plus sensible au déficit hydrique modéré produit par un intervalle plus prolongé de temps entre les irrigations. On a détecté des réductions significatives du rendement, indice de collecte et composantes du rendement. L'irrigation déficitaire dans la phase de remplissement du grain n'a réduit en aucun cas le rendement et ses composantes.<br/>Dans le chapitre 4 se présentent les résultats de la modification, paramètrisation et validation d'un modèle de simulation de cultures pour le maïs avec des données obtenues-dans les essais antérieurs. L'objectif était le développement d'un outil pour pouvoir analyser postérieurement des stratégies d'irrigation dans les conditions de la vallée de l'Ebre en Espagne. Le modèle prédit d'une manière satisfaisante la phénologie, le croissance et le rendement sous des conditions de non-limitation d'eau et sous des différents traitements de l'irrigation déficitaire. On a identifié et discuté quelques limitations du modèle.

Yield losses due to wild species are relevant for a variety of cropping systems worldwide, e.g., in the case of rice weeds they can reach 60%. However, in the broader sense, wild species may also have positive effects on cropping systems for their capability to provide environmental benefits. In fact, they are fundamental to maintain high levels of biodiversity and, in the context of grassland communities, they are crucial for the provision of ecosystem services like those involved with pollination and recreational experiences. A quantitative understanding of the complex and dynamic interactions among species within agro-environmental systems is thus crucial to better analyze, for instance, the possible effects of climate change on community dynamics and to timely define effective adaptation strategies. In this context, the aim of this thesis was the development of new models for the simulation of the interaction between cultivated and wild species. Biophysical models are powerful tools to analyze the interactions between plants and environmental variables as well as to optimize crop management. However, one of their main weakness is the lack of algorithms for simulating the interactions between cultivated and wild species. The few examples available that consider these interactions are mainly related to fungal pathogens, whereas approaches considering weeds, insects and multi-species plant communities are extremely rare and insufficiently validated. To fill this gap, this PhD Thesis focused on the modelling of three categories of communities of increasing complexity: crop-weed (two plant species), grasslands (multi-species plant communities) and crop-insect-insect predators (different kingdoms). For the three categories, agroecosystems of worldwide importance were identified as case studies: paddy rice (chapter 2), grasslands (chapter 3 and 4) and olive trees (chapter 5). In particular, in chapter 2 a new model was developed for simulating the interaction between rice and two weeds (barnyardgrass and red rice); chapter 3 and 4 are focused on the extension of a model for the simulation of plant community dynamics in the context of mountain grassland systems, with case studies in temporary grasslands in the Apennine and in natural pastures in the Alps. The third chapter, in particular, focuses on the definition of strategies for adapting 9 grasslands management to climate change by explicitly considering their floristic composition, whereas the fourth chapter presents initial results on the effects of grazing and climate change on the productivity and floristic composition of pasture communities. Chapter 5 shows a new model of interactions among olive trees, the olive fruit fly (Bactrocera oleae (Rossi, 1790)) and its predators, whereas chapter 6 refers to the general conclusions of the researches carried out in this PhD Thesis. Although the new models developed in this work are process-based to reflect the complexity of interactions occurring in agroecosystems, they assume simplified descriptions of biophysical processes through a limited number of parameters to make them usable in operational contexts.

Land degradation is a widespread problem that affects about 1.5 billion people globally. It can be defined as the decline in the productive capacity of the land, and the loss of functionality of ecosystems. Overall, land degradation leads to ecosystem services degradation, because it affects and causes the depletion of several soil functions (e.g. sediment retention, nutrient cycling, carbon stocks, and water retention). Therefore, it is also a constraint in securing food production and it could cause food insecurity. Hence, land degradation represents a considerable problem especially in developing countries, where people strongly rely on the ecosystems and natural resources for their livelihoods. The principal aim of this study was to assess land degradation by integrating different sources of knowledges and data, to derive a synthesis relevant to inform decision-making processes, and to target priority areas for conservation and restoration interventions. In this study, three ecosystem services (ESS) were modelled to infer land degradation in a small area, in the Halaba special woreda, located in the Ethiopian Great Rift Valley. In particular, sediment erosion and retention, nutrient retention and export, and carbon storage and sequestration were modelled. Data from a local soil survey, from global coverage datasets, and from a supervised land use cover classification were used for the ESS modelling. Remote Sensing data were used during the parametrisation phase of the ESS modelling. Local knowledges and perspectives were gathered using an extensive participatory approach that targeted the communities of three kebeles in the study area, and the experts of the Halaba woreda Agricultural Office. 33 focus group discussions and 32 semi-structured interviews were conducted in the summer 2016. The information acquired through the ESS modelling and during the participatory approach was then integrated in a Bayesian Belief Network (BBN), a probabilistic graphical model, to derive a spatial explicit land degradation risk assessment. The results showed that assessing land degradation through the lens of key ecosystem services represents a valid approach. The ESS modelling results showed that the study area is characterised by high soil erosion rates, low carbon storage and sequestration, and low nitrogen retention. Moreover, the ESS modelling also showed that using data from global coverage datasets could affect the reliability of the ESS assessment. Furthermore, the qualitative study, derived from the participatory approach, highlighted the presence of complex linkages between environmental and socio-economic factors, which exacerbate land degradation. The integration of ESS modelling results, participatory approach and literature data in the BBN proved to be an efficient approach to derive a synthesis of the several knowledges acquired during the several steps of this PhD project. Overall, this study demonstrated that a transdisciplinary and interdisciplinary approach is an effective means to address land degradation risks, taking into consideration people needs and priorities. In order to reverse land degradation trends, there is the need to adopt intense restoration and sustainable land management programs. However, there is also the need to couple conservation interventions with development strategies, such as market access and development, land tenure system improvements, off-farm job opportunities generation, and livelihoods diversification. This could foster land conservation and restoration, and could support sustainable economic growth and inclusive development.

This work aims to improve the existing modelling tools that allow quantifying and evaluating the CA impact on SOC sequestration with a specific link to the ARMOSA cropping system model. This model is a versatile tool to represent the carbon and nitrogen fluxes and the influence of high levels of agroecosystem processes varying in response to agricultural management and pedoclimatic conditions. To define which conservation agriculture practices impact the most on SOC sequestration and to quantify their single impact I reviewed the previous scientific research published between 1998 and 2020 with a meta-analytical approach. The results described that CA performance dramatically depends on the initial SOC stock amount, superficial crop residue retention, soil clay content and duration of the management application. Based on these initial results and on the need to get reliable model outputs in the SOC simulation, I defined which were the ARMOSA requirements that would improve the general model reliability. For this reason, I developed a specific module that accounts for the surface crop residue degradation that was not previously considered. This new module resulted highly dependent on the soil temperature and water content variation. Therefore, the model's capability to react to a variation of these conditions is a key improvement due to the rising temperatures and lack of water that will affect agriculture under the future climate change scenario. On the other hand, besides the carbon input from the surface, the core of the SOC dynamic representation occurs at the bulk soil level. Again, even though many carbon-oriented models represent in detail the bulk soil carbon dynamic, only the full cropping system model has the reliability to be identified as a decision support tool. In addition, the very last scientific modelling guides suggested that these models should ideally be verifiable using physically defined and measurable pools (namely DOM, dissolved organic matter, POM, particulate organic matter and MAOM, mineral associated organic matter) rather than only with conceptual pools as for most historical ecosystem models. For this reason, I developed a new ARMOSA 2.0 release that gathers the robustness of the classical ARMOSA version, with a new SOM dynamic conceptualization accounting for these last scientific achievements. In this last release, the central role of the microbe is worth mentioning as a “microbially explicit” approach has been integrated into the ARMOSA 2.0 version. Thus, microbial biomass now directly leads the decomposition process of the SOM pools. Finally, I tested the ARMOSA 2.0 release compared to the previous ARMOSA 1.0 version and the SALUS model. This comparison was based on measured carbon data collected across different countries and allowed me to test the performance of the new release in the simulation of conventional, minimum and no-till management. The RMSE coefficients (5.3 for ARMOSA 1.0, 5.2 for ARMOSA 2.0 and 4.3 for SALUS, on average from all the simulations) retrieved from the three models are promising since ARMOSA 2.0 performed equal or, in specific cases, even better than the other two competitors. The specific behaviour of the different pools allowed to captured specific characteristics of the CA management. The capability of this new model release to capture the SOC pathways across different soil management practices will be extremely useful in predicting how conservation agriculture can impact SOC across different climates and locations.

The increasing attention of public opinion towards the environmental impact of production activities has made it imperative to reduce the aggressiveness of productive systems on the environment. Also the agricultural sector, considered one of the principal strengths of transformation of the territory, is asked to predispose eco-compatible programmes of production. The institutions and national and international organisms encourage the adoption of techniques of conservative agriculture as a tool for guaranteeing, on the one hand the necessary crop production to face the demand for food of the growing population and, on the other the safeguarding and improvement of the quality of natural resources. Conservative agriculture is born with the intent to reduce or eliminate the intense tillage of cultivated lands that has caused impoverishment, degradation and loss of soil in favour of a more eco-friendly management of different agroecosystem components. Nevertheless weed management, the complexity of which is a deterrent for the adoption of this type of agronomic system, represents one of the main problems. Weeds are the main cause of economic losses in agriculture worldwide, both as crop yield reduction and control costs. In a conventional farming system weeds are controlled by herbicides and mechanical operations that together are able to maintain the infestation level beneath the threshold of economic damage. In a conservative system, to obtain the same level of crop defence, it is necessary to increase the chemical control with the consequent increased costs for farmers, health risks and environmental impacts. In this scenario, Integrated Weed Management plays a key role in order to achieve environmental, social and economic sustainability of crop production. Particularly, weed emergence and weed-crop competition models can provide useful indications about timing, type and cost-effectiveness of control measures. This research has the goal of providing wider and deeper knowledge of what is involved for the weed science sector in the implementation of conservation agriculture protocols. The main objective, common to all the studies presented in this thesis, is the calibration of a prediction model to optimize the timing for the weed control in a no-tillage soil. The model under study is AlertInf, a model created for tilled soils that is based on the concept of hydrothermal time. According to this approach the emergence dynamics is determined by two main factors: temperature and water potential of the soil. Seeds in the soil accumulate hydrothermal time for their germination according to temperature threshold values and a water potential typical for each species. Chapter 1 describes the experiments for the estimation of temperature thresholds for four no-tillage soil weed species: Taraxacum officinale, Sonchus oleraceus, Senecio vulgaris, Conyza spp, comparing different methods for the estimation of this parameter. Chapter 2 highlights the importance of soil microclimate information acquisition (such as temperature and water potential) in the seed germination area. A field experiment was designed to assess the extent of changes in temperature and soil moisture resulting from no-tillage. In particular, a system of sensors, which allows the measurement of temperature and water potential in the upper soil layers, was tested as the soil surface is involved in the germination processes and weed growth in a conservative system. For modelling purposes, the emergence dynamics of the some weed species were studied and whether and how the dynamics of these species change in a different agronomic management was verified. A study was therefore conducted in a controlled environment to test the effect of the seed burial depth and tillage on the amount of emerging plants and the emergence dynamics (Chapter 3). Seasonal weed surveys were done on three experimental farms in Veneto region from 2011 to 2013 in conventional and conservative management fields to verify the species present in the two different systems and the emergence dynamics (Chapter 4). The last chapter (Chapter 5) shows the transferability of AlertInf model from maize to soybean in conventional management. A result that advances the hypothesis of the transferability also in a conservative environment. With this thesis the bases have been established for the construction of a predictive model of weed emergences in conservation agriculture, but model construction necessitates in-depth knowledge of all the factors involved in the phenomenon determination and accurate inputs, therefore it has been underlined that many problems still have to be solved and further researches are needed<br>La crescente attenzione da parte dell’opinione pubblica verso l’impatto che le attività produttive hanno sull’ambiente, ha reso improrogabile l’incentivazione a ridurre l’aggressività dei sistemi produttivi sull’ambiente. Anche il settore agrario, considerato una delle principali forze di trasformazione del territorio, è chiamato a predisporre programmi di produzione eco-compatibili. Le istituzioni e gli organismi nazionali e internazionali incoraggiano l’adozione di tecniche di agricoltura conservativa quale strumento per garantire la produzione agraria necessaria per far fronte alla domanda di cibo della popolazione in crescita e la difesa e il miglioramento della qualità delle risorse naturali. L’agricoltura conservativa nasce con l’intento di ridurre o eliminare le intense lavorazioni del suolo che hanno causato impoverimento, degradazione e perdita di terreno agrario a favore di una gestione più sinergica delle componenti dell’agroecosistema. Tuttavia uno dei problemi principali legati a questo tipo di sistema agronomico è rappresentato dalla gestione delle infestanti, la cui complessità è tale da costituire da costituire spesso un deterrente per gli agricoltori. La presenza delle piante infestanti è imputata essere la principale causa di danno economico per l’agricoltura a livello mondiale, sia in termini di calo di resa delle colture sia come costi sostenuti per il loro controllo. In un sistema agrario convenzionale il controllo delle malerbe è effettuato per mezzo di erbicidi e lavorazioni meccaniche del terreno che in modo sinergico riescono a mantenere il livello delle piante infestanti sotto la soglia di danno economico. In un sistema conservativo, per mantenere lo stesso livello di difesa delle colture è necessario aumentare il controllo chimico con conseguente aumento dei costi per l’azienda, rischi per la salute e danni ambientali. In questo scenario la gestione integrata delle malerbe gioca un ruolo cruciale per il raggiungimento di una maggiore sostenibilità ambientale, sociale ed economica delle produzioni agricole. In particolare, il ricorso a strumenti informatici quali i modelli previsionali della dinamica di emergenza delle malerbe in campo possono fornire utili indicazioni sui tempi, sui modi e sulla convenienza economica di un eventuale intervento di controllo. La presente ricerca nasce con lo scopo di fornire un quadro di conoscenze più ampio e approfondito su ciò che comporta l’applicazione di protocolli di agricoltura conservativa per il settore malerbologico. L’obiettivo principale che guida tutti gli studi svolti in questo lavoro di tesi è la calibrazione di un modello di previsione delle emergenze per ottimizzare il momento di intervento per il controllo delle infestanti in terreno non lavorato. Il modello oggetto di studio è AlertInf, un modello creato per i terreni lavorati che si basa sul concetto di Tempo Idrotermico. Secondo tale approccio la dinamica di emergenza è guidata da due principali fattori, che sono temperatura e potenziale idrico del suolo. I semi nel suolo accumulano tempo idrotermico per la germinazione secondo dei valori soglia di temperatura e potenziale idrico caratteristici per ogni specie. Il primo capitolo della tesi (Capitolo I) descrive gli esperimenti per la stima di queste soglie per le tipiche specie da sodo, Taraxacum officinale, Sonchus oleraceus, Senecio vulgaris, Conyza canadensis e Conyza sumatrensis, mettendo anche a confronto diversi metodi per la stima di tale parametro. Il secondo capitolo (Capitolo II) sottolinea l’importanza dell’acquisizione delle informazioni microclimatiche del suolo (temperatura e potenziale idrico) nella zona di germinazione dei semi. A tale fine, un esperimento di campo è stato predisposto per valutare l’entità dei cambiamenti di temperatura e umidità del suolo derivanti dalla non lavorazione del terreno. In particolare si è testato un sistema di sensori che permettesse la misurazione di temperatura e potenziale idrico negli strati più superficiali di suolo, essendo la superficie il luogo interessato dai processi di germinazione e crescita delle piante infestanti in un sistema conservativo. Ai fini della modellizzazione si è ritenuto fondamentale studiare la dinamica di emergenza di queste specie e allo stesso tempo, verificare se e come varia la dinamica di specie tipiche dell’ambiente arativo a seguito di un cambio di gestione agronomica. Uno studio è stato quindi condotto in ambiente controllato per testare l’effetto della profondità d’interramento dei semi e della lavorazione sulla quantità di piante emerse e sulla dinamica di emergenza (Capitolo III). Rilievi malerbologici stagionali sono stai eseguiti in tre aziende sperimentali del Veneto dal 2011 al 2013 in appezzamenti coltivati in modo convenzionale e conservativo per verificare le specie presenti nei due sistemi di gestione e le dinamiche di emergenza in campo (Capitolo IV) L’ultimo capitolo (Capitolo V) mostra la trasferibilità del modello AlertInf da mais a soia in gestione convenzionale. Un risultato che fa avanzare l’ipotesi di trasferibilità da un sistema agronomico convenzionale a conservativo. Con questo lavoro di tesi sono state poste le basi per la realizzazione di un modello di previsione delle emergenze delle infestanti in agricoltura conservativa, ma la realizzazione di un modello richiede approfondita conoscenza dei fattori coinvolti nella determinazione del fenomeno e accuratezza degli input, ed è stato evidenziato che molti sono ancora i problemi da risolvere e che ulteriore ricerca è necessaria

Despite recent advances in agronomical techniques, N fertilization still shows low efficiency (NUE), with consequently high N loss in the environment. This could be particularly relevant in nitrate vulnerable zones, as the Venice Lagoon watershed, in which N leaching represents a serious risk for water pollution. Applying N site specifically accordingly to crop need, N –VRA (variable rate application) represents a strategy to increase NUE. Although this approach has been proved to provide environmental benefit, a drawback in its application arises from the difficulties to predict precisely final crop yield at the time of fertilizing. This can result in under or over- fertilization which results on one hand in economic loss and on the other in a large N balance on the soil. In this dissertation different approaches N-VRA application were evaluated in the Venice Lagoon Border, and their benefits in term of enhancing grain production and economic and environmental sustainability were evaluated. In the first experiment (Chapter II), a two-years field trial was managed to investigate the effect of N-VRA based on management zones on durum wheat final production. Furthermore, the use of real time sensors on a combine- harvester and the spectrophotometric analysis of gluten composition allowed to evaluate the influence of late N foliar fertilization and N-VRA on grain quality and to verify the feasibility of zone- harvesting. In Chapters III and IV two different strategies of integration of spectral measurements and crop modelling were proposed. An innovative approach of coupling proximal sensing, medium weather forecasts and crop modelling to optimize N-VRA in durum wheat was proposed in Chapter III. After calibration with data collected in the first experiment, the model was run in each management zone with weather forecasts to evaluate N optimum rate, which was then corrected based on NDVI data. In Chapter IV proximal sensing and crop modelling were integrated in order to improve within-field estimation of N stress on corn nd therefore optimize N fertilization. In this case model accuracy in N stress prediction was improved optimizing the model to properly predict the yield and subsequently to match the simulated and the NDVI-derived LAI (leaf area index). The optimized model was subsequently run to evaluate optimum N rates able to minimize N stress. General conclusions were drawn in Chapter V, underlining both the benefits and the limitations of these N-VRA approaches.<br>Nonostante i recenti progressi della tecnica agronomica, la fertilizzazione azotata riporta ancora una bassa efficienza (NUE), con conseguenti ingenti perdite di N nell’ambiente. Questo problema è di particolare importanza in zone vulnerabili ai nitrati, come il bacino scolante della Laguna di Venezia. Somministrando azoto in maniera sito-specifica in base ai bisogni della coltura, la N-VRA (variable rate application) rappresenta una strategia per incrementare l’efficienza della fertilizzazione. Nonostante i provati benefici economici ed ambientali derivanti da questa tecnica, una limitazione deriva dalla difficoltà nella stima della resa finale al momento della concimazione. Questo può causare casi di sottostima o sovrastima o delle dosi che causano da un lato perdite economiche e dall’altro un elevato surplus di N nel suolo. In questa tesi sono state valutate differenti strategie di N-VRA nel bacino scolante della Laguna di Venezia. Nel primo esperimento di campo (Capitolo III) è stata applicata una N-VRA basata su zone omogenee in grano duro e ne sono stati studiati gli effetti sulla produzione. Inoltre, l’uso di sensori montati sulla mietitrebbia e le analisi spettrofotometriche della composizione del glutine hanno permesso di studiare l’effetto della concimazione azotata tardiva e della N-VRA sulla qualità della granella e di valutare l’ attuabilità di una raccolta sito-specifica. Due diversi metodi di integrazione di misure spettrali e modellistica colturale sono state proposti nei Capitoli III e IV. Nel capitolo III è stato studiato un approccio innovativo per l’assimilazione di proximal sensing, previsioni metereologiche e modelli colturali per ottimizzare la concimazione al grano duro. Dopo aver condotto una calibrazione con dati raccolti nel precedente esperimento, è stata simulata la dose ottimale per ogni zona omogenea, che è stata corretta successivamente in base ai valori di NDVI misurati su tutto l’appezzamento. Nel capitolo IV i dati spettrali sono stati integrati al modello per migliorare l’accuratezza della simulazione della carenza di N in mais, e valutare la dose ottimale di N da distribuire in grado di minimizzare lo stress. Il modello è stato inizialmente calibrato per simulare correttamente la resa e successivamente per far coincidere il LAI (leaf are index) simulato con quello ricavato dalle misurazioni di NDVI. Nel capitolo V vengono riportate le conclusioni generali, sottolineando sia in benefici derivanti da queste strategie di N-VRA, sia le limitazioni.

The aim of my Ph.D. work was to investigate the main factors related to N leaching from arable land under different pedoclimatic conditions and cropping systems in Lombardia plain. In situ monitoring and modelling analysis were defined to evaluate the potential N losses via leaching from arable land and the effect of agricultural management. At monitoring sites, representative of Lombardia arable land, data of soil, crop, water, and N-related variables were collected for a period from 2 to 5 years. Soil characterization, crop yield, leaf area index, harvest index, crop nitrogen uptake, soil water content and soil solution nitrogen concentration at different depths were measured over the monitoring period. All the collected data were used to calibrate and validate the ARMOSA model. Such dynamic model was developed by our research team to predict N leaching risk from arable land in northern Italy. The calibration and validation procedures allowed to parameterize (i) pedological parameters related to soil water balance and nitrogen dynamics, such as mineralization, denitrification, volatilization, wet and dry atmospheric deposition, immobilization; (ii) six crops growth and development parameters which lead the gross assimilation of CO2, leaf area index, stem and root elongation, respiration loss, nitrogen dilution curve, crop development based on growing degree days, dry matter partitioning, evapotranspiration and residuals calculation. The outstanding result was that crop, water and N-related variables were accurately simulated, being in full agreement with observed data. Once calibrated and validated, ARMOSA model was applied at regional scale in order to evaluate the potential risk of N leaching. The model run over 20 years in 35 simulation units, obtained by dividing Lombardia plain in homogenous districts in terms of pedological, climatic and cropping systems features. Each district was characterized by two representative soil types, meteorological observed data set, crop rotations according to the regional land use analysis, organic N load, calculated on the basis of livestock density. With regard to results, similar or even higher N use efficiency resulted with increasing organic N supply and proportionally reduced mineral fertilization. In such way, N leaching decreased by half in maize-based forage systems. Moreover, the eventual choice to introduce a catch crop in rotation strongly contributed to minimize N leaching.

Nel contesto dei cambiamenti climatici, al fine di aumentare la resilienza della coltivazione del frumento, risulta necessario comprendere le interazioni e le relazioni tra tecniche agronomiche a basso impatto ambientale e caratteristiche positive delle varietà di frumento. L'obiettivo generale di questo studio è quello di caratterizzare e individuare le varietà di grano più adatte per ridurre l’impatto ambientale della sua coltivazione. Il primo esperimento, di durata triennale, svoltosi presso un'azienda agricola biologica, ha permesso la caratterizzazione di 24 accessioni di grano tenero. Le analisi effettuate hanno riguardato sia gli aspetti agronomici, sia quelli nutrizionali e sia quelli nutraceutici. Il secondo studio ha caratterizzato, da un punto di vista nutrizionale e agronomico, diversi genotipi e popolazioni evolutive di grano tenero. Alcune varietà in condizioni pedoclimatiche favorevoli hanno raggiunto valori di produzione estremamente elevati, mentre in diversi contesti, hanno registrato valori di resa bassi. Diversamente, la popolazione evolutiva Bioadapt ha registrato un'elevata stabilità, in termini di risultati produttivi raggiunti. La terza ricerca ha studiato alcuni aspetti della fisiologia del grano tenero, per approfondire una caratteristica fisiologica delle piante, con particolare rilevanza e possibili importanti implicazioni per la coltivazione sostenibile del grano tenero. L'obiettivo è stato quello di identificare le varietà di grano tenero con un’attività allelopatica potenziale elevata, attraverso l'analisi della crescita iniziale delle radici della pianta di grano e delle erbe infestanti circostanti. Sono state selezionate e confrontate 30 cultivar di grano tenero, mentre il loietto perenne è stato impiegato come specie infestante modello. La capacità allelopatica non si è manifestata semplicemente come una risposta dose-dipendente delle molecole emesse nel substrato di crescita. Le caratterizzazioni delle accessioni effettuate nel presente studio rappresentano un valido punto di partenza per futuri programmi di miglioramento genetico, al fine di ottenere varietà idonee a sistemi di produzione a basso impiego di input.<br>In order to reduce the use of pesticides products and increase the resilience of wheat cultivation, in the context of climate change, it is necessary to fully understand the interactions and relationship between agronomic techniques with low environmental impacts and positive varieties traits. The general aim of this study is to characterize and identify the most suitable wheat varieties to achieve low environmental impact cultivation of common wheat. One experiment, carried out during three years at an organic farm, characterized 24 accessions of common wheat. The surveys carried out concerned both the agronomic, the nutritional, and the nutraceutical components. Some accessions registered excellent agronomic performance. A second study aimed to characterize, from a nutritional and agronomic point of view, different genotypes and evolutionary populations of common wheat, observing how they are influenced by different environments and meteorological trends. Some varieties in favorable pedoclimatic conditions reached extremely high production values, while in different contexts, they recorded lower values. In contrast, the evolutionary Bioadapt population registered high stability, in terms of production results achieved. The third research studied some aspects of common wheat physiology, to understand a physiological characteristic of plants, with particular relevance and important implications for sustainable cultivation of common wheat. The aim was to identify the common wheat varieties with a higher potential allelopathic activity, through the analysis of the initial root growth of the wheat plant and surrounding weeds. 30 cultivars of common wheat were selected and compared, while the perennial ryegrass was employed as weed model species. The allelopathic capacity seemed to be not simply a dose-dependent response to the molecules emitted in the growing substrate. The characterizations of the varietal resources carried out in the present study represent a valid starting point for future breeding programs, to obtain suitable varieties for low-input production systems.

The main challenge of modern agriculture lies in the need of enhancing crop productivity to guarantee food security while achieving the sustainability of cropping systems in a changing climate. In a recent speech to the 21st Conference of Parties to the United Nations Framework Convention on Climate Change (COP21) held in Paris, the president of the United States declared that for all the challenges we face, the growing threat of climate change could define the contours of this century more dramatically than any other. This is why He hopes that all the countries in the world, united in common effort and by a common purpose, will not condemn the next generation to a planet that’s beyond its capacity to repair. Agricultural activities deep influence the carbon, water and nutrients cycles at global level, then still play a vital role in the survival of humankind. The need to double food production by 2050 is entrusted to agriculture, which accounts for 14% of greenhouse gases emission and is considered as the economic sector most uniquely susceptible to changes in climate patterns, due to its dependence on the biophysical environment. Standing first among all food grain crops, rice (Oryza sativa L.) is in the spotlight due to the projected decrease in production in top producing countries and to the environmental sustainability of rice cropping systems, in light of the use of large amount of water for irrigation and of the contribution to the emission of greenhouse gases (GHGs) at the global level. The improvement of the water and nutrient management in paddy rice cropping systems is then considered as a necessary step to mitigate agriculture’s GHG emissions, as reported by the United Nations Foundation. The scaling up of mitigation strategies from farmers’ level to national policy makers needs the support of the scientific community, who is in charge to develop research to address these paramount questions. In this framework, the adoption of cropping system simulation models as a reference to assess both the productivity and the environmental impacts of cropping systems under a variety of management and climatic scenarios seems unavoidable, as they are the only available tools to reproduce the nonlinear responses of biophysical processes to boundary conditions. They also represent a viable solution to design and test alternate strategies to mitigate the emission of GHGs and to optimize the use and management of resources in agriculture. This PhD program enables the scientific community to move forward the integration of available biophysical models to dynamically simulate the different components of the rice cropping system, considering the multiple, mutual interactions among system’s domains which determine rice crop yield and environmental drawbacks. The final achievement is the delivery of a software targeting this purpose, which is documented in the last chapter; the objective of this research product is to give a modelling solution to simulate the comprehensive set of biophysical processes involved with the paddy rice cropping system, considering the crop development and growth, the soil water dynamics, the effects of fertilizers on nitrogen leaching and the emission of greenhouse gases at field scale, considering the impact of alternate farmer management strategies. During the work some deficiencies in current models were highlighted and solved, such as the unjustified complexity of widely adopted crop simulators or the lack, within them, of algorithms for the simulation of processes which significantly contribute to explain the variability of rice yield. The output of this work is made available through software components and modular modelling solutions: this choice, representing the state of the art of software engineering science, removes technological bottlenecks which usually prevent advances in agricultural system modelling and fosters international collaborations between research centers while laying the basis for further developments.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>The objectives of this thesis were (i) to identify the expanded leaves number (LNexp) and tips (LNtip) from which there is reduction in the contribution of culm reserves to leaf appearance rate in sugarcane and (ii) the effect of different densities of stem in leaf development in the culture of sugarcane. The experiments were conducted at the experimental area of the Departamento de Fitotecnia, Centro de Ciências Rurais, Universidade Federal de Santa Maria, during the 2012/2013 growing season. The sugarcane clone used was SP 711406, with intermediate developmental cycle and well adapted to this location. To achieve the first objective, described in Chapter 1, the experimental design was randomized with 32 replications. Treatments were culm cuttings with: twice the length of the internode, one internode, half the length of internodes, and no internode. Results indicated that the reserves of the culm cuttings of sugarcane have their maximum contribution to the emission of the first two expanded leaves and of the first five leaf tips, and the appearance rate of subsequent leaves decrease due to reduction in culm cuttings reserves. To achieve the second objective, described in Chapter 2, the experiment was conducted in plant cane cultivation system. In plants marked the variables expanded leaves number (LNexp) and tips leaves number (LNtip) in the main stem, linear dimensions of expanded leaves and later, at harvest were determined yield components (total stem length were measured, fresh biomass of commercial stem dry mass commercial stem, number of nodes, number of internodes, internode length, fresh weight and dry weight of internode). It was concluded that the change in rate of leaf emergence (phyllochron greater) from the 15th leaf on is caused by a change in microclimate in the canopy and the increase of the sink strength of photosynthates to stem growth; and yield components are affected negatively by lower densities than those recommended for the crop planting.<br>Os objetivos desta tese foram (i) identificar o número de folhas expandidas (NFE) e totais (NFT) a partir do qual ocorre redução da contribuição das reservas do tolete para a taxa de emissão de folhas em cana-de-açúcar e (ii) o efeito de diferentes densidades de colmos no desenvolvimento foliar na cultura da cana-de-açúcar. Os experimentos foram conduzidos na área experimental do Departamento de Fitotecnia, Centro de Ciências Rurais, da Universidade Federal de Santa Maria, na estação de 2012/2013. O clone de cana-de-açúcar utilizado nos experimentos foi SP 711406, por ser um clone de ciclo intermediário e bem adaptado ao local. Para alcançar o primeiro objetivo, descrito no Capítulo 1, o delineamento foi o Inteiramente Casualizado com 32 repetições. Foram testados quatro tratamentos: duas vezes o comprimento do entrenó, uma vez o comprimento do entrenó, metade do comprimento do entrenó e somente o nó. Os resultados indicaram que as reservas no tolete de cana-de-açúcar tem a contribuição máxima para a emissão das duas primeiras folhas expandidas e das cinco primeiras folhas totais e a taxa de emissão de folhas subsequentes decresce devido ao esgotamento das reservas do tolete. Para alcançar o segundo objetivo, descrito no Capítulo 2, o experimento foi conduzido em sistema de cultivo cana-planta. Nas plantas marcadas foram medidas as variáveis número de folhas expandidas (NFE) e número de folhas totais (NFT) no colmo principal, dimensões lineares das folhas expandidas e posteriormente, no momento da colheita, foram determinados os componentes do rendimento (comprimento total do colmo, fitomassa fresca de colmo comercial, fitomassa seca do colmo comercial, número de nós, número de entrenós, comprimento do entrenó, massa fresca do entrenó e massa seca do entrenó). Concluiu-se que a mudança na velocidade da emissão de folhas (filocrono maior) a partir da 15ª folha é causada por formação de microclima no dossel e devido ao aumento do dreno de fotoassimilados para crescimento dos colmos; e que os componentes do rendimento são afetados de forma negativa por densidades de plantio menores que as recomendadas para a cultura.

The exponential development of biotechnology has lead to a quasi unlimited number of potential products going from biopolymers to vaccines. Cell culture has therefore evolved from the simple cell growth outside its natural environment to its use to produce molecules that they do not naturally produce. This rapid development could not be continued without new control and supervising tools as well as a good process understanding. This requirement involves however a large diversity and a better accessibility of process measurements. In this framework, software sensors show numerous potentialities. The objective of a software sensor is indeed to provide an estimation of the system state variables and particularly those which are not obtained through in situ hardware sensors or laborious and expensive analysis. In this context, This work attempts to join the knowledge of increasing bioprocess complexity and diversity and the time scale of process developments and favours systematic modelling methodology, its flexibility and the speed of development. In the field of state observation, an important modelling constraint is the one induced by the selection of the state to estimate and the available measurements. Another important constraint is the model quality. The central axe of this work is to provide solutions in order to reduce the weight of these constraints to software sensors development. On this purpose, we propose four solutions to four main questions that may arise. The first two ones concern modelling uncertainties.<p><p>1."How to develop a software sensor using measurements easily available on pilot scale bioreactor?" The proposed solution is a static software sensor using an artificial neural network. Following this modelling methodology we developed static software sensors for the biomass and ethanol concentrations in a pilot scale S. cerevisae cell culture using the measurement of titrating base quantity, agitation rate and CO&<br>Doctorat en sciences agronomiques et ingénierie biologique<br>info:eu-repo/semantics/nonPublished

The research conducted explored the dynamics of the historical water-management system that was in use at Engaruka, Tanzania, between the 15th to 18th centuries CE, the aim being to model the primary human and environmental factors and their interactions, and to assess how these influenced the development of the system at several spatial and temporal scales. The ABMs developed in this research represent first steps in the integration of archaeological evidence with ABM techniques in order to understand the Engaruka site. This research shows how the integration of data from different sources and disciplines can help in our understanding of how the system could have developed by integrating a multitude of factors and showing how these interactions influenced the development of the system.

The quantification of soil structure is primordial to determine the effects of management practices on soil environment. Soil structure is influenced by soil organic carbon content (SOC), which is usually recognised as one of the main indicator of soil fertility as it improves structure stability. Complex interactions link the soil structure and SOC that acts as a binding agent promoting aggregation. Several studies focussed on SOC dynamics and the relationship with soil aggregate microporosity, which is usually considered as a surrogate of the soil matrix complexity, neglecting the soil macropores outside aggregates. Therefore, the measures made at aggregate scale form only a small part of the important and complex properties of soil. Accordingly, it is important to quantify the effects that SOC exerts both is soil aggregates and undisturbed cores. The general aim of this work is to study the effects of different fertilisations (organic, mineral and mixed) applied to continuous maize by means of a long-term experiment established in 1962 in north-eastern Italy, analysing both small aggregates (few mm) and undisturbed soil cores (5 cm diameter, 6 cm length) with innovative three-dimensional techniques. The thesis is structured in five chapters. The first one is a review of the soil structure-SOC interactions and innovative three-dimensional methods involved in soil structure quantification. The second chapter analyses the effects of SOC and its humic fraction on the mechanisms of aggregate breakdown and improves upon the knowledge of aggregate structural properties. The third chapter compares and combines mercury intrusion porosimetry (MIP) and X-ray computer assisted microtomography (micro-CT) for characterising the soil structure. The fourth chapter analyses the 3D soil structure of undisturbed soil cores and the effects of SOC. The final chapter presents the general conclusions of the work.<br>La quantificazione della struttura del suolo è di primaria importanza per determinare gli effetti di diverse pratiche colturali sul terreno. La struttura è influenzata dal contenuto di carbonio organico (SOC), il quale è ampiamente identificato come il principale indicatore della fertilità del suolo, anche grazie alle sua attitudine di migliorarne la struttura fisica. Le interazioni che legano la struttura al SOC sono complesse e principalmente legate alla capacità di agire come agente aggregante tra le particelle che compongono la matrice del suolo. Molti studi si sono concentrati sulle dinamiche che legano il SOC e la microporosità degli aggregati (che è riconosciuta come un surrogato della complessa struttura del suolo) trascurando, in questo modo, la macroporosità, la quale non è individuabile in campioni di piccole dimensioni. Le misure fatte a scala di aggregato, perciò, ricoprono solo una parte delle importanti e complesse proprietà di un suolo. Di conseguenza è importante valutare l’effetto che esercita il SOC sia in piccoli aggregati che in campioni indisturbati. L’obiettivo generale di questo lavoro è valutare gli effetti di diversi regimi di fertilizzazione (organica, minerale e mista) in una prova di lungo periodo, iniziata nel 1962, gestita secondo una monosuccessione di mais. Sono stati analizzati sia aggregati di piccole dimensioni (pochi mm), che campioni indisturbati (5 cm di diametro, 6 cm di altezza), con innovative tecniche tridimensionali. La tesi è strutturata in cinque capitoli: il primo è una review sulle interazioni struttura del suolo-SOC e sulle tecniche tridimensionali utilizzate per la quantificazione della struttura. Il secondo capitolo analizza gli effetti del SOC e delle frazioni umiche sulla stabilità di struttura degli aggregati, individuando inoltre un nuovo meccanismo, legato alla diversa distribuzione della porosità, finora non considerato. Il terzo capitolo confronta e combina la porosimetria a intrusione di mercurio e la microtomografia a raggi X per la caratterizzazione della struttura. Il quarto capitolo analizza tridimensionalmente la struttura di campioni indisturbati e gli effetti del SOC sulla struttura stessa. Infine, l’ultimo capitolo riporta le conclusioni generali del lavoro.

L'effetto dei gas serra sul cambiamento climatico ha portato molti esperti a considerare la riduzione delle emissioni di gas serra come strategia per il riscaldamento globale. In particolare tale fenomeno è causato dall’anidride carbonica (CO2), metano (CH4) e il protossido di azoto (N2O). E 'ampiamente accettato che la principale fonte antropica di gas a effetto serra (tranne CO2) è dovuta alle attività agricole. Lo scopo di questo studio è quello di definire concetti e strumenti per facilitare il settore agricolo a ridurre le emissioni di gas serra. In particolare, abbiamo posto la nostra attenzione ai sistemi di misurazione delle emissioni dal suolo, testando un nuovo sistema (SASSFlux) e le sue caratteristiche a confronto con due strumenti ampiamente utilizzati (Bruel & Kjaer e gascromatografia). Inoltre abbiamo testato due modelli di simulazione (DNDC e SPACSYS) valutando i dati simulati e quelli misurati su un esperimento effettuato su lisimetri. In fine abbiamo applicato le conoscenze acquisite in pieno campo per la valutazione delle emissioni di CO2 e N2O con diversi concimi e lavorazione del terreno. La tesi si propone di fornire una visione completa dei diversi aspetti da affrontare nella valutazione delle emissioni di gas serra provenienti da diversi scenari di gestione agricola.<br>The effect of greenhouse gases (GHG) on climate change led many experts to consider the reduction of GHGs emissions as a crucial strategy to tackle the predicted global warming. In particular, atmospheric warming is caused mainly by carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). It is widely accepted that the main anthropogenic source of GHG (except CO2) is due to agriculture activities. The purpose of this study was to help define concepts and tools to facilitate agricultural sector to reduce greenhouse gas emissions. In particular we based our focus on measuring systems for CO2 emissions, testing the performance of novel system (SASSFlux) and its features in different condition with two widely used instruments (Bruel&Kjaer and gas chromatography). Moreover we testing two process-based models, DNDC and SPACSYS, evaluating their performance and the agreement between simulated and measured data on a experiment carried out on lysimeters. At the end we applied all the knowledge acquired on a field experiment evaluating CO2 and N2O emissions from different organic and mineral fertilizers and tillage. The complete thesis aims to provide a comprehensive view of the different aspects to be addressed in the assessment of GHG emissions from different scenarios of agricultural management.

L'effetto dei gas serra sul cambiamento climatico ha portato molti esperti a considerare la riduzione delle emissioni di gas serra come strategia per il riscaldamento globale. In particolare tale fenomeno è causato dall’anidride carbonica (CO2), metano (CH4) e il protossido di azoto (N2O). E 'ampiamente accettato che la principale fonte antropica di gas a effetto serra (tranne CO2) è dovuta alle attività agricole. Lo scopo di questo studio è quello di definire concetti e strumenti per facilitare il settore agricolo a ridurre le emissioni di gas serra. In particolare, abbiamo posto la nostra attenzione ai sistemi di misurazione delle emissioni dal suolo, testando un nuovo sistema (SASSFlux) e le sue caratteristiche a confronto con due strumenti ampiamente utilizzati (Bruel & Kjaer e gascromatografia). Inoltre abbiamo testato due modelli di simulazione (DNDC e SPACSYS) valutando i dati simulati e quelli misurati su un esperimento effettuato su lisimetri. In fine abbiamo applicato le conoscenze acquisite in pieno campo per la valutazione delle emissioni di CO2 e N2O con diversi concimi e lavorazione del terreno. La tesi si propone di fornire una visione completa dei diversi aspetti da affrontare nella valutazione delle emissioni di gas serra provenienti da diversi scenari di gestione agricola.<br>The effect of greenhouse gases (GHG) on climate change led many experts to consider the reduction of GHGs emissions as a crucial strategy to tackle the predicted global warming. In particular, atmospheric warming is caused mainly by carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). It is widely accepted that the main anthropogenic source of GHG (except CO2) is due to agriculture activities. The purpose of this study was to help define concepts and tools to facilitate agricultural sector to reduce greenhouse gas emissions. In particular we based our focus on measuring systems for CO2 emissions, testing the performance of novel system (SASSFlux) and its features in different condition with two widely used instruments (Bruel&Kjaer and gas chromatography). Moreover we testing two process-based models, DNDC and SPACSYS, evaluating their performance and the agreement between simulated and measured data on a experiment carried out on lysimeters. At the end we applied all the knowledge acquired on a field experiment evaluating CO2 and N2O emissions from different organic and mineral fertilizers and tillage. The complete thesis aims to provide a comprehensive view of the different aspects to be addressed in the assessment of GHG emissions from different scenarios of agricultural management.

La necessità di garantire l’accesso al cibo per una popolazione mondiale in continua crescita, adempiendo al contempo a precisi requisiti ambientali, rappresenta una grande sfida per il settore agroalimentare. Il successo, in questa sfida, può essere garantito da un utilizzo ottimale delle risorse aziendali, raggiungibile attraverso sforzi notevoli volti al monitoraggio e all’analisi del sistema agricolo. I recenti sviluppi in campo satellitare e modellistico, forniscono strumenti adatti allo scopo specialmente in caso di un utilizzo integrato delle due tecnologie. Il progetto di ricerca, oggetto di questa tesi, mira alla formalizzazione e successiva valutazione di uno strumento, basato sull’integrazione di modelli di simulazione e telerilevamento, per il supporto alle decisioni in agricoltura. L’attività di ricerca, culminata nell’applicazione dello strumento al caso studio, ha previsto la realizzazione di due attività preliminari. In prima istanza è stato eseguito uno studio di analisi di sensibilità per accrescere la conoscenza del modello utilizzato e identificare i parametri, alla cui variazione, il modello risulta più sensibile. In questo studio sono state considerate sia serie climatiche attuali che proiezioni nel medio futuro e, utilizzando due diverse configurazioni del modello WOFOST (una standard ed una che permette di simulare l’impatto degli eventi meteorologici estremi sulle colture), sono state simulate le cinque colture più coltivate in Europa. I risultati evidenziano una forte sensibilità del modello ai parametri coinvolti nella simulazione degli organi di accumulo in quasi tutte le condizioni esplorate a meno dei casi in cui sono state riscontrate condizioni limitanti per la produttività delle colture. In queste condizioni il modello è infatti risultato più sensibile ai parametri che regolano la simulazione delle prime fasi di crescita delle colture. La seconda attività preliminare ha invece permesso di quantificare l’impatto della componente soggettiva sulla precisione delle stime di indice di area fogliare (LAI), una variabile tra le più utilizzate per permettere l’integrazione di modelli di simulazione e telerilevamento. Attraverso l’applicazione del protocollo previsto dalla normativa ISO 5725 è stato possibile calcolare i limiti di ripetibilità e riproducibilità delle stime di LAI da immagini emisferiche e quindi ottenere una misura della loro precisione. I risultati ottenuti, dimostrano l’affidabilità della tecnica seguita per ottenere stime di LAI; la precisione ottenuta è stata infatti comparabile a quella che caratterizza altri strumenti in commercio. I risultati migliori sono stati ottenuti in caso di coperture vegetali continue ed omogenee, caratteristiche dei sistemi agricoli intensivi, sottolineando ulteriormente l’affidabilità di tale tecnica in questi contesti. Entrambe le attività, qui brevemente riassunte, hanno permesso di definire un valido punto di partenza per l’integrazione di modellistica e telerilevamento fornendo informazioni utili per la progettazione e la realizzazione del caso studio. In questa ultima attività, un sistema di previsione ad alta risoluzione basato sull’integrazione di modellistica e telerilevamento è stato formalizzato e quindi valutato utilizzando dati raccolti in risaia durante le annate 2014, 2015 e 2016. Il modello colturale WARM è stato integrato con serie temporali di LAI telerilevate, ricalibrando automaticamente quei parametri, identificati come i più influenti oppure strettamente legati alla simulazione del LAI. Il confronto dei risultati ottenuti adottando questo approccio con quelli ottenuti utilizzando solamente il modello colturale, ha permesso di evidenziare i miglioramenti nella stima della produttività del riso dovuti all’integrazione di informazioni telerilevate. In generale la simulazione delle produttività del riso è risultata affetta da un ridotto RRMSE (13.8%), se confrontata con quella ottenuta usando solamente il modello (RRMSE = 15.7%). Inoltre l’integrazione delle due tecnologie ad una elevata risoluzione spaziale (30 m × 30 m), ha consentito di riprodurre la variabilità interna di ciascun campo. I risultati ottenuti evidenziano la validità del sistema proposto per la stima della produttività del riso ad un’elevata risoluzione spaziale. Ciò detto, durante la valutazione del sistema sono emerse alcune criticità legate ad incongruenze tra le variabili simulate e quelle telerilevate. Questi aspetti, così come la possibilità di considerare altre colture e altri modelli di simulazione, pongono le basi per ricerche future.<br>The need to fulfil sustainability requirements while increasing productions to feed the raising world’s population represents a big challenge for the agricultural sector. To achieve this goal, improving management of resources at farm level is acknowledged as one of the most effective solutions. However, this requires intensive activities targeting cropping system monitoring and data processing. The advances in remote sensing and simulation technologies – especially when used in an integrated way – provide a valuable solution to support farmers and technicians in such a context. This research aims at setting up and evaluating pre-operational tools based on the integration of crop models and remotely sensed information to support decision making in cropping systems management. The research was articulated in two main preliminary activities before the application of crop models and remote sensing in a case study. Extensive sensitivity analysis experiments were performed to deepen the knowledge about model behaviour and to identify the most influential parameters for yield simulation. A wide range of conditions was investigated, considering both current weather and future climate projections, as well as five major crops cultivated in several European sites and using two different modelling solutions (the standard version of WOFOST and a version of the model improved for the simulation of the impact of extreme weather events). Model outputs were mainly influenced by parameters involved with storage organs development; nevertheless, in case limiting conditions were explored, simulations were influenced by parameters driving crop growth during early stages. Given leaf area index (LAI) data are those mostly used when crop models and remote sensing are integrated, the second activity targeted the quantification of the impact of subjectivity in LAI estimates from hemispherical images. Precision was determined via the application of the ISO 5725 validation protocol, thus leading to define repeatability and reproducibility limits. Results proved the reliability of LAI estimates from hemispherical images; the precision obtained was indeed comparable with that of other commercial instruments. The best results were obtained in case of high LAI and continuous canopy, further underlying the reliability of this method for intensive agricultural systems characterized by continuous and homogeneous canopies. Both the activities just presented aimed at defining a sound starting point for the coupling of crop models and remote sensing, providing useful information for the design of the case study. For this last activity, a high-resolution pre-operational system based on the WARM model and remotely sensed information was evaluated using observations from paddy rice fields during the seasons 2014, 2015 and 2016. The remotely sensed information, consisting in temporal series of LAI, were integrated in the model by automatically re-calibrating either parameters identified as the most influential or those strictly related with LAI dynamics. The system performances were compared with those obtained using the default parameterizations of the model. Results underlined the improvement in rice yield simulation after the integration of remotely sensed data, proving the reliability of the system. Overall, the simulation of rice yield was affected by a restrained RRMSE (13.8%), compared to the results obtained with the default model parameterizations (RRMSE = 15.7%). Moreover, the assimilation of remotely sensed information at high spatial resolution (30 m × 30 m) led to satisfactorily describe the within-field yield variability. The obtained results make the proposed system a valuable solution to provide high-resolution estimates of rice productivity. Nonetheless, weakness were highlighted, related with some the inconsistencies between observed crop state variables and crop reflectance properties. This, as well as the possibility to consider other models and crops, lays the basis for further studies.

Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2017-06-02T11:41:33Z No. of bitstreams: 2 Dissertação - Jordene Teixeira de Aguiar - 2016.pdf: 3048073 bytes, checksum: b062d30a5cf4c2dd3b7a78ebc8a9e2c6 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2017-06-02T11:42:03Z (GMT) No. of bitstreams: 2 Dissertação - Jordene Teixeira de Aguiar - 2016.pdf: 3048073 bytes, checksum: b062d30a5cf4c2dd3b7a78ebc8a9e2c6 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Made available in DSpace on 2017-06-02T11:42:03Z (GMT). No. of bitstreams: 2 Dissertação - Jordene Teixeira de Aguiar - 2016.pdf: 3048073 bytes, checksum: b062d30a5cf4c2dd3b7a78ebc8a9e2c6 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2016-03-03<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES<br>The influence of climatic variables on rice diseases was assessed in Brazil. Firstly, it was necessary to validate climate data from remote sensoring, retrieved from NASA’s database Prediction of Worldwide Energy Resource (POWER). POWER data were compared to climate records of surface stations from the National Institute of Meteorology (INMET). Climate data consisted of a time series (2004-2014) of monthly average temperatures and rainfall. Validation tests were carried out with Pearson’s coefficient of correlation and adjustment of linear regression models between the satellite data and surface stations. Further, data accuracy was checked according to average absolute error, root mean square deviation and concordance index. Monthly rainfall from most regions satisfactory correlated with Pearson coefficients between 0.75 and 0.95 (P<0.05). In contrast, maximum and minimum temperatures recorded by satellites showed irregular results that vary by region. In these cases, remote sensing did not detect extreme weather events, such as heavy rainfall or drought. Monthly rainfall comparisons also showed the most consistent results for all regions in accuracy tests. The endorsed data supported the next stage of this work, regarding the effects of climate variables on rice diseases. This investigation counted on a historical series of disease severities recorded in field tests, carried out between 1983 and 2014. Climatic data from INMET, EMBRAPA and NASA/POWER was arranged in a matrix of environmental variables, and tested for correspondence with disease severities recorded in 15 sites for at least eight years. Redundant climate variables were eliminated by principal component analysis. With structured data disposed in two datasets of climate (explanatory variables) and disease severity and productivity (response variables), canonical correlation analysis was performed (CCA) by location and by regions. The influence of climate on disease severity was demonstrated in only five sites, according to CCA models significant at 5%, with their first two axes explaining over than 50% of explanatory variables. In such sites, the total variation in disease severity was partially explained by climate variables. In the regional approach, climate variables did not significantly influence rice diseases in the North Region. Nevertheless, significant models demonstrated the correlation between climatic variables and disease in the Center-West and Northeast, despite the small percentage of explanation by the first two axes. In general, higher disease severity was related to rainfall and lower minimum temperatures during the reproductive stage of rice plots. In all cases, yield was not related to environmental variables.<br>Este estudo foi realizado para se verificar a influência de variáveis climáticas sobre doenças do arroz no Brasil. Inicialmente, foi necessário validar dados climáticos obtidos via sensor remoto orbital, obtidos no banco de dados Prediction of Worldwide Energy Resource (POWER) da NASA. Esses dados foram comparados aos obtidos de estações de superfície brasileiras do Instituto Nacional de Meteorologia (INMET). Os dados foram compostos de séries históricas (2004 a 2014) de médias mensais de temperaturas e precipitação. Para validação, foram estimados os coeficientes correlação de Pearson e modelos de regressão linear entre os dados estimados via satélite e obtidos via estações de superfície. Para verificação da acurácia, foram estimados o erro médio absoluto, o desvio médio quadrático e o índice de concordância. Os dados de precipitação mensal para a maioria das regiões apresentaram coeficientes de correlação satisfatórios, entre 0,75 e 0,95 (P<0,05). Já os dados de temperaturas máxima e mínima obtidos por satélites apresentaram resultados irregulares que variavam conforme a região. Nestes casos, verificou-se que os dados obtidos remotamente não detectaram eventos climáticos extremos, como chuvas ou seca intensas. As médias de precipitação mensal também apresentaram resultados mais consistentes para todas as regiões, em testes de acurácia. Os dados validados subsidiaram a segunda etapa deste trabalho, quando foram avaliados os efeitos das variáveis climáticas sobre as doenças da cultura do arroz. Contou-se com uma série histórica de dados de severidade de doença registrados entre 1983 a 2014. Os dados climáticos do INMET, Embrapa e NASA/POWER foram utilizados para compor uma matriz com variáveis ambientais, e verificação de sua correspondência com a severidade de doenças em 15 locais com séries históricas de pelo menos oito anos. Por meio da análise de componentes principais foram eliminadas as variáveis climáticas redundantes. Com dados estruturados em duas matrizes, clima (variáveis explanatórias) e severidade de doença mais produtividade (variáveis de resposta) foram realizadas análises de correspondência canônicas (CCA) por local e por regiões. Dentre os 15 locais analisados, apenas cinco apresentaram modelos significativos a 5%, com a explicação da variação dos dados pelos dois primeiros eixos acima de 50%, demostrando que, em alguns locais, a variação total da severidade das doenças é explicada parcialmente por variáveis climáticas. De acordo com as CCAs por regiões, observou-se que na região Norte as variáveis climáticas não influenciam significativamente as doenças do arroz. Por outro lado, modelos significativos demonstraram a correspondência entre as variáveis climáticas e doenças para as regiões Centro-Oeste e Nordeste, ainda que com baixa porcentagem de explicação. De modo geral, a maior severidade de doenças foi atribuída á ocorrência de chuvas e menores temperaturas mínimas durante o estádio reprodutivo da cultura. Em todos os casos, a produtividade não foi relacionada ás variáveis ambientais.

Sustainable land management (SLM) practices, as conservation agriculture (CA) and conventional tillage with cover crops (CC), aimed at balancing competitive agricultural production and environmental protection, have been encouraged throughout the EU through policy and subsidisation. Adoption of SLM practices that regulate biogeochemical cycles, however, requires further study, especially given the effects of local pedo-climatic variability and because middle and long-term effects are not fully understood and may differ from short-term outcomes. For these reasons, in this work, field experiments were conducted in three farms in the low-lying venetian plain, characterized by loamy soils, where CA and CC were compared to conventional intensive tillage system (CV) on trials established since 2010. The first objective of the thesis was to evaluate, by integrating experimental field results with model predictions, the potential ecosystem services provided by CA and CC practices on SOC dynamic, air quality and climate regulation, nutrition biomass and regulating of water conditions. In this experiment, CA and CC results contrasted according to the soil functions, the ecosystem service category and evaluation time span. The former was more effective in providing regulating services in the short term, and less consistent in the long term, at least for GHG mitigation. GHG control is only one of the numerous ecosystem services provided by conservation practices (e.g. reduction of erosion and P particulate loss). Many of these depend on the C content which are strongly affected by the C stratification processes. Cover crop adoption, on the contrary, showed promise in the long term, whereas short-term outcomes (two-year experiment) were negatively affected by poor cover crop growth. The second objective aimed to assess the SOC stock variation due to the adoption of CA and CC in comparison to CV within a large sample (i.e., 240) of 0-50-cm soil profiles, comparing two expansive soil sampling operations conducted in 2011 and 2017. The study showed that CA enhances SOC stratification rather than SOC accumulation, with high topsoil SOC that may have partly counteracted soil surface compaction. However, a comparison with previous SOC stock quantifications between CA and CV after three years of the experiment suggests that some SOC stock increase occurred, even at 50 cm, despite being not significant. The burial of fresh biomass-C with cover crops in arable systems (CC) enhanced SOC stock depletion most likely due to priming effects, suggesting that C input management is pivotal for its accumulation in agroecosystems with low soil fertility and low SOC protection capacity.

The general goal of this research was to understand the agronomic and physiological changes of a lucerne crop in distinct physical radiation environments and to verify the potential of lucerne to grow under shaded conditions. To achieve this, the research was conducted in four main steps: (i) firstly, experimental data collection in the field using two artificial shade materials (shade cloth and wooden slats) under inigated and non-irrigated conditions; (ii) a second experiment with data collection in a typical temperate dryland agroforestry area under non-irrigated conditions; (iii) generation of a light interception sub-model suitable for shaded crops and (iv) a linkage between the light interception sub-model and a canopy photosynthesis model for agroforestry use. In experiments 1 and 2, lucerne crop was exposed to 6 different light regimes: full sunlight (FS), shade cloth (FS+CL), wooden slats (FS+SL), trees (T), trees+cloth (T +CL) and trees+slats (T+SL). The FS+SL structure produced a physical radiation environment (radiation transmission, radiation periodicity and spectral composition) that was similar to that observed in the agroforestry site (f). The mean annual photosynthetic photon flux density (PPFD) was 41 % under the FS+CL, 44% under FS+SL and 48% under T compared with FS in clear sky conditions. Plants were exposed to an intermittent (sun/shade) regime under both FS+SL and T, whereas under FS+CL the shaded light regime was continuous. The red to far-red (RIFR) ratio measured during the shade period under the slats was 0.74 and under the trees was 0.64. However, R/FR ratio increased to 1.26 and 1.23 during the illuminated period under FS+SL and T, respectively, and these were equivalent to the ratio of 1.28 observed under the FS+CL and 1.31 in FS. The radiation use efficiency (RUE) of shoots increased under the 5 shaded treatments compared with full sunlight. The pattern of radiation interception was unchanged by radiation flux, periodicity and spectral composition and all treatments had a mean extinction coefficient of 0.82. However, the magnitude of the decrease in canopy growth was less than those in PPFD transmissivity. The mean lucerne annual dry matter (DM) yield was 17.5 t ha⁻¹ in FS and 10 t ha⁻¹ under the FS+CL, FS+SL and T regimes. This declined to 3.4 t DM ha⁻¹ under T+CL (22% PPFD transmissvity) and 4.1 t DM ha⁻¹ under T+SL (23% transmissivity). A similar pattern of response was observed for leaf net photosynthesis (Pn) rates under the shade treatments compared with full sun. In addition, spectral changes observed under the trees and slats affected plant motphology by increasing the number of long stems, stem height and internode length compared with full sunlight. Thus, there were two main explanations for the increase in RUE under shade compared with full sun: (i) preferential partition of assimilates to shoot rather than root growth and/or (ii) leaves under shade were still operating at an efficient part of the photosynthetic light curve. The changes proposed for the canopy Pn model were appropriate to simulate the radiation environment of an agroforestry system. However, the model underestimated DM yields under the continuous and intermittent shade regimes. These were considered to be mainly associated with plant factors, such as overestimation in maintenance respiration and partitioning between shoots and roots in shade and the intermittency light effect on leaf Pn rates. Further investigation in these topics must be addressed to accurately predict crop yield in agroforestry areas. Overall, the lucerne crop responded typically as a sun-adapted plant under shade. It was concluded that lucerne yield potential to grow under intermediate shade was superior to most of C3 pastures previously promoted in the literature.

Les diatomées sont une composante majeure des écosystèmes marins et sont caractérisées par une grande diversité. L’objectif général de cette thèse est d’étudier les facteurs de contrôle des diatomées dans la Zone Côtière Belge (ZCB). Pour ce faire, la modélisation par groupes fonctionnels et l’approche basée sur les traits sont combinées :la première fournit un cadre écosystémique utile pour étudier les interactions des diatomées avec les compartiments biotiques et abiotiques de l’écosystème, et la seconde permet de représenter de façon efficace leur diversité fonctionnelle.<p><p>Dans un premier temps, puisque la taille est reconnue comme un trait majeur affectant de nombreux aspects de la valeur sélective du phytoplancton, la dépendance au biovolume de différents traits des diatomées a été établie sur base d’observations disponibles dans la littérature. Cette revue a montré qu’un compromis sépare les diatomées sur base de leur biovolume :les petites espèces sont meilleures compétitrices pour l’acquisition des ressources mais plus sensibles au broutage, et inversement. <p>Sur cette base, un ré-analyse d’un jeu de données incluant des comptages et mesures de biométrie avec l’identification de 68 taxons dans la ZCB entre 1992 et 2000 a été réalisée, avec une attention particulière pour la structure en termes de taille de la communauté de diatomées. Un regroupement des diatomées en fonction de leur biovolume a été réalisé sur base de leur évolution saisonnière typique. L’analyse de leur évolution temporelle suggère que la communauté des diatomées est composée d’assemblages avec une évolution saisonnière et interannuelle distinctes qui répondent vraisemblablement différemment aux conditions environnementales.<p>Afin d’étudier plus en profondeur les facteurs environnementaux contrôlant la structure en termes de taille de la communauté des diatomées dans la ZCB, le module diatomées du modèle MIRO, qui représente l’écosystème planctonique de la ZCP, a été modifié afin d’inclure les dépendances à la taille de quatre traits des diatomées. Cet outil reproduit correctement l’évolution saisonnière du biovolume moyen de la communauté, qui est caractérisé par de plus petites diatomées au printemps qui maximisent l’acquisition de ressources tandis que la prévalence du broutage en été induit une transition vers des espèces plus grandes. Le modèle a également été exploité pour étudier la gamme de tailles viables dans la ZCB en fonction des conditions environnementales. <p>Les résultats du modèle basés sur les traits ont ensuite été analysés sur la période 1992-2000. Les simulations ont mis en évidence les interactions complexes entre les processus physiques, de contrôles par les ressources et par le broutage, qui sont susceptibles de déterminer la variabilité interannuelle de la structure en termes de taille des diatomées dans la ZCB. La comparaison de ce modèle adaptatif avec un modèle plus conventionnel qui ne représente pas de diversité interne aux diatomées suggère que le premier produit une réponse légèrement plus flexible que le dernier, mais que la rigidité de la réponse simulée demeure un problème avec le modèle adaptatif qui reste incapable de représenter des évènements extrêmes de biomasse ou de structure de la communauté. Cela suggère que des développements supplémentaires du modèle sont nécessaires, en particulier du module zooplancton.<p>Finalement, une fonction écologique particulière est abordée dans une dernière section de cette thèse :la production d’une neurotoxine par certaines diatomées du genre Pseudo-nitzschia. Cette fonction a été incluse comme un métabolisme secondaire dans un modèle idéalisé de la croissance de Pseudo-nitzschia afin d’étudier les facteurs contrôlant la production de la toxine. Il est notamment montré que l’environnement lumineux est déterminant lorsque les conditions menant à la production de toxine sont rencontrées. <p><p>/<p><p>Diatoms are a key component of marine ecosystems and are characterized by an important diversity. The general objective of this thesis is to investigate the bottom-up and top-down controls of diatoms in the Belgian Coastal Zone (BCZ). This is done through the integration of their functional diversity into a coherent framework. In order to achieve this, Plankton Functional Type modelling and trait-based approaches are combined: the former provides an ecosystem context convenient to study the interactions of diatoms with biotic and abiotic compartments, and the latter allows an efficient representation of their functional diversity. <p><p>As a first step, since size is recognized as a master trait shaping many aspects of phytoplankton fitness, the cell volume dependences of diatom functional traits were compiled from observations available in the literature. This review showed that a trade-off distinguishes diatoms on the basis of their cell volume: smaller species are better competitor for resource acquisition but sensitive to grazing, and inversely. <p>On this basis, a re-analysis of a dataset including diatom cell counts and biometry with the identification of 68 taxa in the BCZ over the 1992-2000 period was carried out, with a focus on the size structure of the diatom community. A clustering of diatoms according to their cell volume was realized on the basis of their average seasonality. Investigation of their time evolution suggested that the diatom community in the area is composed of assemblages with distinct seasonal and interannual evolution that likely respond differently to environmental conditions.<p>In order to further investigate the bottom-up and top-down constrains on the size structure of the diatom community in the BCZ, the diatom module of the MIRO model, which represents the planktonic ecosystem of the BCZ, was modified in order to accommodate size-dependences of four diatom functional traits. This tool adequately reproduced the seasonal evolution of the mean cell volume of the diatom community, which is characterized by smaller diatoms in spring that maximize resource acquisition while the prevalence of grazing pressures in summer induces a shift towards larger species. The model was also used to investigate the range of viable diatom sizes in response to the bottom-up and top-down pressures in the BCZ.<p>Results of the trait-based adaptive model were then analysed over the 1992-2000 period. Simulations evidenced the complex interactions between physical, bottom-up and top-down processes that are likely to govern the interannual variability in the size structure of diatom in the area. Comparison of the adaptive model with a more conventional model resolving no diversity within diatoms suggested that the former produces a slightly more flexible response than the latter, but showed that the rigidity of the simulated response persists with the adaptive model which remains unable to catch extreme biomass and community structure events. This calls for further developments of other compartments of the model, more particularly zooplankton.<p>Finally, a peculiar ecological function is addressed on its own in the last section of this thesis: the toxigenicity of some species of the genus Pseudo-nitzschia. This function was added as a secondary metabolism in an idealized model of Pseudo-nitzschia growth in order to investigate the factors affecting toxin production. It notably showed that light was determinant under conditions leading to its production.<p><br>Doctorat en Sciences agronomiques et ingénierie biologique<br>info:eu-repo/semantics/nonPublished

The aim of this PhD research was to describe an assessment of the potential impacts of climate change as well as climate variability on rice production. It also discusses selected adaptation options within the context of the Malian agriculture. The research centers on an integrated modelling approach (BioMA) to compute current and future (2020, 2050) crop yields in the agricultural region of the Office du Niger (Mali). BioMA – Biophysical Models Application – is a platform for running biophysical models on generic spatial units. The application is based on independent components which allow implementing modelling solutions targeted to specific modelling goals. The collected data were used to (i) develop new modules (a model for simulating the height of the plant) (ii) implement the existing ones according to the peculiarities of the sub-Saharan environment (i.e. the Agromanagement module was extended in order to take into account the beginning of the rainy season) and to (iii) calibrate and validate the modelling solution defined for the purpose. Although parameterization procedures were performed in critical conditions – being reference data from the area a limiting factor – a preliminary calibration of WARM, for tropical and subtropical conditions, could be performed aromatically on Chinese datasets. Indeed these results achieved from these modelling exercises showed that the model is robust and able to reproduce yield variability within years and locations which made it suitable for the impact assessment study in Mali. The impact assessment on cropping systems was evaluated via a difference analysis with respect to the current conditions, focusing on changes in total biomass, final yield and transpiration demand. An overall reduction can be expected in 2050 (up to complete failure of the crop) whereas different results were obtained for 2020. The main season seem to be little affected by the increase of temperatures whereas the first cycle, which takes already place under extremely high temperatures, will face reductions up to 25%. Based on the results obtained in the impact assessment changes in sowing dates were tested in order to detect the most suitable management techniques which allow alleviating the negative effect of climate changes. The results suggested that changes in the sowing may be very effective in mitigating the adverse effect of climate change as well as the use of new crop cultivars with longer vegetative cycles. In fact in both systems an increase of production can be expected at short-term whereas at medium-term the losses can be significantly reduced.

The agricultural sector could be one of the most vulnerable economic sectors to climate change impacts during the coming decades. These impacts are related to change in the growth period, agricultural yields, extreme weather events, change in temperature and precipitation patterns, among others. All these impacts will have consequences on the agricultural production. Given the lack of substantial studies for climate change impacts on agriculture in Bolivia, the thesis dissertation develops an analysis and quantification of climatic change impacts and adaptation options using different model techniques, both, bottom-up and top-down, and in the last chapter an integrated assessment is developed. Crop model results obtained at a local scale, are inside the range of previous studies made on larger scales for Latin America and the whole World. On the other hand, the response functions developed by using regression techniques show crop yields with a very high level of accuracy with those of crop models. What is more, when using crop models for adaptation analysis, simulation results show that crop models are sensitive enough to detect optimal changes for different scenarios, and the Cost-Benefit analysis results confirm that changing the planting date is a very feasible and low-cost adaptation measure to face climate change effects. Finally, the Integrated model results show that microeconomic and macroeconomic policies applied together can lead to sustainable development, thus increasing Gross Domestic Product (GDP) and per capita income and reducing deforestation rates at the same time, and the identified forest conservation social cost is a good starting point for PES and REDD+ negotiation schemes in the context of Global Climate Change Agreements.<br>Il settore agricolo potrebbe rivelarsi nelle prossime decadi uno dei settori economici più vulnerabili agli impatti dei cambiamenti climatici. Questi impatti possono riguardare il periodo di crescita, le rese colturali, gli eventi meteorologici estremi, le variazioni di temperature e la distribuzione delle piogge. Tutti questi impatti avranno conseguenze sulle produzioni agricole. Considerata la mancanza di studi rilevanti sugli impatti dei cambiamenti climatici sull’agricoltura in Bolivia, la tesi discute lo sviluppo di un’analisi ed una valutazione degli impatti dei cambiamenti climatici e delle opzioni di adattamento utilizzando differenti modelli, sia con approccio bottom-up (dal basso verso l’alto) che top-down (dall’alto verso il basso), e, nell’ultimo capitolo, viene poi sviluppata una valutazione integrata. I risultati ottenuti con i modelli colturali su scala locale, sono comparabili con quelli ottenuti in precedenti studi effettuati su più larga scala sia per L’America Latina che a livello mondiale. Inoltre le funzioni di risposta sviluppate con tecniche di regressione mostrano rese colturali con elevati livelli di accuratezza rispetto a quelle ottenute con i modelli colturali. Per di più, quando si utilizzano modelli colturali per l'analisi di adattamento, i risultati delle simulazioni mostrano che i modelli colturali sono abbastanza sensibili nel rilevare le variazioni ottimali per i differenti scenari e i risultati dell’analisi Costi-Benefici confermano che la variazione della data di semina è una misura di adattamento facilmente attuabile e poco costosa per affrontare gli effetti del cambiamento climatico. Infine, i risultati del modello integrato mostrano che le politiche microeconomiche e macroeconomiche applicate assieme possono portare ad uno sviluppo sostenibile, aumentando così il Prodotto Interno Lordo (PIL) e il reddito pro capite, riducendo i tassi di deforestazione e, allo stesso tempo, il costo sociale di conservazione identificato si rivela un buon punto di partenza per sistemi di negoziazione PES e REDD+ nel contesto degli accordi globali sul cambiamento climatico.

This dissertation consists in studying the possible effects of climate change in watershed management. Specifically, the dissertation explores the possibility of using a Artificial Neural Networks – ANN models coupled with physically based hydrological models as method for improving the description of the regional hydrologic cycle of a watershed by considering the relationships among geophysical and human systems when stressed by both climatic and anthropogenic factors and under long-term time periods. The selected physically-based model is named Soil and Water Assessment Tool -- SWAT, As watershed management is a broad theme involving the consideration of several interconnected systems, such as biogeophysical and socio-economic systems, the dissertation first reviews basic concepts regarding the management of watersheds, the utilisation of hydrological models as tool in supporting the development of integrated watershed management plans, and the presentation of two case studies: i. The first one, named the Venice Lagoon Watershed – VLW, in Italy, consisting in the study of the possible impacts of climate and land-use changes on the availability of water for irrigation water, both in terms of quantity and quality, and; The second case study, focusing in the study of the possible effects of climate and land-use changes on river flood events the Itajaí River Watershed – IRW, in Brazil. In terms of structure the thesis is divided into five chapters: i. The first chapter reviews concepts of watershed management, while introducing hydrological modelling techniques and proposed innovations to be used throughout the dissertation, such as the consideration of the carbon dioxide fertilisation effect due to an increase concentration of carbon dioxide in the atmosphere; ii. The second chapter presents a literature review and a case study describing the uncertainty in employing ANN models in hydrologic systems; iii. The third chapter describes the complexity of the VLW while presenting two case studies evaluating the feasibility of coupling the two considered models (i.e. ANN and SWAT models); iv. The fourth chapter presents the Italian case study, covering the topic of climate change impacts on irrigation water, and; v. The fifth chapter presents the Brazilian case study, covering the topic of climate change effects on river flood risk. The source code of the proposed ANN model and the modifications in the SWAT model are presented as Annex information, as well as a detailed description of the ANN model.

Dans la première partie de cette thèse effectuée en collaboration avec le groupe expérimental de C. Chazaud (Clermont Université), nous avons étudié théoriquement un processus de différenciation cellulaire intervenant avant l’implantation de l’embryon dans l’utérus. Il s’agit de la spécification des cellules de la masse cellulaire interne (MCI) en épiblaste (EPI) et en endoderme primitif (EPr), processus dans lequel les facteurs de transcription Nanog et Gata6 jouent un rôle essentiel. En effet, en absence de Nanog, les cellules de la MCI acquièrent toutes une identité EPr, tandis qu’en absence de Gata6, elles se différencient toutes en EPI. De plus, la voie de signalisation Fgf/Erk active l’expression de Gata6 et inhibe celle de Nanog. Enfin, Nanog active la sécrétion dans le milieu extracellulaire de Fgf4, une molécule qui active la voie de signalisation Fgf/Erk en se liant au FgfR2. Nous avons développé un modèle mathématique pour ce réseau de régulations, fondé sur des équations différentielles ordinaires décrivant l’évolution temporelle des niveaux de protéines Nanog, Gata6, Fgf4 et Fgfr2 et de l’activité de la voie Fgf-Erk. Nous avons validé ce modèle en montrant qu’il récapitule les résultats expérimentaux obtenus in vivo, dans les embryons wild-type et dans les mutants Nanog-/- et Gata6-/-. De plus, l’analyse des résultats du modèle permet de proposer un nouveau mécanisme pour l’émergence d’une population mixte de cellules EPI et EPr au sein de la MCI. Ce mécanisme repose sur le fait que le système décrit par notre modèle peut présenter trois états stationnaires stables, dont les niveaux d’expression de Nanog et Gata6 correspondent à l’EPI, l’EPr et la MCI non-différenciée, respectivement. De plus, le modèle a été utilisé afin d’interpréter des résultats expérimentaux récents et contre-intuitifs, concernant les embryons hétérozygotes Gata6+/-. Enfin, nous avons établi des prédictions théoriques, dont certaines ont été ultérieurement vérifiées en laboratoire. <p>Dans la seconde partie de la thèse, effectuée dans le laboratoire d’O. Pourquié (Université de Strasbourg), nous avons étudié un processus de différenciation in vitro, par une approche expérimentale. Il s’agit de la différenciation des cellules souches embryonnaires (ES) en cellules de mésoderme paraxial, un tissu dont dérivent –au cours du développement embryonnaire– les cellules formant notamment les vertèbres, les côtes, la peau et les muscles squelettiques du dos.<p><br>Doctorat en Sciences agronomiques et ingénierie biologique<br>info:eu-repo/semantics/nonPublished

The development of new cultivars better adapted to specific growing conditions is a key strategy to meet an ever-increasing growing global food demand and search for more sustainable cropping systems. This is even more crucial in the context of a changing climate. Ecophysiological models and advanced computational techniques (e.g., sensitivity analysis, SA) represent powerful tools to analyze genotype (G) by environment (E) interactions, thus supporting breeders in identifying key traits for specific agro-environmental contexts. However, limits for the effective use of mathematical models within breeding programs are represented by the uncertainty in the distribution of plant trait values, the lack of processes dealing with resistance/tolerance traits in most ideotyping studies, the partial suitability of current crop models for ideotyping purposes, and the absence of modelling tools directly usable by breeders. The aim of this research was to address these issues improving methodologies already in use, proposing new paradigms for the development of crop models explicitly targeting ideotyping applications and developing tools that would encourage a deep interaction of the modelling and breeding communities. The focus was on rice, for its role as staple food for more than a half of world’s population, and on resistance/tolerance traits to biotic/abiotic stressors, for their central role in increasing crop adaptation. Moreover, current conditions and climate change projections were considered, to support the definition of strategies for breeding in the medium-long term. A standard procedure to quantify − and manage − the impact of the uncertainty in the distribution of plant trait values was developed, using the WARM rice model and the Sobol’ method as case study. The approach is based on a SA (generating sample of parameter distributions) of a SA (generating samples of parameters for each generated distribution) using distributions of jackknife statistics calculated on literature values to reproduce the uncertainty in defining parameters distributions. As a practical implication, the procedure developed allows identifying plant traits whose uncertainty in distribution can alter ideotyping results, i.e., traits whose distributions could need to be refined. Global SA was then used to identify rice traits putatively producing the largest yield benefits in five contrasting districts in the Philippines, India, China, Japan and Italy. The analysis involved phenotypic traits dealing with light interception, photosynthetic efficiency, tolerance to abiotic stressors, resistance to fungal pathogens and grain quality. Results suggested that breeding for traits involved with disease resistance and tolerance to cold- and heat-induced spikelet sterility could provide benefits similar to those obtained from improving traits affecting potential yield. Instead, advantages resulting from varying traits involved with grain quality were markedly frustrated by inter-annual weather variability. Since results highlighted strong G×E interactions, a new index to derive district-specific ideotypes was developed. Given the key role of biotic/abiotic stressors in determining actual yield and the deep impact of related G×E interactions, a study was carried out by explicitly focusing on the definition of rice ideotypes improved for their resistance to fungal pathogens and tolerance to abiotic constraints (temperature shocks inducing sterility). The analysis was carried out at district level with a high spatial resolution (5 km × 5 km elementary simulation unit), targeting the improvement of the most representative 34 varieties in six Italian rice districts. Genetic improvement was simulated via the introgression of traits from donor varieties. Results clearly showed that breeders should focus on increasing resistance to blast disease, as this appears as a factor markedly limiting rice yields in Italy, regardless of the districts and climate scenarios, whereas benefits deriving from improving tolerance to cold-induced sterility could be markedly affected by G×E interactions. To reduce the risk of discrepancies between in silico ideotypes and their in vivo realizations, both studies involved only model parameters with a close relationship with phenotypic traits breeders are working on. However, a long-term strategy to overcome limitations related with the partial suitability of available models would be building new ideotyping-specific models explicitly around traits involved in breeding programs. This proposal for a paradigm shift in model development was illustrated taking salt stress tolerance and rice as a case study. Dedicated growth chamber experiments were conducted to develop a new model explicitly accounting for tolerance traits modulating Na+ uptake and distribution in plant tissues, as well as the impact of the accumulated Na+ on photosynthesis, senescence and spikelet sterility. An ideotyping study was conducted at two sites (in Greece and California) characterized by different seasonal dynamics of salinity in field water. Results showed how, under different scenarios, traits assuring the largest contribution to the overall tolerance could refer to completely different physiological mechanisms: tissue tolerance in one case, sodium exclusion in the other. This encourages the development of explicit trait-based approaches to increase the integration of crop models within breeding programs. A parallel path to achieve this goal is the development of modelling platforms targeting breeders as final users, who does not have necessarily in-depth skills in crop modelling and IT. The platform ISIde, derived from a close collaboration between target users, biophysical modelers and IT specialists, represents the first prototype of a platform specifically developed for being used directly by breeders to evaluate in silico improved varieties at district level. This thesis demonstrated the usefulness of simulation models for the definition of ideotypes for specific agro-environmental conditions. Targeting ideotyping applications, new methodologies, paradigms for model development and modelling tools were developed, thus contributing to improve the potential of crop modelling to support breeding programs. Future developments will target researches aimed at overcoming the limits behind this study, i.e., (i) absence of explicit interactions between traits, (ii) no adaptation strategies considered, and (iii) lack of approaches for the simulation of the evolutionary potential of pathogens in response to long-term climate variations and increased host resistance.

La coltivazione dei sistemi colturali poliennali su terreni marginali combina la produzione sostenibile di biomassa per diversi utilizzi a benefici di carattere ambientale come il sequestro del C atmosferico nel suolo. La limitata longevità di questi sistemi colturali (10-20 anni), fornisce la possibilità di sfruttarli come una tecnica temporanea per rigenerare la fertilità dei terreni marginali e di studiare il loro effetto nel lungo periodo sul carbonio del suolo. Con questa tesi, avevo l'obiettivo di studiare l'effetto della riconversione a coltura annuali dei sistemi agricoli poliennali sul carbonio del suolo: per raggiungere questo obiettivo, ho combinato ad una meta-analisi di letteratura sull'effetto della riconversione, con un esperimento di campo di lungo periodo, un esperimento di incubazione in laboratorio e l'uso di un modello matematico del carbonio del suolo. L'uso combinato di questi approcci mi ha permesso di mostrare il potenziale che i sistemi colturali poliennali hanno nel sostenere il sequestro del C ne suolo anche dopo la loro riconversione. Quindi i sistemi colturali poliennali sono una pratica sostenibile promettente che può essere integrata in rotazioni agricole di 13 anni sui terreni marginali del nord d'Italia per ripristinare il carbonio del suolo.<br>The cultivation of perennial cropping systems on marginal lands combines the production of sustainable biomass for multiple uses with environmental benefits such as carbon (C) sequestration in soil. In this thesis, we studied the effect of perennial cropping system on soil C considering the scenario of perennial cropping systems reversion to arable land. The limited longevity (10-20 years) of perennial cropping systems, gives the possibility of using these crops as a temporary- option to restore soil fertility of marginal lands and to study the long-term legacy of these cropping systems on soil C. In this thesis I aimed to study the effect of perennial cropping systems reversion to arable land on soil C: to achieve this objective, I combined a literature meta-analysis on the effect of reversion of perennial cropping systems on soil C, with a long-term field experiment on perennial cropping systems, an incubation experiment and the use of a process-based soil C model. The combined use of these approaches gave me the chance to show the potential of perennial cropping systems to support C sequestration even after their reversion. Therefore, perennial cropping systems are a promising sustainable practice which could be integrated on a 13-year agricultural rotation on marginal lands of northern Italy to restore soil C.

La coltivazione dei sistemi colturali poliennali su terreni marginali combina la produzione sostenibile di biomassa per diversi utilizzi a benefici di carattere ambientale come il sequestro del C atmosferico nel suolo. La limitata longevità di questi sistemi colturali (10-20 anni), fornisce la possibilità di sfruttarli come una tecnica temporanea per rigenerare la fertilità dei terreni marginali e di studiare il loro effetto nel lungo periodo sul carbonio del suolo. Con questa tesi, avevo l'obiettivo di studiare l'effetto della riconversione a coltura annuali dei sistemi agricoli poliennali sul carbonio del suolo: per raggiungere questo obiettivo, ho combinato ad una meta-analisi di letteratura sull'effetto della riconversione, con un esperimento di campo di lungo periodo, un esperimento di incubazione in laboratorio e l'uso di un modello matematico del carbonio del suolo. L'uso combinato di questi approcci mi ha permesso di mostrare il potenziale che i sistemi colturali poliennali hanno nel sostenere il sequestro del C ne suolo anche dopo la loro riconversione. Quindi i sistemi colturali poliennali sono una pratica sostenibile promettente che può essere integrata in rotazioni agricole di 13 anni sui terreni marginali del nord d'Italia per ripristinare il carbonio del suolo.<br>The cultivation of perennial cropping systems on marginal lands combines the production of sustainable biomass for multiple uses with environmental benefits such as carbon (C) sequestration in soil. In this thesis, we studied the effect of perennial cropping system on soil C considering the scenario of perennial cropping systems reversion to arable land. The limited longevity (10-20 years) of perennial cropping systems, gives the possibility of using these crops as a temporary- option to restore soil fertility of marginal lands and to study the long-term legacy of these cropping systems on soil C. In this thesis I aimed to study the effect of perennial cropping systems reversion to arable land on soil C: to achieve this objective, I combined a literature meta-analysis on the effect of reversion of perennial cropping systems on soil C, with a long-term field experiment on perennial cropping systems, an incubation experiment and the use of a process-based soil C model. The combined use of these approaches gave me the chance to show the potential of perennial cropping systems to support C sequestration even after their reversion. Therefore, perennial cropping systems are a promising sustainable practice which could be integrated on a 13-year agricultural rotation on marginal lands of northern Italy to restore soil C.

Résumé<p>Afin de mieux comprendre l’anthropisation des paysages au Bénin, la dynamique de l’occupation du<p>sol a été évaluée en zone soudanienne (Nord-Bénin), soudano-guinéenne (Centre-Bénin) et guinéenne (Sud-Bénin) à partir de trois images satellitaires de type Landsat MSS 1972, TM 1986 et ETM+ 2006.<p>Ces trois zones reflètent assez bien le contexte environnemental et humain de la zone intertropicale.<p>L’objectif principal de la présente thèse est de quantifier la dynamique paysagère due à l’anthropisation des paysages de forêts-savanes à partir de la télédétection, du système d’information géographique et de l’écologie du paysage.<p>Nos résultats ont montré que l’équilibre écologique des paysages de forêts-savanes a subi<p>d’importantes perturbations. L’agriculture itinérante sur brûlis, l’exploitation forestière, la carbonisation, l’urbanisation, les feux de végétation et les plantations ont été identifiés comme les principales forces motrices de ces dynamiques. Les matrices paysagères, qui étaient historiquement constituées de forêts-savanes ont été remplacées par une mosaïque de savanes, de champs-jachères, de sols nus-agglomérations, des plantations forestières et fruitières. L’exploitation des données de télédétection a permis de distinguer 4 grands processus de transformation spatiale des classes d’occupation du sol.<p>Ainsi, entre 1972 et 2006, les processus dominants dans le paysage ont été la déforestation, la savanisation, le développement agricole marqué par la création suivie de l’agrandissement des taches de champs-jachères.<p>La quantification des perturbations anthropiques, des indices de la structure spatiale calculés pour<p>chaque classe d’occupation du sol sur la base de la densité, de l’aire moyenne, de la dominance, de<p>l’indice de forme et la dimension fractale des taches des classes a permis de détecter un processus global de fragmentation et d’anthropisation des paysages.<p>Les dynamiques temporelles de la structure et de la composition des paysages de forêts-savanes dans<p>les 3 zones climatiques du Bénin ont montré une anthropisation illustrée surtout par la fragmentation des forêts-savanes. La simulation des dynamiques à l’horizon 2025 à partir de la chaine de Markov de premier degré a montré que pendant que les champs-jachères, plantations et les sols nus-agglomération s’étendront, les forêts-savanes connaîtrons une forte diminution. En définitive, notre étude a mis en évidence que toutes les trois zones étaient fortement dynamiques. Ces transformations anthropiques vont compromettre dangereusement l’avenir de ces paysages dont dépend la survie des populations locales. Notre approche permet de poser les bases d’une politique rationnelle de conservation et d’aménagement des paysages naturelles en établissant des seuils structuraux minimaux des fragments nécessaires à la préservation de la biodiversité.<p><p>Abstract<p>To understand better the landscape anthropization in Benin, the dynamics of the land use was<p>estimated in soudanian zone (North-Benin), soudano-Guinean (Centre-Benin) and guinean (south-<p>Benin) from 3 Landscape satellite images (MSS 1972, TM 1986, and ETM+ 2006), supported by field<p>visits. These 3 zones reflect well enough the environmental and human context of the intertropical zone. The main objective of the present dissertation was to quantify the landscape dynamics due to the landscapes anthropization of forests-savannahs from the Remote Sensing, Geographic Information System and from Landscape Ecology.<p>Our results showed that the ecological balance of the forests-savannahs underwent important<p>disturbances. Slash-and-burn agriculture, logging for timber, carbonization, urbanization, vegetation fire and tree plantations have been identified as the main driving strengths of these dynamics.<p>The landscape matrix’s, which were historically constituted by forests-savannah, has been substituted by a mosaic of savannah, fields-fallows, grounds nudes-urban area and plantations. The use of Remote Sensing data allowed distinguishing four big spatial transformation processes of the land cover classes.<p>So, between 1972 and 2006, the dominant processes in the landscape were the deforestation, the<p>savanization, the agricultural development marked by the creation followed by the enlargement of the<p>spots of field-fallows. The anthropogical disturbances quantification of the spatial structure indications calculated for every land cover classes on the basis of the density, average area, dominance, shape index and the fractal dimension index of the patches classes allowed detecting a global fragmentation<p>process and the anthropization of the landscapes.<p>The temporal dynamics of the structure and composition of the forests-savannahs landscape in the 3 climatic zones area of Benin showed an anthropization illustrated especially by the forest-savannahs fragmentation. The dynamics simulation by 2025 referring to Markov chains of the first degree tendency showed that while fields-fallows, tree plantations and nudes-urban area will extend, forestssavannahs shall know a strong decrease.<p>After all, our study highlighted that every 3 zones were highly disturbed. These anthropogenic<p>transformations are dangerously going to compromise the future of these landscapes on which depends the local populations survival.<p>Our approach allows putting the bases of a rational preservation policy and management natural landscapes by the thresholds establishment of fragments necessary for the biodiversity conservation.<p><p><br>Doctorat en Sciences agronomiques et ingénierie biologique<br>info:eu-repo/semantics/nonPublished

Les travaux de recherche effectués dans le cadre de cette thèse ont été guidés par le manque d’information et une compréhension limitée des mécanismes épidémiologiques à l’origine de l’émergence et de la diffusion de la grippe aviaire hautement pathogène, souche H5N1 en Chine du Sud, aussi reconnue comme l’épicentre potentiel de l’émergence des virus influenza aviaires à caractères pandémiques. <p>Dans ce cadre, des données spatio-temporelles relatives aux foyers de la maladie ainsi que des données de surveillance virologiques (isolement du virus effectué dans le cadre du système de surveillance nationale) ont été collectées sur une période de quatre ans et analysées afin d’éxplorer les facteurs de risque relatifs à l’émergence et persistence de la maladie dans certaine zones de production du sud de la Chine. Les analyses ainsi effectuées ont permis d’identifier, à travers l’utilisation de méthodes statistiques robustes ayant fait leur preuve dans le domaine de la santé ou de l’écologie (la régression logistique classique et les arbres de regression logistique), des facteurs de risque liés à certains types de production de volailles (canards élevés en plein air, zones riches en eau et par extension associées à la riziculture) ou des facteurs associés à l’activité humaine. A travers une représentation cartographique des facteurs ainsi identifiés, des cartes de risque ont été produites permettant ainsi de visualiser d’une part les zones à haut risque de persistence de l’infection virale et d’autre part les zones vulnérables à l’apparition de foyers de la maladie, donnant aux autorités nationales la possibilité de mieux cibler leurs politiques de surveillance et de contrôle. <p>Dans un second temps, notre étude s’est portée sur les marchés à volailles traditionnels du sud de la Chine qui représentent un risque permanent de persistence, d’évolution et de diffusion des virus influenza aviaires, ainsi qu’un risque important en matière de santé publique. La dynamique de ces marchés et les liens qui les unissent ont été étudiés à travers des outils d’analyse empruntés à la sociologie tels que l’Analyse des Réseaux Sociaux (Social Network Analysis). Grace à cette approche, l’importance de l’hygiène de ces marchés et notamment du nettoyage et de la désinfection des cages dans la persistence du virus a été mise en évidence. Enfin, des enquêtes effectuées auprès des vendeurs de volailles ont permis d’identifier l’origine et la destination des animaux vendus et de reconstruire des réseaux plus ou moins intriqués de liens commerciaux qui unissent ces marchés entre eux dans trois provinces du sud de la Chine. L’analyse de ces réseaux et de leurs configurations ont permis d’identifier des marchés à plus haut risque de persistence de l’infection du fait de leur position centrale au sein de ces réseaux. De même qu’il est indispensable de cibler la surveillance et le contrôle de la maladie dans des zones écologiquement favorables à la persistence des virus influenza aviaires, cette étude révèle l’importance de certaines pratiques hygiéniques et commerciales dans la persistence de la maladie et la nécessité de cibler la surveillance et le contrôle au niveau de certains de ces marchés situés au centre d’un réseau dense et connecté, pour pouvoir in fine mieux contrôler la maladie au niveau national.<p><br>Doctorat en Sciences agronomiques et ingénierie biologique<br>info:eu-repo/semantics/nonPublished

There is an extensive debate on the potential environmental impact of dairy farms and in particular the effect of dairy farms on the nitrogen cycle and the effect that this has on ecosystems. Within New Zealand and in particular in the South Island, the expansion of dairying and the adoption of new dairy systems has led to this becoming an increasingly important issue, locally through its effect on water quality and the environment and nationally and internationally through the production of green house gases. Increases in nitrogen usage at the expense of clover nitrogen fixation, irrigation, stocking rate and the introduction of dairy cows onto light free draining soils previously the preserve of arable or sheep farming has led to concern as to the effect intensive pastoral dairying may have on the nitrogen dynamics of the farm and the environment. This study is designed to assess how changes in grazing management in particular changes in pre-grazing and post-grazing residuals alter the clover/ryegrass balance on the farm and the effect that this has on the farm’s nitrogen dynamics. The effects of qualitative changes in grazing management on pasture composition are well established but little is known of the effect of quantitative changes in pasture management on composition, in particular the effect of grazing residuals. There are a number of detailed models of the physiological processes in the energy and nutrient cycling in plants, animals and the soil. There are a smaller number of whole farm models that through integration and simplification of component models attempt to represent the flux of nutrients though a dairy farm. None of these whole farm models is currently able to model the nitrogen flux through a dairy farm at a sufficient level of resolution to capture differences in pasture composition as these occur spatially, temporally and in response to grazing management. This project sought to better understand the nitrogen dynamics on a dairy farm by constructing and then linking component models – a pasture composition and growth model, a cow model, an excretal return model, a soil model and a water balance model – within a whole farm management schedule. The formal null hypothesis is that the mechanistic, mathematical model constructed for this PhD cannot capture and explain the full range of the changes in soil water content, soil nitrogen status, pasture production and composition and animal production, following the alteration in management of the dairy farm between 2002 and 2004. Individual component models were constructed by the author using the computer software package (Matlab) and validated against data extracted from the literature. The models were then converted into one simulation package using C-sharp as the source code language by Elizabeth Post, Senior Computer Scientist at Lincoln Ventures Ltd, Lincoln, New Zealand and the author. This model was then used to investigate the nitrogen dynamics of a dairy farm: the relationship with pasture composition and whether small changes in pasture residuals make a difference to pasture composition and nitrogen dynamics. Two different simulations were run based on the management practice of Lincoln University Dairy farm (LUDF) over two dairy seasons (2002-03 and 2003-04) and validated against the data recorded on this farm. In 2002-03, 50 cows were over wintered and 580 cows were subsequently milked on 200ha. Post grazing residuals where maintained at 1600-1750KgDM/ha. In 2003-04, 125 cows were overwintered and 635 cows were milked on 200ha with post grazing residuals maintained at 1400KgDm/ha. All models operate on a daily time step. Within the pasture model composition is described by 9 state variables describing different components of the pasture and pasture growth is modelled mechanistically from a calculation of component photosynthesis. A further 9 state variables describe the nitrogen composition of the pasture components. The soil model is a variable two layer, mechanistic representation, parametised for the shallow, stony soils of LUDF. Soil water status is an input for the pasture model while water uptake by the growing plants affects the soil water balance within the soil model. Animal intake and production are modelled mechanistically with model cows described in terms of their age, genetic merit, body weight, breed, pregnancy status, conception date and body condition score. Each cow type produces a different quantity of urinary and faecal excretion which varies with dry matter intake, milk yield and the sodium and potassium status of the pasture. Excretal nitrogen composition is predicted within a separate model which calculates daily nitrogen excretion in faeces, urine and milk. Excretions are deposited randomly over the grazed area and account is taken of overlapping excretions that are created on the same day and overlaps that occur with older excretal patches deposited in previous grazing rounds. Each excretal patch has its own associated pasture, water and soil model reflecting the differences in nitrogen status between patches. Grazing preference is expressed within the model between different classes of excretal patch and between excretal patches and the base pasture and between clover and grass. Supplementary silage is conserved and fed according to the management schedule of LUDF. Cows calve, become pregnant and are dried off within the model according to the relevant records from LUDF. Cows are deemed to arrive on the farm on the day of calving and to leave on the day that drying off is finished (a 5 day procedure within the model), except for those cows that are overwintering which remain on the farm. The soil model has multiple nitrogen/carbon pools and is dynamically linked to all the other models. External nitrogen losses from the system are modelled as volatilisation, leaching and denitrification, with pasture nitrogen uptake from the soil model and fixation by clover from the atmosphere. Both the individual component models and the final assembled composite model were successful in matching the available data in terms of pasture and animal production, pasture composition, soil water balance and nitrogen status and external losses. The model indicates that the low residual, high stocking rate farm returns more excreta to the soil. However, this is countered by a reduction in the amount of dead material returned to the paddock and this reduces the relative size of the pool of nitrogen in the dead organic matter. This produces a relative lack of substrate for the soil microbes which are thus unable to exploit all of the nitrogen in the available pool. Soil ammonium and nitrate pools are also increased from the increase in faecal and urinary return so precipitating an immobilising flux from these larger pools to the smaller pool of nitrogen available to the soil microbes. However, the relative inability of the soil bacteria to fully exploit this means that the production of soil organic live matter and the resulting mineralising flux from the dead organic matter pool through the available pool to the ammonium and nitrate pools is reduced. The larger ammonium and nitrate pools will also be associated with increased external losses from the system as denitrification, leaching and volatilisation are increased. The increase in the clover percentage within the sward in 2003-04 led to greater nitrogen fixation and the model suggests that some of the extra nitrogen is effectively captured by the animals in increased production. However, the reduction in the return of dead matter coupled with an increase in excretal return and the consequent increase in the mineral nitrogen pools within the soil lead to greater losses of nitrogen from the soil.

This thesis investigates the suitability of degradable clear polymer film use to support the production of cold-sensitive crops in Tasmania. Film used in this manner is poorly understood and rarely practiced in Australia but is practiced more widely in cold regions of the northern hemisphere. There has been limited agronomic research conducted in the area of film use to assist crop propagation, and contemporary research efforts in this field focus almost exclusively on film chemistry, particularly in the areas of formulation, spectral properties and degradation rate. Authors currently working in this field instead primarily focuses on clear film use for solarisation in summer for weed/pathogen suppression, and the thermal and reflected spectral effects associated with opaque ‘mulch’ film use for weed suppression. In addition to these main areas, there is some exciting work being made coupling novel-spectral absorption properties with changes in rates of pest insect development, but to date this has been focused on greenhouse cladding materials and has not yet made the transition across to clear propagation film. This thesis first explores the effects of film use upon temperature conditions and gaseous substrate composition within the film-enclosed growing area, as well as solar radiation transmission properties of film under Tasmanian field conditions. Film use reduced the transmission of solar radiation into the headspace by 20 % and increased the concentration of water vapour and CO\(_2\) within the film-enclosed headspace. Film use was shown to increase maximum daily temperatures within the film-growing environment. Film use increased minimum daily temperatures by ~4°C between late spring and early autumn, but reduced minimum daily temperatures during other months. Maximum daily temperatures beneath film varied seasonally in response to solar radiation intensity and cloud shading, increasing temperatures by as much as 10 °C above ambient temperatures during winter and 40 °C above ambient temperatures during summer. Models of these environmental changes were developed from ambient climate data, and were incorporated into APSIM to estimate temperatures at other sites from historical climate data. After discussing the climate effects of film use, this thesis explored the effects of film use upon the agronomy and physiology of maize (Zea mays L.), a C4 model crop species and forage source that is sensitive to cold and frost. Film-enclosed chambers were developed to enable establishment and growth of seedlings under different headspace gas compositions. Use of film was shown to improve all aspects of maize seedling performance under cold seasonal conditions. Film use in winter and early spring protected seedlings from exposure to frost and increased soil and air temperatures, leading to earlier, more uniform crop emergence, faster seedling growth, and improved photosynthetic performance. Increases in seedling chlorophyll content, CO\(_2\) assimilation and solar radiation utilisation caused by film use had few persistent effects on maize seedling physiology following removal of the film enclosure. Film use was less beneficial under warmer conditions, causing seedlings to regularly experience acute heat stress when exposed to damaging supra-optimal headspace temperatures above 40 °C. Increased headspace CO\(_2\) concentration ([CO\(_2\)]) had minimal effect on maize emergence, growth rate or leaf carbon assimilation. Information from climate monitoring and physiology experiments was used to inform APSIM modelling to estimate the effect of the film on crop survival and yield in several scenarios. Modelling suggested the production of above-ambient temperature conditions beneath the film favoured earlier planting dates during winter and early spring, with later dates subject to potentially damaging supra-optimal temperatures. Optimal film use was shown to increase simulated maize forage productivity by 10-15 % above existing industry practices in coastal regions. In inland regions, incorporation of film into early-sowing systems greatly reduced maize exposure to frost and subsequent crop failure, and increased long-term crop yields by 7-10 % above existing industry practices. Yields from film-supported production systems reported in this thesis represent conservative estimates only, and potential increases in yield productivity achieved through film use may exceed those reported in this thesis. The results from this indicate that installation of film can create conditions suitable for maize establishment during winter and spring in this cool temperate environment. Extension of the growing season permits flowering and embryogenesis, facilitates the use of longer-season cultivars in cold-affected areas, and enables crop growth to be realigned to better match temperate winter-spring dominant rainfall patterns. Adoption of this technology may improve dryland maize productivity in some cold-limited regions, and reduce seasonal water consumption for existing irrigated maize producers. These benefits may also promote maize cultivation outside of existing coastal production regions in Tasmania.

The experimental work reported in this thesis quantified the productivity of lucerne over a two-year period (2000-2001) for a Mediterranean climate at Roseworthy in South Australia (34°32′S, 138°45′E), and determined associated dynamics for water and nitrogen in duplex soil. Shoot growth of dryland lucerne was limited primarily by the pattern and amount of incident rainfall, but high temperature (30-35oC) also constrained summer production. These high summer temperatures induced greater production when irrigation was applied, but under the normally dry summer conditions high temperatures combined with soil water deficit (up to 200mm) caused growth to cease. Thus, shoot dry matter yield under rainfed conditions was 4.9 t ha⁻¹ in 2000 (from 7 harvests) and 1.8 t ha⁻¹ in 2001 (from 5 harvests) whereas summer irrigation increased yield to 14.9 t ha⁻¹ in 2000 (7 harvests) and 7.1 t ha⁻¹ in 2001 (5 harvests). Under rainfed conditions the RUE was 0.55 g DM MJ⁻¹ PARi compared with 1.08 g DM MJ⁻¹ PARi in the irrigated treatment in 2000, reducing to 0.4 g DM MJ⁻¹ for the rainfed and 0.7 g DM MJ⁻¹ under limited irrigation in 2001. Lucerne plant population declined from 69 to 20 (plants m⁻²) in the rainfed treatment and the plants partially compensated for this in 2000 by increasing stem density from 300 to 400 m⁻² in 2000 although this declined back to 300 m⁻² in 2001. In all treatments more than 70% of root biomass was in the top 40 cm soil, this was partially due to the vertical distribution of plant available water but also to subsoil constraints to root development below 0.6m. Nevertheless, lucerne was able to extract water and nitrate to 1800 mm soil depth. Large amounts of irrigation >400mm) over summer (Dec 1999-Mar 2000) increased total soil water content, approaching the drained upper limit; causing a 600% increase in shoot dry matter yield, similarly higher growth rate (71 kg DM d⁻¹) and higher RUE (~1.7 g DM MJ⁻¹ ), confirming that water availability was the main constraint to lucerne growth. Delayed benefits of summer irrigation, especially in the subsurface treatment, were also observed later (July to October) when lucerne was able to scavenge excess irrigation water and nitrate stored in the 600-1800 mm soil profile, which resulted in increased shoot growth. Drainage below the effective rooting depth was negligible, even under irrigation, confirming that lucerne can dry soil profiles and reduce deep drainage. Average annual water use efficiency was 9 kg DM ha⁻¹ mm⁻¹ under rainfed conditions compared to ~15 kg DM ha⁻¹ mm⁻¹ under irrigated conditions. Shoot dry mattter production was closely related to evapotranspiration in all treatments, however, under rainfed conditions losses from evaporation were proportionally higher compared to irrigated treatments. Sub-surface drip irrigation proved superior to surface irrigation using 22% less water compared to surface sprinkler irrigation treatment with comparable yields. Biological N₂fixation was strongly related to shoot production with 18 to 27 kg N fixed per tonne of shoot dry matter across all seasons and treatments. Dependence on N₂fixation appeared to be unrelated to soil mineral N concentration and amounts of nitrate in the profile (to 1m) were generally quite low <35 kg N ha⁻¹). Soil water dynamics under both rainfed and surface irrigated treatments were adequately simulated by the Agricultural Production System Simulator (APSIM) with RMSD < 10% of the observed means and R² > 0.80 for the total soil profile (0-2000 mm). Simulation of growth and development was less satisfactory. For example, the RMSD was ~50% of observed mean for shoot biomass (R² = 0.68) in the rainfed treatment, and 36% (R² = 0.77) in the irrigated treatment. Overall, simulation of shoot DM production was close to observed values during the growing season (Apr-Nov), however the model was unable to capture the observed shoot yield in response to summer irrigation, with simulated shoot DM 40% less than the observed value in 2000 and 35% less in 2001. N dynamics were poorly simulated under these soil and climate conditions. Amounts of soil mineral nitrogen (kg NO⁻₃-N ha⁻¹) were adequately simulated in rainfed conditions but consistently over-predicted under irrigated conditions. This evaluation of APSIM highlights both good and poor model performance and the analysis indicates the need for caution when applying the model in situations where observed data is scarce. Areas requiring improvements to the model are identified. Overall this research has improved understanding of the limitations to potential production of lucerne in a Mediterranean environment on duplex soils and shown that APSIM-Lucerne can be used confidently for many applications, particularly soil-water dynamics.<br>http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1352515<br>Thesis (Ph.D.) - University of Adelaide, School of Earth and Environmental Sciences, 2009

This research work concentrate on developing digital soil maps to support field based plant phenotyping research. We have developed soil organic matter content (OM), cation exchange capacity (CEC), natural soil drainage class, and tile drainage line maps using topographic indices and aerial imagery. Various prediction models (universal kriging, cubist, random forest, C5.0, artificial neural network, and multinomial logistic regression) were used to estimate the soil properties of interest.

<div>The demand for customized farm management prescription is increasing in order to maximize crop yield and minimize environmental risks under a changing climate. One great challenge to modeling crop growth and production is spatial and temporal variability. The goal of this dissertation research is to use publicly available Landsat imagery, ground samples and historical yield data to establish methodologies to spatially quantify cover crop growth and in-season maize yield. First, an investigation was conducted into the feasibility of using satellite remote sensing and spatial interpolation with minimal ground samples to rapidly estimate season-specific cover crop biomass and N uptake in the small watershed of Lake Bloomington in Illinois. Results from this study demonstrated that remote sensing indices could capture the spatial pattern of cover crop growth as affected by various cover crop and cash crop management systems. Soil adjusted vegetation index (SAVI), enhanced vegetation index (EVI) and triangular vegetation index (TVI) were strongly correlated with cover crop biomass and N uptake for low and moderate biomass and N uptake ranges (0-3000 kg ha-1 and 0-100 kg N ha-1). The SAVI estimated cover crop biomass and N uptake were +/- 15% of observed value. Compared to commonly used spatial interpolation methods such as ordinary kriging (OK) and inverse distance weighting (IDW), using the SAVI method showed higher prediction R2 values than that of OK and IDW. An additional advantage for these remote sensing vegetation indices, especially in the context of diverse agronomic management practices, is their much lower labor requirements compared to the high density ground samples needed for a spatial interpolation analysis. </div><div>In the second study, a new approach using the multivariate spatial autoregressive (MSAR) model was developed at 10-m grid resolution to forecast maize yield using historical grain yield data collected at farmers’ fields in Central Indiana, publicly available Landsat imagery, top 30 cm soil organic matter and elevation, while accounting for yield spatial autocorrelation. Relative mean error (RME) and relative mean absolute error (RMAE) were used to quantify the model prediction accuracy at the field level and 10-m grid level, respectively. The MSAR model performed reasonably well (absolute RME < 15%) for field overall yield predictions in 32 out of 35 site-years on the calibration dataset with an average absolute RME of 6.6%. The average RMAE of the MSAR model predictions was 13.1%. It was found that the MSAR model could result in large estimation error under an extreme stressed environment such as the 2012 drought, especially when grain yield under these stressed conditions was not included in the model calibration step. In the validation dataset (n=82), the MSAR model showed good prediction accuracy overall (± 15% of actual yield in 56 site-years) in new fields when extreme stress was not present. The novel approach developed in this study demonstrated its ability to use elevation and soil information to interpret satellite observations accurately in a fine spatial scale. </div><div>Then we incorporated the MSAR approach into a process-based N transformation model to predict field-scale maize yield in Indiana. Our results showed that the linear agreement of predicted yield (using the N Model in the Mapwindow GIS + MMP Tools) to actual yield improved as the spatial aggregation scale became broader. The proposed MSAR model used early vegetative precipitation, top 30 cm soil organic matter and elevation to adjust the N Model yield prediction in 10-m grids. The MSAR adjusted yield predictions resulted in more cases (77%) that fell within 15% of actual yield compared to the N Model alone using the calibration dataset (n=35). However, if the 2012 data was not included in the MSAR parameter training step, the MSAR adjusted yield predictions for 2012 were not improved from the N Model prediction (average RME of 24.1%). When extrapolating the MSAR parameters developed from 7 fields to a dataset containing 82 site-years on 30 different fields in the same region, the improvement from the MSAR adjustment was not significant. The lack of improvement from the MSAR adjustment could be because the relationship used in the MSAR model was location specific. Additionally, the uncertainty of precipitation data could also affect the relationship. </div><div>Through the sequence of these studies, the potential utility of big data routinely collected at farmers’ fields and publicly available satellite imagery has been greatly improved for field-specific management tools and on-farm decision-making. </div>

Much older soils data and soils information lies idle in libraries and archives and is largely unused, especially in developing countries like Kenya. We demonstrated the usefulness of a stepwise approach to bring legacy soils data ‘back to life’ using the 1980 <i>Reconnaissance Soil Map of the Busia Area</i> <i>(quarter degree sheet No. 101)</i> in western Kenya as an example. Three studies were conducted by using agronomic information, field observations, and laboratory data available in the published soil survey report as inputs to several digital soil mapping techniques. In the first study, the agronomic information in the survey report was interpreted to generate 10 land quality maps. The maps represented the ability of the land to perform specific agronomic functions. Nineteen crop suitability maps that were not previously available were also generated. In the second study, a dataset of 76 profile points mined from the survey report was used as input to three spatial prediction models for soil organic carbon (SOC) and texture. The three predictions models were (i) ordinary kriging, (ii) stepwise multiple linear regression, and (iii) the Soil Land Inference Model (SoLIM). Statistically, ordinary kriging performed better than SoLIM and stepwise multiple linear regression in predicting SOC (RMSE = 0.02), clay (RMSE = 0.32), and silt (RMSE = 0.10), whereas stepwise multiple linear regression performed better than SoLIM and ordinary kriging for predicting sand content (RSME = 0.11). Ordinary kriging had the narrowest 95% confidence interval while stepwise multiple linear regression had, the widest. From a pedological standpoint, SoLIM conformed better to the soil forming factors model than ordinary kriging and had a narrower confidence interval compared to stepwise multiple linear regression. In the third study, rules generated from the map legend and map unit descriptions were used to generate a soil class map. Information about soil distribution and parent material from the map unit polygon descriptions were combined with six terrain attributes, to generate a disaggregated fuzzy soil class map. The terrain attributes were multiresolution ridgetop flatness (MRRTF), multiresolution valley bottom flatness (MRVBF), topographic wetness index (TWI), topographic position index (TPI), planform curvature, and profile curvature. The final result was a soil class map with a spatial resolution of 30 m, an overall accuracy of 58% and a Kappa coefficient of 0.54. Motivated by the wealth of soil agronomic information generated by this study, we successfully tested the feasibility of delivering this information in rural western Kenya using the cell phone-based Soil Explorer app (<a href="https://soilexplorer.net/">https://soilexplorer.net/</a>). This study demonstrates that legacy soil data can play a critical role in providing sustainable solutions to some of the most pressing agronomic challenges currently facing Kenya and most African countries.<div><p></p></div>