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Momsen, Eric. "Vector-Vector Patterns for Agricultural Data." Thesis, North Dakota State University, 2013. https://hdl.handle.net/10365/27040.
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Agriculture is increasingly driven by massive data, and some challenges are not covered by existing statistics, machine learning, or data mining techniques. Many crops are characterized not only by yield but also by quality measures, such as sugar content and sugar lost to molasses for sugarbeets. The set of features furthermore contains time series data, such as rainfall and periodic satellite imagery. This study examines the problem of identifying relationships in a complex data set, in which there are vectors (multiple attributes) for both the explanatory and response conditions. This problem can be characterized as a vector-vector pattern mining problem. The proposed algorithm uses one of the vector representations to determine the neighbors of a randomly picked instance, and then tests the randomness of that subset within the other vector representation. Compared to conventional approaches, the vector-vector algorithm shows better performance for distinguishing existing relationships.National Science Foundation Partnerships for Innovation program Grant No. 1114363
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Koyuncu, Atayil. "Acquisition Of Field Data For Agricultural Tractor." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/2/12607237/index.pdf.
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During the operations of an agricultural tractor, front axle and front axle support encounter the worst load conditions of the whole tractor. If the design of these components is not verified by systematic engineering approach, the customers could face with sudden failures. Erkunt Agricultural Machinery
Company, which is located in Ankara, has newly designed and manufactured the front axle support of its agricultural tractors. In this study, the design of 2WD (Wheel Drive) Erkunt Bereket Agricultural Tractor’
s front axle support has been verified by developing a verification method, which involves testing the tractor on a special test track and field and together with the computer aided engineering analysis, in order to prevent such failures in the lifetime of the tractor. For this purpose, a strain gage data acquisition system has been designed to measure the strain values on the component, while the tractor is operating on a test track and field. The locations of the strain gages have been determined by simulating the selected design load cases through finite element method. Measuring the maximum strains for the front axle support that have been experienced by the tractor while operating, the stress values have been calculated and the design safety has been investigated considering the material&
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s tensile strength. Secondly, the fatigue life of the component regarding the acquired strain data has been predicted. These processes have led the company to verify the design of the front axle support.
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Xu, Xing John. "Multi-Variate Attribute Selection for Agricultural Data." Thesis, North Dakota State University, 2015. https://hdl.handle.net/10365/27612.
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Farmers always have been concerned about the quantity of crops (yield) as well as
the quality of crops (sugar content of the sugar beets). The quality and quantity of crops
are affected by various attributes, some are natural elements (rain, sunshine etc) and some
are not (the amount of fertilizer, seed type etc). Some techniques have been developed to
discover attributes that are important to different crops? yield. But within those selected
attributes, how can we tell one attribute is more important than the other? The proposed
algorithm is aimed to utilize the advantages of multiple response attributes to select the
important attributes and then put the selected attributes in a hierarchical order. Although
at the end this paper only focuses on yield prediction, any other target attribute can be a
candidate for the prediction model.Grant No. 1114363 from National Science Foundation
4
Chaddad, Fabio R. "Financial constraints in U.S. agricultural cooperatives : theory and panel data econometric evidence /." free to MU campus, to others for purchase, 2001. http://wwwlib.umi.com/cr/mo/fullcit?p3036812.
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Lawal, Najib. "Modelling and multivariate data analysis of agricultural systems." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/modelling-and-multivariate-data-analysis-of-agricultural-systems(f6b86e69-5cff-4ffb-a696-418662ecd694).html.
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The broader research area investigated during this programme was conceived from a goal to contribute towards solving the challenge of food security in the 21st century through the reduction of crop loss and minimisation of fungicide use. This is aimed to be achieved through the introduction of an empirical approach to agricultural disease monitoring. In line with this, the SYIELD project, initiated by a consortium involving University of Manchester and Syngenta, among others, proposed a novel biosensor design that can electrochemically detect viable airborne pathogens by exploiting the biology of plant-pathogen interaction. This approach offers improvement on the inefficient and largely experimental methods currently used. Within this context, this PhD focused on the adoption of multidisciplinary methods to address three key objectives that are central to the success of the SYIELD project: local spore ingress near canopies, the evaluation of a suitable model that can describe spore transport, and multivariate analysis of the potential monitoring network built from these biosensors. The local transport of spores was first investigated by carrying out a field trial experiment at Rothamsted Research UK in order to investigate spore ingress in OSR canopies, generate reliable data for testing the prototype biosensor, and evaluate a trajectory model. During the experiment, spores were air-sampled and quantified using established manual detection methods. Results showed that the manual methods, such as colourimetric detection are more sensitive than the proposed biosensor, suggesting the proxy measurement mechanism used by the biosensor may not be reliable in live deployments where spores are likely to be contaminated by impurities and other inhibitors of oxalic acid production. Spores quantified using the more reliable quantitative Polymerase Chain Reaction proved informative and provided novel of data of high experimental value. The dispersal of this data was found to fit a power decay law, a finding that is consistent with experiments in other crops. In the second area investigated, a 3D backward Lagrangian Stochastic model was parameterised and evaluated with the field trial data. The bLS model, parameterised with Monin-Obukhov Similarity Theory (MOST) variables showed good agreement with experimental data and compared favourably in terms of performance statistics with a recent application of an LS model in a maize canopy. Results obtained from the model were found to be more accurate above the canopy than below it. This was attributed to a higher error during initialisation of release velocities below the canopy. Overall, the bLS model performed well and demonstrated suitability for adoption in estimating above-canopy spore concentration profiles which can further be used for designing efficient deployment strategies. The final area of focus was the monitoring of a potential biosensor network. A novel framework based on Multivariate Statistical Process Control concepts was proposed and applied to data from a pollution-monitoring network. The main limitation of traditional MSPC in spatial data applications was identified as a lack of spatial awareness by the PCA model when considering correlation breakdowns caused by an incoming erroneous observation. This resulted in misclassification of healthy measurements as erroneous. The proposed Kriging-augmented MSPC approach was able to incorporate this capability and significantly reduce the number of false alarms.
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Reynolds, Curt Andrew 1960. "Estimating crop yields by integrating the FAO crop specific water balance model with real-time satellite data and ground-based ancillary data." Thesis, The University of Arizona, 1998. http://hdl.handle.net/10150/192102.
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The broad objective of this research was to develop a spatial model which provides both timely and quantitative regional maize yield estimates for real-time Early Warning Systems (EWS) by integrating satellite data with groundbased ancillary data. The Food and Agriculture Organization (FAO) Crop Specific Water Balance (CSWB) model was modified by using the real-time spatial data that include: dekad (ten-day) estimated rainfall (RFE) and Normalized Difference Vegetation Index (NDVI) composites derived from the METEOSAT and NOAA-AVHRR satellites, respectively; ground-based dekad potential evapo-transpiration (PET) data and seasonal estimated area-planted data provided by the Government of Kenya (GoK). A Geographical Information System (GIS) software was utilized to: drive the crop yield model; manage the spatial and temporal variability of the satellite images; interpolate between ground-based potential evapotranspiration and rainfall measurements; and import ancillary data such as soil maps, administrative boundaries, etc.. In addition, agro-ecological zones, length of growing season, and crop production functions, as defined by the FAO, were utilized to estimate quantitative maize yields. The GIS-based CSWB model was developed for three different resolutions: agro-ecological zone (AEZ) polygons; 7.6-kilometer pixels; and 1.1-kilometer pixels. The model was validated by comparing model production estimates from archived satellite and agro-meteorological data to historical district maize production reports from two Kenya government agencies, the Ministry of Agriculture (MoA) and the Department of Resource Surveys and Remote Sensing (DRSRS). For the AEZ analysis, comparison of model district maize production results and district maize production estimates from the MoA (1989-1997) and the DRSRS (1989-1993) revealed correlation coefficients of 0.94 and 0.93, respectively. The comparison for the 7.6-kilometer analysis showed correlation coefficients of 0.95 and 0.94, respectively. Comparison of results from the 1.1-kilometer model with district maize production data from the MoA (1993-1997) gave a correlation coefficient of 0.94. These results indicate the 7.6-kilometer pixel-by-pixel analysis is the most favorable method. Recommendations to improve the model are finer resolution images for area planted, soil moisture storage, and RFE maps; and measuring the actual length of growing season from a satellite-derived Growing Degree Day product.
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Jones, Brenda M., and n/a. "Digging up data: a reanalysis of so called �horticultural� tools." University of Otago. Department of Anthropology, 1999. http://adt.otago.ac.nz./public/adt-NZDU20070523.153015.
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Elsdon Best�s 1925 work Maori Agriculture has been influential in New Zealand archaeology impacting on the terminology and assumed functions applied to so called �horticultural� implements retrieved in excavations, as well as those in museums and private collections. This thesis critically examines Best�s horticultural tool classification and the decisions he made with regards to tool function. Ethnographic accounts are investigated in an effort to understand how and why Best selected the terms and functions that he did. The literature review reveals anomalies in the conclusions that Best drew and the morphology of the tools that he described, highlighting the lack of order and confusion surrounding horticultural tool function, terminology and morphology, and prompting a much needed reassessment of horticultural implements.
A study of artefacts from New Zealand museums was undertaken with the aim of generating two typologies for so called �horticultural� tools. The artefacts are classified to specific types using specified attributes, and following the classification process, are investigated for metric and non-metric variables that are indicative of the tool�s function. Graphical and basic statistical analyses revealed largely unimodal distributions for the metric attributes recorded for each tool type. Non-metric qualities also displayed a uniformity to their occurrence within the individual types.
The data for each type is discussed with regards to tool function, combining the results of the attribute analyses with comparable tool morphologies from other Pacific cultures. The distribution of tool types in prehistoric New Zealand is also investigated in an effort to elucidate tool function.
This investigation highlights the artefacts as earth-working implements, disestablishing the restricted horticultural context which for so long has been associated with such tools.
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Smith, Derik Lafayette, and Satya Prakash Dhavala. "Using big data for decisions in agricultural supply chain." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/81106.
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Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 53-54).
Agriculture is an industry where historical and current data abound. This paper investigates the numerous data sources available in the agricultural field and analyzes them for usage in supply chain improvement. We identified certain applicable data and investigated methods of using this data to make better supply chain decisions within the agricultural chemical distribution chain. We identified a specific product, AgChem, for this study. AgChem, like many agricultural chemicals, is forecasted and produced months in advance of a very short sales window. With improved demand forecasting based on abundantly-available data, Dow AgroSciences, the manufacturer of AgChem, can make better production and distribution decisions. We analyzed various data to identify factors that influence AgChem sales. Many of these factors relate to corn production since AgChem is generally used with corn crops. Using regression models, we identified leading indicators that assist to forecast future demand of the product. We developed three regressions models to forecast demand on various horizons. The first model identified that the price of corn and price of fertilizer affect the annual, nation-wide demand for the product. The second model explains expected geographic distribution of this annual demand. It shows that the number of retailers in an area is correlated to the total annual demand in that area. The model also quantifies the relationship between the sales in the first few weeks of the season, and the total sales for the season. And the third model serves as a short-term, demand-sensing tool to predict the timing of the demand within certain geographies. We found that weather conditions and the timing of harvest affect when AgChem sales occur. With these models, Dow AgroSciences has a better understanding of how external factors influence the sale of AgChem. With this new understanding, they can make better decisions about the distribution of the product and position inventory in a timely manner at the source of demand.
by Derik Lafayette Smith and Satya Prakash Dhavala.
M.Eng.in Logistics
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Catney, Denise Catherine. "Mathematical modelling of abbatoir condemnation data." Thesis, Queen's University Belfast, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388044.
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Dlamini, Luleka. "Exploring the potential of using remote sensing data to model agricultural systems in data-limited areas." Master's thesis, Faculty of Science, 2020. http://hdl.handle.net/11427/32239.
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Crop models (CMs) can be a key component in addressing issues of global food security as they can be used to monitor and improve crop production. Regardless of their wide utilization, the employment of these models, particularly in isolated and rural areas, is often limited by the lack of reliable input data. This data scarcity increases uncertainties in model outputs. Nevertheless, some of these uncertainties can be mitigated by integrating remotely sensed data into the CMs. As such, increasing efforts are being made globally to integrate remotely sensed data into CMs to improve their overall performance and use. However, very few such studies have been done in South Africa. Therefore, this research assesses how well a crop model assimilated with remotely sensed data compares with a model calibrated with actual ground data (Maize_control). Ultimately leading to improved local cropping systems knowledge and the capacity to use CMs. As such, the study calibrated the DSSAT-CERES-Maize model using two generic soils (i.e. heavy clay soil and medium sandy soil) which were selected based on literature, to measure soil moisture from 1985 to 2015 in Bloemfontein. Using the data assimilation approach, the model's soil parameters were then adjusted based on remotely sensed soil moisture (SM) observations. The observed improvement was mainly assessed through the lens of SM simulations from the original generic set up to the final remotely sensed informed soil profile set up. The study also gave some measure of comparison with Maize_control and finally explored the impacts of this specific SM improvement on evapotranspiration (ET) and maize yield. The result shows that when compared to the observed data, assimilating remotely sensed data with the model significantly improved the mean simulation of SM while maintaining the representation of its variability. The improved SM, as a result of assimilation of remotely sensed data, closely compares with the Maize_control in terms of mean but there was no improvement in terms of variability. Data assimilation also improved the mean and variability of ET simulation when compared that of Maize_control, but only with heavy clay soil. However, maize yield was not improved in comparison. This confirms that these outputs were influenced by other factors aside from SM or the soil profile parameters. It was concluded that remote sensing data can be used to bias correct model inputs, thus improve certain model outputs.
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Mello, Marcio Pupin. "Spectral-temporal and Bayesian methods for agricultural remote sensing data analysis." Instituto Nacional de Pesquisas Espaciais (INPE), 2013. http://urlib.net/sid.inpe.br/mtc-m19/2013/09.17.18.58.
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Informações agrícolas confiáveis tem se tornado cada vez mais importantes para os tomadores de decisões. Especialmente quando são obtidas em tempo hábil, essas informações são altamente relevantes para o planejamento estratégico do país. Apesar de o sensoriamento remoto mostrar-se promissor para aplicações em mapeamento agrícola, com potencial de melhorar as estatísticas agrícolas oficiais, esse potencial não tem sido amplamente explorado. Existem poucos exemplos bem sucedidos do uso operacional do sensoriamento remoto para mapeamento sistemático de culturas agrícolas e, para garantir resultados precisos, eles são fortemente baseados em interpretação visual de imagens. De fato, apesar dos substanciais avanços em análise de dados de sensoriamento remoto, novas técnicas para automatizar a análise de dados em sensoriamento remoto com aplicações agrícolas são desejáveis, especialmente no propósito de manter a consistência e a precisão dos resultados. Neste contexto, existe uma demanda crescente pelo desenvolvimento e implementação de métodos automatizados de análise de dados de sensoriamento remoto com aplicações em agricultura. Assim, o principal objetivo desta tese é propor o desenvolvimento e a implementação de métodos para automatizar a análise de dados de sensoriamento remoto em aplicações agrícolas, com foco na consistência e precisão dos resultados. Este documento foi escrito como uma coleção de dois artigos, cada um com foco nos seguintes pontos: (i) análise multitemporal, multiespectral e multisensor, permitindo a descrição das variações espectrais de alvos agrícolas ao longo do tempo; e (ii) inteligência artificial na modelagem de fenômenos usando dados de sensoriamento remoto e informações complementares de maneira integrada. Dois estudos de caso referentes ao mapeamento da colheita da cana em São Paulo e ao mapeamento da soja no Mato Grosso foram usados para testar as metodologias batizadas de STARS e BayNeRD, respectivamente. Os resultados dos testes confirmaram que ambos os métodos propostos foram capazes de automatizar processos de análises de dados de sensoriamento remoto com aplicações agrícolas, com consistência e precisão.Reliable agricultural statistics has become increasingly important to decision makers. Especially when timely obtained, agricultural information is highly relevant to the strategic planning of the country. Although remote sensing shows to be of great potential for agricultural mapping applications, with the benefit of further improving official agricultural statistics, its potential has not been fully explored. There are very few successful examples of operational remote sensing application for systematic mapping of agricultural crops, and they are strongly supported by visual image interpretation to allow accurate results. Indeed, despite the substantial advances in remote sensing data analysis, techniques to automate remote sensing data analysis focusing on agricultural mapping applications are highly valuable but have to maintain consistency and accuracy. In this context, there continues to be a demand for development and implementation of computer aided methods to automate the processes of analyzing remote sensing datasets for agriculture applications. Thus, the main objective of this thesis is to propose implementation of computer aided methodologies to automate, maintaining consistency and accuracy, processes of remote sensing data analyses focused on agricultural thematic mapping applications. This thesis was written as a collection of two papers related to a core theme, each addressing the following main points: (i) multitemporal, multispectral and multisensor image analysis that allow the description of spectral changes of agricultural targets over time; and (ii) artificial intelligence in modeling phenomena using remote sensing and ancillary data. Study cases of sugarcane harvest in São Paulo and soybean mapping in Mato Grosso were used to test the proposed methods named STARS and BayNeRD, respectively. The two methods developed and tested confirm that remotely sensed (and ancillary) data analysis can be automated with computer aided methods to model a range of cropland phenomena for agriculture applications, maintaining consistency and accuracy.
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Moreno-Urquiza, Magdalena 1967. "Intelligent data acquisition system for continuous measurements of soil moisture in the field." Thesis, The University of Arizona, 1993. http://hdl.handle.net/10150/278271.
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A data acquisition system to collect soil moisture readings at 60 field locations was developed. The system predicted a resistance value from a measured counts per time. An error was associated with the measured counts and time, however, this error was minimized by increasing the time for resistance measurement. The effect of temperature was minimized by an automatic calibration of the system before collecting readings. The Watermark electrical resistance moisture sensor was used to sense water content. The system, including eight sensors, was tested in the field. The data collected was difficult to explain. An evaluation of the Watermark sensors indicated a large variation from sensor to sensor, and also indicated a marked influence of soil texture on sensor resistance.
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Schemper, Janel K. "Efficiency of combine usage: a study of combine data comparing operators and combines to maximize efficiency." Thesis, Kansas State University, 2014. http://hdl.handle.net/2097/17738.
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Master of AgribusinessDepartment of Agricultural Economics
Vincent Amanor-Boadu
Farming is an important industry in the United States. The custom harvesting industry plays a major role in feeding the world. Schemper Harvesting is a family-owned and operated custom harvesting service that employs 20-25 seasonal workers and understanding how to manage a custom harvesting business professionally and efficiently is the key for its success. Today, there is data available through JDLink on John Deere combine performance beginning in year 2012. The purpose of this study is to examine the usefulness of this JDLink data to assess the efficiency of each of Schemper Harvesting’s seven combines, including machine efficiency and different combine operators. The goal is to determine how the data can improve Schemper Harvesting’s overall performance. Statistical methods were used to analyze Schemper Harvesting’s performance. The analysis indicated that fuel is a major expense and there are ways Schemper Harvesting can conserve fuel. This information may prove valuable in being able to operate a combine more efficiently and save money on expenses. Overall, the objective is to improve Schemper Harvesting’s performance, which results in higher profit without sacrificing quality. Precision technology is an added expense to the business. Being able to justify this expense with profit is the answer. Fuel, labor and machinery are the biggest inputs in the custom harvesting business. These costs related to production agriculture have increased the demand for precision agriculture to increase efficiency and profitability. In order to compensate for the investment in technology, it has been demonstrated that it pays for itself. Making correct use of precision technology adds to productivity. With experience, operators improve increasing their overall efficiency. Incentive plans can be utilized through this data. With the availability of data, the costs and benefits of precision technology can be further evaluated. Five of the seven combines are operated by family members and the other two by non-family employees. This study shows that the performance of the non-family employees was below that of family members. The initial assessment for this difference may be attributed to experience because all the family members have been operating combines for most of their lives. This implies that employing people with excellent performance experience records and/or a need to train non-family employees to help them understand the performance expectations at Schemper Harvesting. The results indicate that tracking operational output performance indicators, such as acreage and volume harvest should be completed so that they may be assessed in concert with the technical indicators such as time and fuel use. The study provides the potential benefits of using John Deere’s JDLink data service providing telematics information for its customers with the latest precision agriculture technologies.
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Assoumou, Ebo Etienne 1956. "Comparison of field furrow data to predictions made with a hydrodynamic model." Thesis, The University of Arizona, 1990. http://hdl.handle.net/10150/277317.
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Field data were taken on furrow irrigations and compared with a hydrodynamic model (SRFR) which was used to predict irrigation performance. The field data were the furrow shape and slope, the infiltration characteristics of the furrow, the initial and final moisture content of the furrow, the rate and time of inflow, and the advance and recession trajectories. The hydrodynamic model predicted well the advance trajectories. It predicted recession trajectories which coincided with those of the field measurements for the upper end of the furrow but varied from the field measurements for the lower end. On the average, the uniformities calculated from observed data were higher than those predicted by the model. On the average, irrigation efficiencies calculated from field measurements were higher than those calculated with the model. Storage efficiencies for the observed data were all 100 percent because all irrigations completely met the requirement.
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Moolman, Christina Elizabeth. "Modeling the marginal revenue of water in selected agricultural commodities a panel data approach /." Diss., Pretoria : [s.n.], 2005. http://upetd.up.ac.za/thesis/available/etd-09162005-094852.
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Urganci, Ilksen. "Positional Uncertainty Analysis Using Data Uncertainy Engine A Case Study On Agricultural Land Parcels." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/3/12611409/index.pdf.
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Most of spatial data extraction and updating procedures require digitization of geographical entities from satellite imagery. During digitization, errors are introduced by factors like instrument deficiencies or user errors. In this study positional uncertainty of geographical objects, digitized from high resolution Quickbird satellite imagery, is assessed using Data Uncertainty Engine (DUE). It is a software tool for assessing uncertainties in environmental dataand generating realisations of uncertain data for use in uncertainty propagation analyses. A case study area in Kocaeli, Turkey that mostly includes agricultural land parcels is selected in order to evaluate positional uncertainty and obtain uncertainty boundaries for manually digitized fields. Geostatistical evaluation of discrepancy between reference data and digitized polygons are undertaken to analyse auto and cross correlation structures of errors. This process is utilized in order to estimate error model parameters which are employed in defining an uncertainty model within DUE. Error model parameters obtained from training data, are used to generate simulations for test data. Realisations of data derived via Monte Carlo Simulation using DUE, are evaluated to generate uncertainty boundaries for each object guiding user for further analyses with pre-defined information related to the accuracy of spatial entities. It is also aimed to assess area uncertainties affected by the position of spatial entities. For all different correlation structures and object models, weighted average positional error for this study is between 2.66 to 2.91 meters. At the end of uncertainty analysis, deformable object model produced the smallest uncertainty bandwidth by modelling cross correlation.
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Aucott, Lorna S. "Statistical analysis of near infra-red reflectance data." Thesis, University of Aberdeen, 1990. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU045678.
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Near Infra-red (NIR) reflectance spectroscopy is an instrumental technique to analyse the chemical composition (eg. nitrogen content) of organic materials. As an approach it is rapid, accurate and hence cost effective. Composition is currently determined by calibration equations which relate traditional wet chemical measurements to NIR spectral measurements for the same sample. This thesis examines statistical methods of estimating composition from the NIR spectra and suggests new methods. The relative merits of each of the methods is described. Variation within the spectra is also affected by physical attributes like particle size. Several transformations are examined for their ability to reduce non-chemical differences. These include some transformations previously found to be useful and also some new approaches. Methods of calibration are then investigated. Of the 'standard* methods, stepwise multiple linear regression, principal component regression, latent root regression and partial least squares are discussed. In addition, some new methods are considered. Firstly, three new calibration models are derived which, like some of the 'standard' methods, use information from the whole spectra. Next is a slightly different approach, whereby only the information from informative areas of the spectra, called 'windows', are used for calibration. Finally, hierarchical models for combining information from different sample sets in a flexible way are considered and adapted for NIR data types.
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Zhuo, Shuai He. "Agricultural productivity growth in chinese economy : a provincial panel data analysis after 1980." Thesis, University of Macau, 2008. http://umaclib3.umac.mo/record=b1783730.
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Kumar, Vijendra. "Prediction of agricultural drought for the Canadian prairies using climatic and satelllite data." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0019/NQ45005.pdf.
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Atici, Kazim Baris. "Using data envelopment analysis for the efficiency and elasticity evaluation of agricultural farms." Thesis, University of Warwick, 2012. http://wrap.warwick.ac.uk/54354/.
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Data Envelopment Analysis (DEA) is a well-established relative efficiency measurement technique, which has been widely applied to evaluate the technical efficiency of agricultural units in different countries by focusing on different aspects of agricultural production. This research deals with the evaluation of efficiency through DEA in non-homogeneous agricultural production, where units produce a wide range of different outputs. The objectives are threefold. Firstly, we propose a novel methodological approach of integrating the production trade-offs concept of DEA into non-homogeneous agricultural efficiency evaluation to prevent the overstatement of the efficiency of specialist farms and overcome the issue of insufficient discrimination due to large number of outputs in the models. Secondly, we aim to integrate this methodological perspective to the theory of elasticity measurement on DEA frontiers. The efficient frontiers of DEA are not defined in functional forms as in the classical economic theory, therefore obtaining elasticity measures on them require different considerations. We introduce the production trade-offs to the elasticity measurement and derive the necessary models to calculate the elasticities of response in the presence of production trade-offs. As a third objective, before moving to the introduction of the trade-offs in elasticity measurement, for theoretical completeness, we first consider the elasticity measurement on DEA frontiers of constant returns-to-scale (CRS) technologies. Our proposed methodology and all the developed elasticity theory are illustrated in a real world case of Turkish agricultural sectors. We provide extensive empirical applications covering all the proposed theory and methodology. Among the results of this research, we provide an elasticity measurement framework, which enables us to calculate elasticities of response measures in both VRS and CRS technologies, with or without production tradeoffs included. We observe that the integration of production trade-offs provide better discrimination of efficiency scores compared to the models without trade-offs included. We also investigate how changing production trade-offs affect the efficiency and elasticity measures of the evaluated units.
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Donnelly-Morrison, Duane N. "Defining agricultural land use in Rondonia, Brazil by examination of spot multispectral data." Thesis, This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-09052009-040803/.
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Bailey, Alastair S. "The estimation of input-output coefficients for agriculture from whole farm accounting data." Thesis, University of Reading, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320135.
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Bruce, David William. "Optimising broiler production using a computerised system." Thesis, Queen's University Belfast, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.335342.
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Young, Jeffrey S. "Competition between private labels and national brands| Empirical evidence from Homescan data on fluid milk markets." Thesis, Purdue University, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1585447.
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The purpose of this study is to empirically examine the nature of the pricing relationship between private labels (or "store brands") and national brands. To accomplish this, we control for the exogenous variation in the farm price of a commodity that serves as the main agricultural input common to both private labels and national brands (any shocks to this farm price will pass through to both retail prices - private label and retail). The product of choice is fluid milk, as the farm price of milk comprises a large share of producer and retailer cost.
Two examples of underlying theories concerning this relationship are that (1) the introduction of private labels into a market lowers relative national brand prices, and (2) the introduction of private labels raises the relative national brand prices. The intuition following these two theories about private label/national brand competition tells us the patterns we should look for in the farm-to-retail price transmissions - whether relative national brand prices rise or fall. Hence, the models we estimate are standard price transmission models, each appropriate under specific assumptions about the data.
We obtain results that are inconsistent with either of the chosen theories. Furthermore, the results are robust across model specification. Within the results, we do observe that for small number of markets, the price transmission patterns for private labels are statistically different from those of national brands. Using Chow tests, these markets can be identified and set aside for further investigation.
Finally, we estimate the models again using private label retail prices from retailers for whom private labels are a relatively larger share of sales, and private label prices from retailers for whom private labels are a relatively lower share of sales. On average, we observe no difference in price-setting by retailers who feature national brands and those who don't, which is consistent with the preliminary findings.
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Naude, Stephanus David. "Application of spatial resource data to assist in farmland valuation." Thesis, Stellenbosch : Stellenbosch University, 2011. http://hdl.handle.net/10019.1/18118.
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Thesis (MScAgric) -- Stellenbosch University, 2011.ENGLISH ABSTRACT: In South Africa more than 80 percent of the total land area is used for agriculture and subsistence livelihoods. A land transaction is generally not a recurring action for most buyers and sellers, their experience and knowledge are limited, for this reason the services of property agents and valuers are sometimes used, just to get more information available. The condition of insufficient information and the inability to observe differences in land productivity gives rise to the undervaluation of good land and overvaluation of poor land. The value of a property plays an important role in the acquisition of a bond, in this context farm valuations are essential and therefore commercial banks make more use of specialist businesses that have professional valuers available. The advent of the Internet made access to comprehensive information sources easier for property agents and valuers whose critical time and resources can now be effectively managed through Geographic Information System (GIS) integrated workflow processes. This study aims to develop the blueprint for a farm valuation support system (FVSS) that assists valuers in their application of the comparable sales method by enabling them to do the following: (1) Rapid identification of the location of the subject property and transaction properties on an electronic map. (2) Comparison of the subject property with the transaction properties in terms of value contributing attributes that can be expressed in a spatial format, mainly a) location and b) land resource quality factors not considered in existing valuation systems that primarily focus on residential property. Interpretation of soil characteristics to determine the suitability of a soil for annual or perennial crops requires specialized knowledge of soil scientists, knowledge not normally found among property valuers or estate agents. For this reason an algorithm, that generates an index value, was developed to allow easy comparison of the land of a subject property and that of transaction properties. Whether this index value reflects the soil suitability of different areas sufficiently accurate was confirmed by soil suitability data of the Breede and Berg River areas, which were obtained by soil scientists by means of a reconnaissance soil survey. This index value distinguishes the proposed FVSS from other existing property valuation systems and can therefore be used by valuers as a first approximation of a property’s soil suitability, before doing further field work. A nationwide survey was done among valuers and estate agents that provided information for the design of the proposed FVSS and proved that the need for such a system does exist and that it will be used by valuers.
AFRIKAANSE OPSOMMING: Meer as 80 persent van die totale grondoppervlakte in Suid-Afrika word gebruik vir landbou en bestaansboerdery. 'n Grondtransaksie is oor die algemeen nie 'n herhalende aksie vir die meeste kopers en verkopers nie, hul ervaring en kennis is beperk, om hierdie rede word die dienste van eiendomsagente en waardeerders soms gebruik om meer inligting beskikbaar te kry. Die toestand van onvoldoende inligting en die onvermoë om verskille in grondproduktiwiteit te identifiseer gee aanleiding tot die onderwaardering van goeie grond en oorwaardering van swak grond. Die waarde van 'n eiendom speel 'n belangrike rol in die verkryging van 'n verband. In hierdie konteks is plaaswaardasies noodsaaklik en daarom maak kommersiële banke meer gebruik van gespesialiseerde maatskappye wat oor professionele waardeerders beskik. Die koms van die Internet het toegang tot omvattende inligtingsbronne makliker gemaak vir eiendomsagente en waardeerders wie se kritiese tyd en hulpbronne nou effektief bestuur kan word deur middel van Geografiese Inligtingstelsel (GIS) geïntegreerde werksprosesse. Hierdie studie poog om die bloudruk vir 'n plaaswaardasie ondersteuningstelsel te ontwikkel wat waardeerders sal help in hul toepassing van die vergelykbare verkope metode deur hul in staat te stel om die volgende te doen: (1) Vinnige identifisering van die ligging van die betrokke onderwerp eiendom en transaksie eiendomme op 'n elektroniese kaart. (2) Vergelyking van die onderwerp eiendom met transaksie eiendomme in terme van waardedraende eienskappe wat in 'n ruimtelike formaat uitgedruk word, hoofsaaklik a) ligging en b) bodem gehaltefaktore wat nie oorweeg word in bestaande residensieel georiënteerde waardasiestelsels nie. Interpretasie van grondeienskappe om die geskiktheid van grond vir eenjarige of meerjarige gewasse te bepaal vereis gespesialiseerde kennis van grondkundiges, kennis wat nie normaalweg gevind word onder eiendomswaardeerders of eiendomsagente nie. Om hierdie rede is 'n algoritme ontwikkel sodat die grond van ‘n onderwerp eiendom d.m.v. ‘n indekswaarde met transaksie eiendomme vergelyk kan word. Die indekswaarde is akkuraat genoeg bevestig toe dit vergelyk is met grond geskiktheidsdata wat deur grondkundiges in die Breede- en Bergrivier gebiede ingesamel is. Hierdie indekswaarde onderskei die voorgestelde plaaswaardasie ondersteuningstelsel van ander bestaande eiendom waardasiestelsels en kan dus deur waardeerders gebruik word as 'n eerste bepaling van 'n eiendom se grond geskiktheid, voordat verdere veldwerk gedoen word. 'n Landwye opname is gedoen onder waardeerders en eiendomsagente wat inligting voorsien het vir die ontwerp van die voorgestelde plaaswaardasie ondersteuningstelsel, asook bewys gelewer het dat daar ‘n behoefte aan so 'n stelsel bestaan en dat dit deur waardeerders gebruik sal word.
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Figueiredo, Gleyce Kelly Dantas Araújo 1984. "Soybean yield estimates based on temporally stables pixels using MODIS/EVI data = Estimativa de produtividade da cultura da soja baseada na estabilidade temporal de pixels utilizando dados MODIS/EVI." [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/257114.
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Orientadores: Jansle Vieira Rocha, Rubens Augusto Camargo LamparelliTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agrícola
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Resumo: A soja é uma das principais commodities do mercado agrícola brasileiro, e está em constante especulação no mercado interno e externo. A estimativa da produtividade com precisão e antecedência utilizando o sensoriamento remoto representa um importante avanço na procura de formas objetivas para previsão de safras no Brasil, uma vez que pode auxiliar a avaliação de rendimento da cultura, servir de apoio à segurança alimentar, ao planejamento econômico e a gestão dos recursos naturais. No entanto, ainda não há no país um sistema operacional para estimar produtividade. O principal objetivo desse estudo foi propor uma metodologia para estimar, por município, a produtividade da soja, baseado em dados espectrais (EVI/MODIS) e dados históricos de rendimento durante os anos safra 2000/2001 a 2010/2011 no estado do Paraná. Esses dados foram utilizados para estabelecer a correlação entre EVI e produtividade da soja por pixel utilizando duas abordagens: por mês (outubro a abril) e por estágios fenológicos (emergência a maturação, emergência a floração, floração a maturação, floração ao enchimento dos grãos), criando-se então dois tipos de mapas de correlação. Com isso foi possível detectar pixels que tinham as melhores correlações ao longo do tempo e ainda encontrar o período mais adequado para estimar a produtividade. Os resultados mostraram que a maior correlação foi encontrada no período de pico vegetativo da cultura para ambas as abordagens. Em seguida comparou-se o desempenho dos mapas de correlação com máscaras de culturas especificas para estimar a produtividade. Os mapas de correlação apresentaram resultados mais significativos, com RMSE de 0.173 ton/ha, enquanto a máscara de cultura específica apresentou RMSE de 0.294 ton/ha. Em seguida selecionamos os pixels temporalmente estáveis dentro dos mapas de correlação por meio da técnica de estabilidade temporal, a fim de incluir somente pixels que apresentassem o mesmo padrão temporal de desenvolvimento durante a safra. A técnica apresentou-se eficiente, selecionando desde pixels puros a pixels com alguma porcentagem da cultura dentro dele, assim, estes pixels foram utilizados para estimar a produtividade da soja durante os onze anos de estudo, também utilizando as abordagens por mês e por fase fenológica. Para a primeira abordagem o período de pico vegetativo apresentou melhor resultado, sendo o mês de fevereiro o que apresentou valores mais próximos aos dados oficiais com RMSE de 0.187 ton/ha, na segunda abordagem o melhor desempenho foi para o período de floração a maturação com RMSE de 0.193 ton/ha e o índice de concordância de Willmott foi de 96% para fevereiro e 95.8% durante a floração e maturação. Esta metodologia mostrou ser eficiente para estimar a produtividade por mês, assim é possível utilizá-la como ferramenta auxiliar na previsão de produtividade
Abstract: Soybean is one of the main commodities of the Brazilian agricultural market, and is subject to constant speculation in internal and external markets. Timely and accurate yield estimation using remote sensing represents an important advance in the search for objective crop forecasting in Brazil, since it may help government to plan storage and/or acquisition of food, serving as support to food security, decision making and management of natural resources. However, an operating crop yield estimating system is not currently available in the country. The main goal of this study was to propose a methodology to estimate soybean yield at county level, based on spectral data (EVI/MODIS) and historical yield data during 2000/2001 to 2010/2011 cropping season, in Parana state. These data were used to establish the correlation between EVI and soybean yield at pixel level using two approaches: by month (October to April) and by phenological stages (emergence to maturity, emergence to flowering, flowering to maturity, flowering to grain filling), generating two types of correlation maps. It was possible to detect pixels that had the best correlation over the crop cycle and still find the most suitable period to estimate yield. The results showed that the highest correlation was found in the vegetative peak period of the crop for both approaches. Then I compared the performance of correlation maps against crop specific mask to estimate soybean yield. The correlation maps showed meaningful results with RMSE of 0.173 ton/ha while the crop specific mask showed RMSE of 0.294 ton/ha. Then I selected the temporally stable pixels within the correlation maps using the temporal stability technique in order to include only pixels that presented the same temporal development pattern during the crop cycle. The technique was efficient, once selected pure pixels or pixels with some percentage of the crop, so these pixels were used to estimate soybean yield during the eleven years of study; also using the approaches by month and by phenological stages. For the first approach the vegetative peak showed better results and February showed values closest to official data with RMSE of 0.187 ton/ ha, the best performance of the second approach was the period from flowering to maturity, with RMSE of 0.193 ton/ ha and Willmott agreement index of 96% for February and 95.8% for the flowering to maturity period. This methodology showed to be efficient to estimate yield monthly, thereby it is possible to use it as an auxiliary tool in yield forecast
Doutorado
Planejamento e Desenvolvimento Rural Sustentável
Doutora em Engenharia Agrícola
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Hirsch, Cornelius, and Harald Oberhofer. "Bilateral Trade Agreements and Trade Distortions in Agricultural Markets." WU Vienna University of Economics and Business, 2017. http://epub.wu.ac.at/5428/1/wp240.pdf.
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Agricultural support levels are at a crossroad with reduced distortions in OECD countries and increasing support for agricultural producers in emerging economies over the last decades. This paper studies the determinants of distortions in the agricultural markets by putting a specific focus on the role of trade policy. Applying various different dynamic panel data estimators and explicitly accounting for potential endogeneity of trade policy agreements, we find that an increase in the number of bilateral free trade agreements exhibits significant short- and long-run distortion reducing effects. By contrast, WTO's Uruguay Agreement on Agriculture has not been able to systematically contribute to a reduction in agriculture trade distortions. From a policy point of view our findings thus point to a lack of effectiveness of multilateral trade negotiations.Series: Department of Economics Working Paper Series
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Kempen, Markus [Verfasser]. "EU wide analysis of the Common Agricultural Policy using spatially disaggregated data / Markus Kempen." Bonn : Universitäts- und Landesbibliothek Bonn, 2013. http://d-nb.info/1045345814/34.
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Blank, Sebastian [Verfasser]. "A Biological Inspired Approach for Sensor Data Management in Modular Agricultural Machines / Sebastian Blank." München : Verlag Dr. Hut, 2012. http://d-nb.info/1029399867/34.
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Zarzycka, Sandra Elzbieta. "Assessing Agricultural and Hydrologic Potential of Ancestral Puebloan Community Centers using Open Source Data." Thesis, University of North Texas, 2020. https://digital.library.unt.edu/ark:/67531/metadc1703409/.
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The Pueblo III period marks a critical shift in settlement location of Ancestral Puebloan people within the Mesa Verde region. Community centers during the Pueblo I and Pueblo II periods were built on mesa tops, whereas canyon-rims and alcoves became the preferred settlement location during the Pueblo III period. Beginning in the Pueblo I period, community centers consisted of linear roomblock villages. By the late Pueblo II period great house community centers influenced by the Chaco culture system spanned the Mesa Verde region. The Pueblo III period hallmarks the transition to canyon-rim villages and cliff dwellings. The location of these Pueblo III centers is thought to be related to the need for a defensive position on the landscape, and access to water sources. This shift in settlement locations undoubtedly led to change in the access to resources, such as water, arable farmland, and wild food plants and game. This study aims to evaluate whether the change in community center location impacted the accessibility to arable farmland and water sources immediately available to Ancestral Puebloan people throughout time. Specifically, several variables related to farming potential and hydrologic potential, including soil type, soil moisture, elevation, cropland suitability, distance to water sources, drainage density, and hydrogeologic units were evaluated. Nine community centers within the McElmo drainage area in southwestern Colorado ranging in age from the Pueblo II to Pueblo III periods were included in this study.
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Jiang, Yitong. "Identification of Sewage Sludge Injection Application on Harvested Agricultural Fields Using Landsat TM Data." University of Toledo / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1290201856.
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Maurer, Jacob Lafe. "The development of a conceptual benchmarking tool representing big data and agricultural technology adoption on the farm." Thesis, Kansas State University, 2015. http://hdl.handle.net/2097/19071.
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Master of AgribusinessDepartment of Agricultural Economics
Gregory Ibendahl
One of the latest buzzes amongst agriculture is the storage and analysis of “Big Data.” There are a number of questions surrounding the quality, quantity, and capacity of big data to form real-world decisions based upon past information. Much like the teachings of history, the storybook that big data can reveal about a grower’s operation may hold the answers to the question of: “what is necessary to increase food production which will be required to feed an ever-growing world?” With the increase in interest in precision agriculture, sustainability practices, and the processing of the immense spatial dataset generated on the farm, the next challenge at hand will be in determining how to make technology not only streamlined, but also profitable. Over the past few years, precision agriculture technology has become widely adopted as an agronomic decision making tool. Much like a scientific experiment, the greater the number of similar observations, the greater the degree of confidence can be placed upon a decision. As a means of increasing the number of observations that a farmer can use to base a decision upon, there is becoming increasing demand in being able to combine the data of similar farming operations in order to increase the size and scope of the dataset to generate better decisions benefitting many farms instead of just one. The growing interest in forming community data pools for farm data demonstrates the need for a study for determining how farming practices can be properly benchmarked. The goal was be to evaluate how to use farm data to make economic decisions in a similar manner as one would make agronomic decisions using similar observations. The objective was to design the proper protocol for benchmarking the farm’s potential, and evaluating potential increases in technical efficiency by adopting precision agriculture technology. To accomplish this, a data envelopment analysis was conducted using scale efficiency as a means of determining the frontier of efficient farms. The resounding goal for this study in the future will be to use the model as a means of implementing the secondary process of pooling precision agriculture data to analyze efficiencies gained by the adoption of technology. By demonstrating the value of generating peer groups to increase observations and refine farming practices, farmers can find increased profitability and efficiency by using resources that may already be held within the operation.
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Barreto-Munoz, Armando. "Multi-Sensor Vegetation Index and Land Surface Phenology Earth Science Data Records in Support of Global Change Studies: Data Quality Challenges and Data Explorer System." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/301661.
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Synoptic global remote sensing provides a multitude of land surface state variables. The continuous collection, for more than 30 years, of global observations has contributed to the creation of a unique and long term satellite imagery archive from different sensors. These records have become an invaluable source of data for many environmental and global change related studies. The problem, however, is that they are not readily available for use in research and application environment and require multiple preprocessing. Here, we looked at the daily global data records from the Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS), two of the most widely available and used datasets, with the objective of assessing their quality and suitability to support studies dealing with global trends and changes at the land surface. Findings show that clouds are the major data quality inhibitors, and that the MODIS cloud masking algorithm performs better than the AVHRR. Results show that areas of high ecological importance, like the Amazon, are most prone to lack of data due to cloud cover and aerosols leading to extended periods of time with no useful data, sometimes months. While the standard approach to these challenges has been compositing of daily images to generate a representative map over a preset time periods, our results indicate that preset compositing is not the optimal solution and a hybrid location dependent method that preserves the high frequency of these observations over the areas where clouds are not as prevalent works better. Using this data quality information the Vegetation Index and Phenology (VIP) Laboratory at The University of Arizona produced over 30 years of seamless sensor independent record of vegetation indices and land surface phenology metrics. These data records consist of 0.05-degree resolution global images for daily, 7-days, 15-days and monthly temporal frequency. These sort of remote sensing based products are normally made available through the internet by large data centers, like the Land Processes Distributed Active Archive Center (LP DAAC), however, in this project an online tool, the VIP Data Explorer, was developed to support the visualization, exploration, and distribution of these Earth Science Data Records (ESDRs) keeping it closer to the data generation center which provides a more active data support and distribution model. This web application has made it possible for users to explore and evaluate the products suite before download and use.
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Muwanga-Zake, E. S. K. "The determination of data needs and priorities : a case study of food and agricultural statistics in Uganda." Thesis, University of East Anglia, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.376061.
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Shabbir, Javid. "Choice and collection of agriculture survey data in Punjab and its use in planning improved food supply." Thesis, University of Kent, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362192.
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Kostrzewski, Michael Albert. "Determining the feasibility of collecting high-resolution ground-based remotely sensed data and issues of scale for use in agriculture." Diss., The University of Arizona, 2000. http://hdl.handle.net/10150/280686.
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A ground-based remote sensing system was attached to a linear move irrigation system and successfully collected pixels at an approximate density of 1/meter 2. This low-resolution data was used to create 1-meter resolution images in near real time over a 1-hectare cotton field. A new method using GIS and spatial statistics (kriging) was successfully developed for evaluating the 1-meter images and simulate 2 through 7 meter resolution for determining the effects of scale on data collection for crop management as applied to precision agriculture. The images collected reliably predicted nitrogen and water stress in the field and demonstrated how scale from 1 to 7 meters affects reliability of measuring water and nitrogen stress. A 2X2 Latin square water and nitrogen experiment on cotton consisting of optimal and low nitrogen and water treatments was conducted within 4 replicates of the 4 treatments. The remotely sensed data were used to develop images of the plot to ascertain the ability to detecting nitrogen and water stress. Nitrogen stress was evaluated using the canopy chlorophyll content index while water stress was evaluated using the difference between canopy and air temperature. Four days of field images collected in 1999 at a 1-meter resolution were selected for evaluation. The days represent, one day prior to water and nitrogen treatments, two days of little to moderate nitrogen stress, and one day with severe nitrogen stress and moderate water stress. The image analysis incorporated standard statistics, kriging, and fractals. The 1-meter data was used to produce images with grids of 2 through 10 meters. Standard statistics were used to analyze the four days by grid size. The results indicated no difference in the mean in the data for any grid size within a treatment for either water or nitrogen; however, CV generally decreased with grid size. Kriging was used to evaluate the data for pretreatment day and stressed day for one plot representing each of the four treatments. Data for 1, 3, 5, and 7 meters resolution was kriged and compared to the 1-meter grid to determine reproducibility. It was determined that for temperature it is difficult to reproduce finer resolution data, especially in stressed plots. The nitrogen indice was reproducible to a high degree of accuracy for grids as large as 7 meters. Fractal analysis was used to evaluate the kriged data. The results were mixed in that numbers for some plots increased as grid size increased, and decreased as expected for others.
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Wang, Wenjia. "Food safety supply and demand across the agricultural value chain in China." Thesis, Massachusetts Institute of Technology, 2018. https://hdl.handle.net/1721.1/122527.
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Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2018Cataloged from PDF version of thesis.
Includes bibliographical references (pages 51-55).
This thesis studies the food safety supply and demand in China with the focus on the producing entities and the end consumers. The first chapter concerns different farmers' organizational models and their implications for food safety issues. We conducted three research trips to China and interviewed key personnel from 25 agricultural cooperatives and one agricultural enterprise about the way they organize production activities with farmers. Our findings show that agricultural cooperatives employ a mix of models to mobilize farmers that exert different levels of direct controls over the production activities. We concluded that the choice of model is likely to be based on the difficulty of cultivating certain types of crops. Also, the motivation of agricultural cooperatives in obtaining quality certifications varies based on their position in the value chain: cooperatives that sell directly to end consumers are more motivated to obtain quality certifications than cooperatives selling to downstream processors or distributors. In the case of agricultural enterprise who employs large area of land employ, the contracting farming model is usually adopted. Despite low cost in acquiring land and labor for production, the enterprise has to compromise with a lower level of control over the production activities in the contract farming model. The second chapter studies consumers' response towards different food safety transparency information with respect to different demographic and socio-economical characteristics. The findings suggest that consumers are most likely to respond to seeing organic certificates and the use of organic ingredients in processed products with higher level of purchase intention and a higher willingness to pay. We also found out that respondents who are either male or have children are more likely to respond to food safety information than the other demographic groups..
by Wenjia Wang.
S.M. in Technology and Policy
S.M.inTechnologyandPolicy Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society
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Löw, Fabian [Verfasser], Christopher [Gutachter] Conrad, and Ulrich [Gutachter] Michel. "Agricultural crop mapping from multi-scale remote sensing data - Concepts and applications in heterogeneous Middle Asian agricultural landscapes / Fabian Löw. Gutachter: Christopher Conrad ; Ulrich Michel." Würzburg : Universität Würzburg, 2014. http://d-nb.info/1112655654/34.
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Desmond, Eric D. "Studies including hydrologic modeling and data analysis at the Ohio management systems evaluation." Columbus, Ohio : Ohio State University, 2003. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1070465699.
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Thesis (Ph. D.)--Ohio State University, 2003.Title from first page of PDF file. Document formatted into pages; contains xvii, 104 p.; also includes graphics (some col.). Includes abstract and vita. Advisor: Andy Ward, Dept.of Food, Agricultural, and Biological Engineering. Includes bibliographical references (p. 100-104).
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Huang, Yanping. "Modelling land use change and agricultural performance in post-reform China using remotely sensed data and GIS." Thesis, University of Oxford, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.264570.
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Mugadza, Precious. "An assessment of the usefulness of spatial agricultural land resource digital data for agritourism and ecotourism." Thesis, Link to the online version, 2005. http://hdl.handle.net/10019/1125.
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Smith, Tiziana. "Estimating hydrologic fluxes, crop water use, and agricultural land use in China from multiple data sources." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104166.
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Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2016.Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, Institute for Data, Systems, and Society, Technology and Policy Program, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 95-99).
Crop production has significantly altered the terrestrial environment by changing land use (Ramankutty et al., 2008) and by altering the water cycle through both co-opting rainfall and surface water withdrawals (Postel et al., 1996). As the world's population continues to grow and individual diets become more resource-intensive, the demand for food - and the land and water necessary to produce it - will continue to increase. Quantitative data about water availability, water use, and agricultural land use are needed to develop sustainable water and agricultural planning and policies. However, existing large-scale data are susceptible to errors and can be physically inconsistent. China is an example of a large area where food demand is expected to increase and a lack of data clouds the resource management dialogue. Some assert that China will have insufficient land and water resources to feed itself, posing a threat to global food security if they seek to increase food imports (Brown and Starke, 1995). Others believe resources are plentiful (Lomborg, 2001). Without quantitative data, it is difficult to discern if these concerns are realistic or overly dramatized. This thesis presents a quantitative approach to characterize hydrologic fluxes, crop water use, and agricultural land use and applies the methodology in China using data from around the year 2000. The approach uses the principles of water balance and of crop water requirements to assimilate existing data with a least-squares estimation technique, producing new estimates of water and land use variables that are physically consistent while minimizing differences from measured data. We argue that this technique for estimating water fluxes and agricultural land use can provide a useful basis for resource management and policy, both in China and around the world.
by Tiziana Smith.
S.M.
S.M. in Technology and Policy
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Lin, Nannan. "Prediction of Wheeled Tractor Fuel Use Rate Distributions from CAN-bus Data for Agricultural Field Operations." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1397730103.
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Rossi, James. "Comparing the Impacts of Biofuels Using Survey and Non-survey Data." Thesis, University of Missouri - Columbia, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=13850745.
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This paper utilizes survey data to compare several non-survey methods of modeling the economic impacts of biofuels plants. It examines differences in the input coefficients derived from the survey versus the trade coefficients generated through the non-survey methods. It finds that of the three non-survey methods examined, the Swenson (2006) scenario input coefficients most closely represent those found in the survey based on the performance of the non-survey scenario input coefficients in a variety of statistical tests. Further, it examines the economic impacts (multipliers) generated by these scenarios compared to those generated from the survey. Based upon statistical tests of the multipliers, the Swenson scenario’s estimated impacts most closely represent the impacts derived from the survey.
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Grossen, Grace Elizabeth. "Agricultural Trade Performance and Potential: A Retrospective Panel Data Analysis of US Exports of Corn and Soybeans." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/93225.
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There are a variety of international issues that disrupt the global trade market, an important one being national policies on the regulation of genetically modified organisms, or GMOs. Many crops have been genetically modified for reasons from herbicide resistance to correcting dietary shortfalls. This study evaluates the United States' exports of corn and soybeans from 1998 to 2016 to identify unusual shocks in trade values. In particular, this study quantifies how the importers' policy stance on the GMO issue impacts bilateral trade values. I estimate a gravity model with both ordinary least squares (OLS) and Poisson pseudo maximum likelihood (PPML) estimations. Residual analysis is used to assess the difference between actual trade and the trade levels predicted by the models. The results suggest that anti-GMO policies reduce trade values by an average of 11%. The largest difference between predictions and actual trade values is seen in corn exports to the European Union. Between 1998 and 2016, this forgone trade in corn was valued at $52.7 billion, which is $2.77 billion per year on average. This value is similar to the annual average value of U.S. exports of corn to Japan in the same period, $2.46 billion. The results have important implications for the agricultural industry. For developing nations, adoption of GMO crops could increase productivity and help alleviate poverty. Ultimately, the decision to adopt is up to the consumer, so the factors of consumer knowledge and opinions of GMOs are not to be ignored.Master of Science
There are a variety of international issues that disrupt the global trade market, an important one being national policies on the regulation of genetically modified organisms, or GMOs. This study evaluates the United States’ exports of corn and soybeans from 1998 to 2016 to identify unusual drops in trade values. In particular, this study quantifies how the importers’ policy stance on the GMO issue impacts bilateral trade values. I estimate a gravity model with various estimation methods. Residual analysis is used to assess the difference between actual trade and the trade levels predicted by the models. The results suggest that anti-GMO policies reduce trade values by an average of 11%. The largest difference between predictions and actual trade values is seen in corn exports to the European Union. Between 1998 and 2016, this forgone trade in corn was valued at $52.7 billion, which is $2.77 billion per year on average. This value is similar to the annual average value of U.S. exports of corn to Japan in the same period, $2.46 billion. The results have important implications for the agricultural industry. For developing nations, adoption of GMO crops could increase productivity and help alleviate poverty. Ultimately, the decision to adopt is up to the consumer, so the factors of consumer knowledge and opinions of GMOs are not to be ignored.
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Ozdarici, Ok Asli. "A Segment-based Approach To Classify Agricultural Lands Using Multi-temporal Kompsat-2 And Envisat Asar Data." Phd thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614195/index.pdf.
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Agriculture has an important role in Turkeyhence automated approaches are crucial to maintain sustainability of agricultural activities. The objective of this research is to classify eight crop types cultivated in Karacabey Plain located in the north-west of Turkey using multi-temporal Kompsat-2 and Envisat ASAR satellite data. To fulfill this objective, first, the fused Kompsat-2 images were segmented separately to define homogenous agricultural patches. The segmentation results were evaluated using multiple goodness measures to find the optimum segments. Next, multispectral single-date Kompsat-2 images with the Envisat ASAR data were classified by MLC and SVMs algorithms. To combine the thematic information of the multi-temporal data set, probability maps were generated for each classification result and the accuracies of the thematic maps were then evaluated using segment-based manner. The results indicated that the segment-based approach based on the SVMs method using the multispectral Kompsat-2 and Envisat ASAR data provided the best classification accuracies. The combined thematic maps of June-August and June-July-August provided the highest overall accuracy and kappa value around 92% and 0.90, respectively, which was 4% better than the highest result computed with the MLC method. The produced thematic maps were also evaluated based on field-based manner and the analysis revealed that the classification performances are directly proportional to the size of the agricultural fields.
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Lauer, Johannes [Verfasser], and Alexander [Akademischer Betreuer] Zipf. "Extraction of routing relevant geodata using telemetry sensor data of agricultural vehicles / Johannes Lauer ; Betreuer: Alexander Zipf." Heidelberg : Universitätsbibliothek Heidelberg, 2018. http://d-nb.info/1177251582/34.
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Perry, Lyndi. "The Value of Farmland: Mapping Assessor Data to Understand Land Use Change." DigitalCommons@USU, 2019. https://digitalcommons.usu.edu/etd/7413.
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Ideas developed by regional economists have potential applications within the urban planning field. One potential application is toward conserving farmland, and within this thesis this topic is examined for the study area of Utah County, Utah. Using assessor data, a land value map is created and further used to develop a regional economic model and spatial models that were analyzed for patterns of land use change.
Findings show that representing land value as continuous surface maps is a useful approach. The maps reveal that Utah County has densified as its population increased while farmland loss still occurred in agriculturally-important areas. Vulnerable areas were identified by examining the value of changed lands. Change mapping shows that macro-level variables affect local land values and subsequent development patterns.
While limitations exist, the conclusion was drawn that this data is useful in connecting land value to location, examining change over time, and understanding how individuals’ priorities (as represented through property values) may conflict with (and potentially solve) collective goals.
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Warren, Georgina. "Developing land management units using Geospatial technologies: An agricultural application." Curtin University of Technology, Department of Spatial Sciences, 2007. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=17509.
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This research develops a methodology for determining farm scale land managementunits (LMUs) using soil sampling data, high resolution digital multi-spectral imagery (DMSI) and a digital elevation model (DEM). The LMUs are zones within a paddock suitable for precision agriculture which are managed according to their productive capabilities. Soil sampling and analysis are crucial in depicting landscape characteristics, but costly. Data based on DMSI and DEM is available cheaply and at high resolution.The design and implementation of a two-stage methodology using a spatiallyweighted multivariate classification, for delineating LMUs is described. Utilising data on physical and chemical soil properties collected at 250 sampling locations within a 1780ha farm in Western Australia, the methodology initially classifies sampling points into LMUs based on a spatially weighted similarity matrix. The second stage delineates higher resolution LMU boundaries using DMSI and topographic variables derived from a DEM on a 10m grid across the study area. The method groups sample points and pixels with respect to their characteristics and their spatial relationships, thus forming contiguous, homogenous LMUs that can be adopted in precision agricultural applications. The methodology combines readily available and relatively cheap high resolution data sets with soil properties sampled at low resolution. This minimises cost while still forming LMUs at high resolution.The allocation of pixels to LMUs based on their DMSI and topographic variables has been verified. Yield differences between the LMUs have also been analysed. The results indicate the potential of the approach for precision agriculture and the importance of continued research in this area.
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Takahashi, Fabio 1982. "Avaliação da sustentabilidade de sistemas agrícolas brasileiros através de ferramentas computacionais." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/256250.
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Orientador: Enrique Ortega RodriguezTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia de Alimentos
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Resumo: Este estudo utilizou a metodologia emergética para avaliar 39 culturas agrícolas de manejo convencional e 15 culturas agrícolas de manejo orgânico com o objetivo de traçar um perfil da sustentabilidade de alguns produtos da agricultura brasileira. Todas as avaliações foram arquivadas em um banco de dados que pode ser acessado em uma página web dinâmica que foi desenvolvida para divulgar os resultados deste trabalho e permitir que o usuário crie suas próprias avaliações emergéticas de sistemas agrícolas. Na primeira etapa da análise dos resultados, os sistemas foram agrupados em 5 categorias; a) oleaginosas b) grãos c) frutas d) hortaliças, raízes e tubérculos e) hortaliças orgânicas. Técnicas de mineração de dados foram utilizadas para interpretar todo o conjunto de resultados com o objetivo de encontrar relações entre os indicadores emergéticos que classificassem os sistemas de acordo com o manejo e em categorias sugeridas por especialistas de acordo com os valores dos índices emergéticos. A avaliação emergética mostra o melhor desempenho das culturas orgânicas quando comparadas com as culturas de manejo convencional. A mineração de dados se mostrou uma ferramenta eficiente para avaliação de todos os resultados encontrados nesse trabalho, pois foi possível encontrar relações dos indicadores emergéticos que descrevem o comportamento dos sistemas e os classificam em grupos encontrados pela clusterização (sistemas convencionais e sustentáveis; sistemas orgânicos e sustentáveis; sistemas insustentáveis) e também em categorias de acordo com os indicadores emergéticos propostos por especialistas
Abstract: This study used the emergy methodology for assessing 39 conventional crops and 15 organic crops in order to draw a profile of sustainability of some products of Brazilian agriculture. All evaluations were stored in a database that can be accessed in a dynamic web page developed to disseminate the results of this study and allow the user to create his own evaluation of agricultural systems. In the first step of analysis of the results, the systems were grouped into 5 categories: a) oil plants b) fruits c) grains d) vegetables and tubers e) organic. Data mining techniques were used to interpret the whole set of results in order to find relationships among the emergy indicators to classify the systems according to the management and groups established by experts in accordance with the values of emegy indices. The emergy evaluation shows a better performance of organic crops compared with conventional crops. Data mining has proven an effective tool for evaluation of all results found in this study. It was possible to find relations of emergy indicators that describe the behavior of systems and classify them into groups found by clustering ( conventional and sustainable systems; organic and sustainable systems; unsustainable systems) and also into categories according to emergy indicators proposed by experts
Doutorado
Engenharia de Alimentos
Doutor em Engenharia de Alimentos