Relevant bibliographies by topics / Precision livestock farming

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Precision livestock farming'

Author: Grafiati
Published: 4 June 2021
Last updated: 21 February 2023

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Journal articles on the topic "Precision livestock farming"

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István Komlósi. "The precision livestock farming." Acta Agraria Debreceniensis, no. 49 (November 13, 2012): 201–2. http://dx.doi.org/10.34101/actaagrar/49/2525.

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The application of information technology is the response of the livestock farming to the demand of customer, legal and economical expectations. This technology is the socalled precision livestock farming (PLF). The elements of the PLF are: continuous monitoring of inputs, animal behaviour by sensors, an algorithm which converts these signals into a figure, this figure is compared to an optimum then adjustment of the input is followed, if it is necesary.
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Berckmans, Daniel. "Precision livestock farming (PLF)." Computers and Electronics in Agriculture 62, no. 1 (June 2008): 1. http://dx.doi.org/10.1016/j.compag.2007.09.002.

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Norton, T., and D. Berckmans. "Developing precision livestock farming tools for precision dairy farming." Animal Frontiers 7, no. 1 (January 1, 2017): 18–23. http://dx.doi.org/10.2527/af.2017.0104.

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Vranken, Erik, and Dries Berckmans. "Precision livestock farming for pigs." Animal Frontiers 7, no. 1 (January 1, 2017): 32–37. http://dx.doi.org/10.2527/af.2017.0106.

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Juarez, Manuel M. "238 Linking livestock phenomics and precision livestock farming." Journal of Animal Science 98, Supplement_3 (November 2, 2020): 124. http://dx.doi.org/10.1093/jas/skaa054.212.

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Abstract Numerous pre- and post-mortem factors, such as genotype, production system, growth promotants, diet, health events, stress, slaughter age and weight, carcass chilling, and ageing time, have been shown to impact beef production and final product quality. The objective of livestock phenomics is the systematic acquisition of high dimensional phenotypic data, which requires measuring phenomes as they change in response to genetic mutation and environmental influences. Due to the decrease in costs associated to genomics technology and related fields, researchers had to face the so called “phenomic gap”, a lack of sufficient, appropriate phenotypic data. Selecting phenotypes of interests, standardizing methodologies, developing high-throughput data collection systems, systematically recording environmental factors, and integrating bioinformatics are some of the challenges when developing a livestock phenomics program. Precision livestock farming aims at applying continuous, automated real-time monitoring systems to optimize livestock management. The information collected by these systems can be used to optimize individual animal health and welfare, reproductive traits, and productivity, as well as environmental influences. This approach requires the use of novel technologies and the management of large amounts of data. Multiple technologies and sensors are already being used, or have the potential, to monitor important individual traits. These two interdisciplinary fields share multiple objectives that could lead to significant synergies. The complexity of in-farm data collection varies depending on the species and production system, with beef cattle presenting specific challenges. In addition, data collection needs to continue after slaughter, as carcass and meat quality traits are influenced by in vivo practices, determine the final profitability of the system, and need to be taken into consideration to modify management practices. Integrating livestock phenomics and precision livestock farming approaches will lead to a faster development of both fields and an optimal use of resources.
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Werkheiser, Ian. "Precision Livestock Farming and Farmers’ Duties to Livestock." Journal of Agricultural and Environmental Ethics 31, no. 2 (February 16, 2018): 181–95. http://dx.doi.org/10.1007/s10806-018-9720-0.

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Berckmans, D. "General introduction to precision livestock farming." Animal Frontiers 7, no. 1 (January 1, 2017): 6–11. http://dx.doi.org/10.2527/af.2017.0102.

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Xin, Hongwei, and Kai Liu. "Precision livestock farming in egg production." Animal Frontiers 7, no. 1 (January 1, 2017): 24–31. http://dx.doi.org/10.2527/af.2017.0105.

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Berckmans, Daniel. "Bright Farm by Precision Livestock Farming." Impact 2017, no. 1 (January 9, 2017): 4–6. http://dx.doi.org/10.21820/23987073.2017.1.4.

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Norton, Tomas, and Daniel Berckmans. "Engineering advances in Precision Livestock Farming." Biosystems Engineering 173 (September 2018): 1–3. http://dx.doi.org/10.1016/j.biosystemseng.2018.09.008.

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Dissertations / Theses on the topic "Precision livestock farming"

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Bahlo, Christiane. "Open data and interoperability standards : opportunities for animal welfare in extensive livestock systems." Thesis, Federation University Australia, 2021. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/177520.

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Extensive livestock farming constitutes a sizeable portion of agriculture, not only in relation to land use, but in contribution to feeding a growing human population. In addition to meat, it contributes other economically valuable commodities such as wool, hides and other products. The livestock industries are adopting technologies under the banner of Precision Livestock Farming (PLF) to help meet higher production and efficiency targets as well as help to manage the multiple challenges impacting the industries, such as climate change, environmental concerns, globalisation of markets, increasing rules of governance and societal scrutiny especially in relation to animal welfare. PLF is particularly dependent on the acquisition and management of data and metadata and on the interoperability standards that allow data discovery and federation. A review of interoperability standards and PLF adoption in extensive livestock farming systems identified a lack of domain specific standards and raised questions related to the amount and quality of public data which has potential to inform livestock farming. A systematic review of public datasets, which included an assessment based on the principles that data must be findable, accessible, interoperable and reusable (FAIR) was developed. Custom software scripts were used to conduct a dataset search to determine the quantity and quality of domain specific datasets yielded 419 unique Australian datasets directly related to extensive livestock farming. A FAIR assessment of these datasets using a set of non-domain specific, general metrics showed a moderate level of compliance. The results suggest that domain specific FAIR metrics may need to be developed to provide a more accurate data quality assessment, but also that the level of interoperability and reusability is not particularly high which has implications if public data is to be included in decision support tools. To test the usefulness of available public datasets in informing decision support in relation to livestock welfare, a case study was designed and farm animal welfare elements were extracted from Australian welfare standards to guide a dataset search. It was found that with few exceptions, these elements could be supported with public data, although there were gaps in temporal and spatial coverage. The development of a geospatial animal welfare portal including these datasets further explored and confirmed the potential for using public data to enhance livestock welfare.
Doctor of Philosophy
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Johansson, Nicklas. "Effekter av kameraövervakning av boskap hos sex lantbrukare i Sverige." Thesis, Karlstads universitet, Handelshögskolan (from 2013), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-70935.

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Bakgrund: Lantbruket står inför stora framtida utmaningar som t.ex. stora befolkningsökningar och minskade jordbruksarealer. Ett förslag för att lösa en del av problemet och öka effektiviteten inom lantbruket är att implementera och använda olika digitala tjänster och produkter. Ett av koncepten för den digitala tekniken som har lyfts fram av bland annat EU är Smart farming. Konceptet är brett och innefattar många olika tekniska lösningar, varav en av dessa är kameraövervakning av boskapsdjur. Frågeställning: Har de lantbrukare som använder kameraövervakning av boskapsdjur upplevt en förändring av sin livskvalitet och har användningen av tekniken medfört några ekonomiska effekter? Metod: Ett kvalitativt angreppssätt valdes där sex lantbrukare intervjuades i semistrukturerade intervjuer. Resultat: De medverkande lantbrukarna var överlag positiva till kameraövervakningssystemen och flera av lantbrukarna anser att tekniken möjliggjort att de kunnat spara tid och att djur i viss utsträckning kunnat räddats. Flera av lantbrukarna menar också att användandet av kameraövervakningssystemen lett till positiva effekter gällande deras livskvalitet, där det framför allt var möjligheten att kunna spendera mer tid med familj och ökad flexibilitet som var bidragande. Slutsatser: Undersökningens resultat tyder på att kameraövervakningssystemen kan spara tid och pengar för lantbrukarna och att den upplevda livskvaliteten förbättras. Den grupp respondenter i undersökningen som upplevde störst effekter av kameraövervakningen var mindre lantbruk. Kameraövervakningen användes till flera olika ändamål, t.ex. brottsförebyggande, kalvning, personalsäkerhet, övervakning av foderbord, lösdrift samt gård och ägor.
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Casten, Carlberg Carl Johan, and Elsa Jerhamre. "Artificial Intelligence in Agriculture : Opportunities and Challenges." Thesis, Uppsala universitet, Avdelningen för datorteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-443576.

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Artificial Intelligence (AI) is increasingly used in different parts of society for providing decision support in various activities. The agricultural sector is anticipated to benefit from an increased usage of AI and smart devices, a concept called smart farming technologies. Since the agricultural sector faces several simultaneous challenges, such as shrinking marginals, complicated pan-European regulations, and demands to mitigate the environmental footprint, there are great expectations that smart farming will benefit both individual farmers and industry stakeholders. However, most previous research focuses only on a small set of characteristics for implementing and optimising specific smart farming technologies, without considering all possible aspects and effects. This thesis investigates both technical and non-technical opportunities and hurdles when implementing AI in Swedish agricultural businesses. Three sectors in agriculture are scrutinized: arable farming, milk production and beef production. As a foundation for the thesis, a literature review revises former research on smart farming. Thereafter, an interview study with 27 respondents both explores the susceptibility and maturity of smart farming technologies and provides examples of technical requirements of three chosen applications of AI in agriculture. Findings of the study include a diverse set of aspects that both enable and obstruct the transition. Main identified opportunities are the importance smart farming has on the strategic agendas of several industry stakeholders, the general trend towards software technology as a service through shared machinery, the vast amount of existing data, and the large interest from farmers towards new technology. Contrasting, the thesis identifies main hurdles as technical and legislative challenges to data ownership, potential cybersecurity threats, the need for a well-articulated business case, and the sometimes lacking technical knowledge within the sector. The thesis concludes that the macro trend points towards a smart farming transition but that the speed of the transformation will depend on the resolutions for the identified obstacles.
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Condotta, Isabella Cardoso Ferreira da Silva. "Automatic assess of growing-finishing pigs\' weight through depth image analysis." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/11/11152/tde-03082017-093143/.

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A method of continuously monitoring weight would aid producers by ensuring all pigs are gaining weight and increasing the precision of marketing pigs thus saving money. Electronically monitoring weight without moving the pigs to the scale would eliminate a stress-generating source. Therefore, the development of methods for monitoring the physical conditions of animals from a distance appears as a necessity for obtaining data with higher quality. In pigs\' production, animals\' weighing is a practice that represents an important role in the control of the factors that affect the performance of the herd and it is an important factor on the production\'s monitoring. Therefore, this research aimed to extract weight data of pigs through depth images. First, a validation of 5 Kinect ® depth sensors was completed to understand the accuracy of the depth sensors. In addition, equations were generated to correct the dimensions\' data (length, area and volume) provided by these sensors for any distance between the sensor and the animals. Depth images and weights of finishing pigs (gilts and barrows) of three commercial lines (Landrace, Duroc and Yorkshire based) were acquired. Then, the images were analyzed with the MATLAB software (2016a). The pigs on the images were selected by depth differences and their volumes were calculated and then adjusted using the correction equation developed. Also, pigs\' dimensions were acquired for updating existing data. Curves of weight versus corrected volumes and corrected dimensions versus weight were adjusted. Equations for weight predictions through volume were adjusted for gilts and barrows and for each of the three commercial lines used. A reduced equation for all the data, without considering differences between sexes and genetic lines was also adjusted and compared with the individual equations using the Efroymson\'s algorithm. The result showed that there was no significant difference between the reduced equation and the individual equations for barrows and gilts (p<0.05), and the global equation was also no different than individual equations for each of the three sire lines (p<0.05). The global equation can predict weights from a depth sensor with an R2 of 0,9905. Therefore, the results of this study show that the depth sensor would be a reasonable approach to continuously monitor weights.
Um método de monitoramento contínuo da massa corporal de suínos auxiliaria os produtores, assegurando que todos os animais estão ganhando massa e aumentando a sua precisão de comercialização, reduzindo-se perdas. Obter eletronicamente a massa corporal sem mover os animais para a balança eliminaria uma fonte geradora de estresse. Portanto, o desenvolvimento de métodos para monitorar as condições físicas dos animais à distância se mostra necessário para a obtenção de dados com maior qualidade. Na produção de suínos, a pesagem dos animais é uma prática que representa um papel importante no controle dos fatores que afetam o desempenho do rebanho e o monitoramento da produção. Portanto, esta pesquisa teve como objetivo extrair, automaticamente, dados de massa de suínos por meio de imagens em profundidade. Foi feita, primeiramente, uma validação de 5 sensores de profundidade Kinect ® para compreender seu comportamento. Além disso, foram geradas equações para corrigir os dados de dimensões (comprimento, área e volume) fornecidos por estes sensores para qualquer distância entre o sensor e os animais. Foram obtidas imagens de profundidade e massas corporais de suínos e crescimento e terminação (fêmeas e machos castrados) de três linhagens comerciais (Landrace, Duroc e Yorkshire). Em seguida, as imagens foram analisadas com o software MATLAB (2016a). Os animais nas imagens foram selecionados por diferenças de profundidade e seus volumes foram calculados e depois ajustados utilizando a equação de correção desenvolvida. Foram coletadas, ainda, dimensões dos animais para atualização de dados existentes. Curvas de massa versus volumes corrigidos e de dimensões corrigidas versus massa, foram ajustadas. Equações para predição de massa a partir do volume foram ajustadas para os dois sexos e para as três linhagens comerciais. Uma equação reduzida, sem considerar as diferenças entre sexos e linhagens, também foi ajustada e comparada com as equações individuais utilizando o algoritmo de Efroymson. O resultado mostrou que não houve diferença significativa entre a equação reduzida e as equações individuais tanto para sexo (p <0,05), quanto para linhagens (p <0,05). A equação global pode predizer massas a partir do volume obtido com o sensor, com um R2 de 0,9905. Portanto, os resultados deste estudo mostram que o sensor de profundidade é uma abordagem razoável para monitorar as massas dos animais.
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Rico, José Carlos Silva. "Condicionamento ambiental em suínos na fase de crescimento e engorda." Master's thesis, Universidade de Évora, 2019. http://hdl.handle.net/10174/27904.

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No âmbito do Projeto AWARTECH efetuaram-se dois ensaios com o objetivo de perceber como se monitorizam os parâmetros ambientais e analisar a sua importância na produção e bem-estar animal de suínos em fase de crescimento e engorda. Utilizaram-se 14 fêmeas (7 por ensaio), que foram sujeitas a três ambientes térmicos: inverno (INV), termoneutralidade (TNZ) e verão (VER). Nos dois ensaios, as condições ambientais influenciaram significativamente (p<0,001) a ingestão alimentar (IA), tendo esta sido superior no inverno. Este efeito não foi verificado (p≥0,05) sobre o ganho médio diário (GMD), embora se tenham registado diferenças numéricas nas taxas de crescimento. No ensaio 1, o menor índice de conversão alimentar (IC) verificou-se no verão (p<0,05). No ensaio 2, o IC foi menor (p<0,05) na termoneutralidade. Estes resultados evidenciam a importância que o ambiente térmico exerce sobre as performances de suínos, e fornecem informação acerca das adaptações comportamentais dos animais às variações térmicas; “ENVIRONMENTAL CONTROL FOR GROWING-FINISHING PIGS” SUMMARY: Two trials were carried out within the AWARTECH project with the objective to understand how environmental parameters are monitored and to analyse their importance in the welfare and production of growing-finishing pigs. Fourteen gilts were used (7 per trial) and were exposed to three types of environmental conditions: winter (W), thermoneutrality (TN) and summer (S). In the two trials, environmental conditions significantly influenced (p <0.001) the feed intake (FI), which was higher in W. This effect wasn’t observed (p≥0.05) in average daily gain (ADG), although there were numerical differences in growth rates. In trial 1, the lowest feed conversion ratio (FCR) was observed in S (p <0.05). In trial 2, FCR was lower (p <0.05) in TN. These results show the importance of the thermal environment on the performance of pigs and provide information about the behavioural adaptations of the animals to the thermal variations.
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Anguzza, Umberto. "A method to develop a computer-vision based system for the automaticac dairy cow identification and behaviour detection in free stall barns." Doctoral thesis, Università di Catania, 2013. http://hdl.handle.net/10761/1334.

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In this thesis, a method to develop a computer-vision based system (CVBS) for the automatic dairy cow identification and behaviour detection in free stall barns is proposed. Two different methodologies based on digital image processing were proposed in order to achieve dairy cow identification and behaviour detection, respectively. Suitable algorithms among that used in computer vision science were chosen and adapted to the specific characteristics of the breeding environment under study. The trial was carried out during the years 2011 and 2012 in a dairy cow free-stall barn located in the municipality of Vittoria in the province of Ragusa. A multi-camera video-recording system was designed in order to obtain sequences of panoramic top-view images coming from the multi-camera video-recording system. The two methodologies proposed in order to achieve dairy cow identification and behaviour detection, were implemented in a software component of the CVBS and tested. Finally, the CVBS was validated by comparing the detection and identification results with those generated by an operator through visual recognition of cows in sequences of panoramic top-view images. This comparison allowed the computation of accuracy indices. The detection of the dairy cow behavioural activities in the barn provided a Cow Detection Percentage (CDP) index greater than 86% and a Quality Percentage (QP) index greater than 75%. With regard to cow identification the CVBS provided a CDP > 90% and a QP > 85%.
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Rosa, Filho Gilberto [UNESP]. "Produtividade da soja em função de atributos físicos de um latossolo vermelho distroférrico sob plantio direto." Universidade Estadual Paulista (UNESP), 2008. http://hdl.handle.net/11449/98897.

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Atualmente, no cenário nacional, a cultura da soja no sistema plantio direto é amplamente utilizada na integração agricultura-pecuária. No ano agrícola de 2006/07, no município de Selvíria (MS), foi analisada a produtividade da soja, em plantio direto, em função de alguns atributos físicos de um Latossolo Vermelho Distroférrico (Typic Acrustox) local. O objetivo foi selecionar entre os atributos pesquisados do solo aquele que melhor se apresentasse para explicar a variabilidade da produtividade agrícola. Para tanto, foi instalada a malha geoestatística para a coleta dos dados do solo e da planta, contendo 120 pontos amostrais, numa área de 4068 m2 e declive homogêneo de 0,025 m m-1. Do ponto de vista linear e espacial, a elevada produtividade de grãos de soja pôde ser explicada em função da densidade do solo e da umidade volumétrica. A baixa variabilidade obtida para a maioria dos atributos do solo denotou ser o plantio direto um sistema que proporciona a homogeneização do ambiente físico do solo.
Nowadays the soybean crop in no-tillage is widely used in the national crop-livestock integration. The soybean productivity in no-tillage was analysed in Selvíria County (Mato Grosso do Sul State – Brazil), during the 2006/07 agricultural year, in function of some physical attributes of a Typic Acrustox local. The objective was to select, among the soil attributes, the one that better could stand out in way to explain the variability of the agricultural productivity. Therefore, a geostatistical grid was installed for data collecting regarding the soil and the plant, with 120 sampling station, in an area of 4068 m2 and homogeneous slope of 0,025 m m-1. In the linear and spatial point of view, the high productivity of soybean grains could be explained by reason of both bulk density and volumetric moisture. The low variability of the majority soil attributes showed no-tillage as a system that causes the homogenization of the physical environment of soil.
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Fischer, Amélie. "Etude de la variabilité interindividuelle de l'efficience alimentaire de la vache laitière." Thesis, Rennes, Agrocampus Ouest, 2017. http://www.theses.fr/2017NSARB296/document.

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L’amélioration de l’efficience alimentaire des animaux peut contribuer à un élevage plus durable par la réduction des ressources utilisées et des rejets associés. Les caractères qui déterminent l’efficience alimentaire des vaches laitières restent mal identifiés. Le projet se propose donc d’identifier les facteurs biologiques associés à la variabilité interindividuelle de l’efficience alimentaire des vaches laitières. La variation d’efficience alimentaire a été estimée avec l’ingéré résiduel, classiquement défini comme la variabilité résiduelle de l’énergie nette ingérée corrigée pour l’énergie nette du lait, l’entretien et les variations de réserves corporelles. Cet ingéré résiduel inclut par définition toutes les erreurs de mesure. Pour réduire ces erreurs, la note d’état corporel, qui classiquement se fait par notation visuelle, a été automatisée et de nombreux autres caractères candidats ont été mesurés fréquemment dans un environnement stable sur quasiment toute la lactation.La variabilité de l’ingéré résiduel ne représentait que 8% de la variabilité de l’ingéré mesuré, dont 58,9% étaient associés à de l’efficience et non de l’erreur. L’étude de la répétabilité de cet ingéré résiduel au cours de la lactation suggère d’éviter les 7 premières quinzaines au profit du milieu de lactation. Parmi tous les caractères mesurés, le comportement alimentaire, la température ruminale, la variation des réserves corporelles et l’activité expliquaient 58,9% de la variabilité de l’ingéré résiduel. Les effets de plusieurs de ces caractères semblent confondus. Leur lien de causalité av
Achieving higher feed efficiency of animals is expected to improve animal production sustainability through reduction of the used resources and of the associated emissions. The traits determining feed efficiency remain poorly understood. The present project aimed therefore at identifying the biological factors associated with feed efficiency differences in lactating dairy cows. Feed efficiency variation was estimated with the traditional residual intake, which was defined as the residual variability of net energy intake which is not explained by net energy required for lactation, maintenance and body reserves change. This residual intake includes by definition all measurement errors. To reduce these errors, body condition score, which is commonly measured visually, has been automated and several other candidate traits were measured frequently in a steady environment for almost whole lactation.Residual intake variability represented only 8% of intake variability in our study, among which only 58.9% were found to be associated with feed efficiency variability and not to errors. The repeatability analysis of the residual intake throughout the lactation suggested to avoid the 7 first lactation fortnights, and rather to focus on lactation middle. Among all measured traits, feeding behaviour, rumen temperature, body reserves change and activity explained 58.9% of residual intake variability. Many of these traits seemed confounded with others, which claimed for the need for further work to properly define their causal relationship with feed efficiency, especially focussing on di
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Mostaço, Gustavo Marques. "Determinação da temperatura retal e frequência respiratória de suínos em fase de creche por meio da temperatura da superfície corporal em câmara climática." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/11/11152/tde-29052014-150905/.

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A constante influência humana em atividades de manejo animal, além de aumentar os custos de produção, torna-se uma adicional fonte geradora de estresse sobre os animais. Nesse sentido, é necessária a busca pelo desenvolvimento de métodos alternativos de acompanhamento, à distância e em tempo real, das condições físicas dos animais, em conjunto com o controle das instalações. Para a identificação da condição de conforto ou estresse calórico dos animais, alguns indicativos podem vir a auxiliar, tais como a temperatura retal (TR), sendo esse um bom indicador da temperatura do núcleo corporal, bem como, a frequência respiratória (FR). Porém, com a crescente preocupação em relação ao bem-estar animal, vários questionamentos são feitos acerca de métodos invasivos, motivando a busca por alternativas à mensuração da TR. Surge então, como variável alternativa, a temperatura da superfície corporal, buscando-se correlacioná-la com a TR e FR. Sendo assim, com essa pesquisa objetivou-se identificar a região mais adequada da superfície corporal dos suínos, em fase de creche, que apresente a melhor correlação com a TR e FR. Para tal, foi conduzido um experimento, dividido em duas etapas: etapa 1) pré-experimento, sendo conduzido com dois animais em câmara climática, variando-se as condições de temperatura e testando-se métodos de fixação de sensores e coleta de dados inicialmente propostos; e etapa 2) experimento principal. Este último foi conduzido em uma câmara climática, com cinco leitões da raça Landrace x Large White, com 30 dias de idade, provenientes de uma mesma ninhada e do mesmo sexo (fêmea). Variaram-se as condições de temperatura no interior da câmara climática de 14°C a 35,5°C, de modo a atingir situações de estresse tanto por frio quanto por calor, sendo calculada a entalpia para os propósitos do presente estudo. O delineamento estatístico utilizado foi o inteiramente casualizado, com um único fator, a entalpia ambiente, com sete níveis (31,26; 39,56; 51,12; 59,24; 74,82; 82,96; 94,26 kJ.kg de ar seco-1). Foram realizadas medidas repetidas em intervalos de 30 minutos, em seis diferentes regiões corporais: cabeça (A), paleta (B), lombo (C), pernil (D), orelha (E) e timpânica (F). Para as regiões de A a E foram utilizados dois métodos de medida diferentes: datalogger de temperatura Thermochron iButton® - DS1921G e outro via termômetro de infravermelho Fluke® 566. Para a região F, utilizou-se um termômetro de infravermelho de testa e ouvido G-Tech - T1000. Todos com cinco repetições das medidas para cada variável, em cada situação ambiente. Com os resultados obtidos foi possível propor equações de regressão múltipla para a TR e FR, sendo esta última apontada pela análise de componentes principais como a melhor candidata a correlações com as temperaturas da superfície corporal e por ser um bom indicador da situação de estresse térmico. Por meio desses resultados foi possível observar que a região timpânica mostrou-se como a melhor opção para acompanhamento tanto da TR quanto da FR via termômetro de infravermelho (TiF), enquanto que ao utilizar sensores de temperatura da superfície corporal, a melhor opção foi a orelha (TbE) para predição de TR, e a região do lombo (TbC) para predição de FR.
Human constant influence in handling activities, besides raising production costs, becomes another stress source for the animals. In this sense, it becomes necessary the development of alternative methods, that can remotely monitor, in real time, animal\'s physical conditions, together with remote facilities control. In terms of identifying comfort or stressful thermal situations for animals, some indicators can be handy, such as rectal temperature (RT), which is a good indicator of the core body temperature, as well as, the respiratory rate (RR). Although, with the raising concerns about animal welfare, several questions are raised against invasive methods, encouraging the search for alternatives to RT measuring. The determination of body surface temperature values, trying to correlate them to RT and RR, emerges as an alternative. Thus, it\'s aimed, with this research, to identify the most adequate swine body surface region, in nursery phase, which presents better correlation with RT and RR. For that, an experiment was conducted, divided in two stages: stage 1) pre-experiment, being conducted with two animals in a climate chamber, varying temperature conditions and testing sensor fixation and data collection methods previously proposed; and stage 2) main experiment. The last one was conducted in a climate chamber, with five Landrace x Large White piglets, 30 days aged, from the same litter and of the same sex (female). Temperature conditions inside the chamber were varied from 14°C to 35.5°C, attaining stressful situations both for cold and heat, being calculated the enthalpy for this study purposes. The statistical design used was the completely randomized, with one factor only, the ambient enthalpy, in seven levels (31.26; 39.56; 51.12; 59.24; 74.82; 82.96; 94.26 kJ.kg of dry air-1). Repeated measures were taken in 30 minutes intervals, in six different body regions: head (A), shoulder (B), loin (C), ham (D), ear (E) and tympanic (F). For regions from A to E, two different methods were used: temperature datalogger Thermochron iButton® - DS1921G and infrared thermometer Fluke® 566. For region F, a forehead and ear infrared thermometer G-Tech - T1000 was used. All of them had five replicates of measures for each variable, in each environment situation. With the obtained data, it was possible to propound multiple regression equations for RT and RR, the last one being shown by principal components analysis as a better candidate to correlate to body surface temperatures and because it\'s a good indicator of the animal\'s thermal stress situation. By means of these results it was possible to observe that the tympanic region arises as the better option for monitoring RT and RR through infrared thermometer (TiF), while when using body surface temperature sensors, the best option was the ear (TbE) for predicting RT, and the loin region (TbC) for predicting RR.
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Ornelas, Mário André Santos de. "Electronic sow feeding : making sense of feeding data to support sow management." Master's thesis, Universidade de Lisboa, Faculdade de Medicina Veterinária, 2021. http://hdl.handle.net/10400.5/21184.

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Dissertação de Mestrado Integrado em Medicina Veterinária
This study aimed to address the knowledge gaps concerning how group-housed gestating sows interact with modern electronic sow feeding (ESF) stations and to explore the potential of data recorded by these systems to enhance farm management. ESF records of 276 sow-gestations, from a dynamic group of c. 120 individuals were investigated. Data was analysed to identify patterns in the use of feeding stations by animals, and associations between feeding patterns and reproductive performance. Throughout the approximate 15 weeks that each sow spent on the dry sow house during a gestation, the total number of visits to the feeding stations varied greatly among individuals (367.7 ± 282.8) most of which were non-feeding visits (60.01 ± 19.8%). Feeding activity was highly concentrated within the first 12 h of feeding cycles (23 h) and sows ate their daily rations predominantly on a single feeding station visit (98.3 ± 1.7%). A mixed effects model revealed a weak effect of time on the number of feeding station visits, and a negative relationship between parity and total number of visits (b = - 0.230, SE = 0.022, p < 0.001). Sows kept feeding order relatively stable across gestation, especially among those who fed first. Additionally, results suggested that with every additional parity, the odds of a sow being among the first 15% group members to feed increased by a factor of 2.16 [OR: 2.16, p<0.010]. Statistically significant associations were found between feeding patterns and pre weaning piglet mortality, but not with number of piglets born alive nor average birth weight. Median piglet mortality was lower for sows feeding last compared to those feeding first (4.5% vs 14.3%, p = 0.025) and with a middle position in the feeding order (4.5% vs 11.8%, p = 0.045). Individuals with a regular feeding time showed higher piglet mortality rates than those with moderately regular (14.3% vs 10.6%, p = 0.029) and irregular (14.3% vs 9.5%, p = 0.047) feeding times. Median piglet mortality was superior in fast feeding sows compared to those feeding slower (13.3% vs 9.1%, p = 0.053). This work enhances current understanding of how gestating sows interact with ESF stations and highlights the potential of ESF data to support sow management.
RESUMO - ALIMENTAÇÃO ELETRÓNICA DE PORCAS: UTILIZAÇÃO DOS SEUS REGISTOS COMO SUPORTE AO MANEIO DA PORCA REPRODUTORA - Em suinicultura, o sucesso dos sistemas produtivos é influenciado em larga escala pelo desempenho do efetivo reprodutor. O maneio alimentar assume, a esse respeito, um papel decisivo na performance reprodutiva a médio e longo prazos e deve ter presentes as diferentes necessidades de cada animal. A alimentação eletrónica permite que porcas gestantes sejam alimentadas de forma individual estando alojadas em grupos, conforme previsto na legislação europeia. Ao passo que a adoção deste sistema tem vindo a crescer ao longo dos anos, a valorização dos seus registos tem recebido pouca atenção. Não obstante, alguns estudos sugerem que a informação recolhida automaticamente pelas estações de alimentação eletrónica (EAE) pode constituir uma ferramenta de monitorização, capaz de fomentar o maneio individual da porca gestante. Este trabalho visa enriquecer a compreensão do modo como as porcas em gestação em grupo interagem com EAE e avaliar a utilidade dos registos gerados por este sistema para apoiar o maneio da porca reprodutora. Para o efeito, analisaram-se registos de 276 gestações pertencentes a um grupo dinâmico de cerca de 120 porcas com acesso a duas EAE. A análise focou-se na identificação de padrões de utilização das EAE e no estudo de relações entre padrões de alimentação e performance reprodutiva. ...
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Books on the topic "Precision livestock farming"

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Cox, S., ed. Precision Livestock Farming. The Netherlands: Wageningen Academic Publishers, 2003. http://dx.doi.org/10.3920/978-90-8686-515-4.

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Cox, S., ed. Precision Livestock Farming '05. The Netherlands: Wageningen Academic Publishers, 2005. http://dx.doi.org/10.3920/978-90-8686-548-2.

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Cox, S., ed. Precision livestock farming '07. The Netherlands: Wageningen Academic Publishers, 2007. http://dx.doi.org/10.3920/978-90-8686-604-5.

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Lokhorst, C., and P. W. G. Groot Koerkamp, eds. Precision livestock farming '09. The Netherlands: Wageningen Academic Publishers, 2009. http://dx.doi.org/10.3920/978-90-8686-663-2.

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Halachmi, Ilan, ed. Precision livestock farming applications. The Netherlands: Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5.

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Banhazi, T., V. Halas, and F. Maroto-Molina, eds. Practical Precision Livestock Farming. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-934-3.

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Cox, S. W. R. (Sidney Walter Reginald), Institutet för jordbruks- och miljöteknik, and Sveriges lantbruksuniversitet, eds. Precision livestock farming '05. Wageningen [Netherlands]: Wageningen Academic Publishers, 2005.

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Van Erp-Van der Kooij, E., ed. Precision technology and sensor applications for livestock farming and companion animals. The Netherlands: Wageningen Academic Publishers, 2021. http://dx.doi.org/10.3920/978-90-8686-917-6.

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Grandin, Temple, ed. Improving animal welfare: a practical approach. 3rd ed. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789245219.0000.

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Abstract The third edition of this book contains a total of 20 chapters (including 3 new chapters), including the implementation of an effective animal welfare programme; the importance of measurement to improve the welfare of livestock, poultry and fish; the social and ethical importance of agricultural animal welfare; the implementation of effective animal-based measurements for assessing animal welfare on farms and slaughter plants; how to improve livestock handling and reduce stress; painful husbandry procedures in livestock and poultry; the importance of good stockmanship and its benefits to animals; in-farm considerations of animal behaviour and emotions; improving livestock, poultry and fish welfare in slaughter plants with auditing programmes and animal-based measures; recommended on-farm euthanasia practices; welfare during transport of livestock and poultry; animal well-being on organic farms; a practical approach on sustainability for supply chain managers of meat, dairy and other animal proteins; the effect of economic factors on the welfare of livestock and poultry; practical approaches for changing and improving animal care and welfare; successful technology transfer of behavioural and animal welfare research to the farm and slaughter plant; technological innovations for individualized animal care and welfare; technology designed to enhance poultry welfare; precision livestock farming and technology in swine welfare and practical methods for improving the welfare of horses, donkeys and mules. There is also a list of videos that will allow students to see different types of farms and technology for raising broiler chickens, cattle, laying hens and pigs. This book provides practical information which will enable veterinarians, managers, animal scientists and policy makers to improve welfare. It will be especially useful for training animal welfare specialists.
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Precision Livestock Farming '07. Wageningen Pers, 2007.

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Book chapters on the topic "Precision livestock farming"

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Ozguven, Mehmet Metin. "Precision Livestock Farming." In The Digital Age in Agriculture, 29–58. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/b23229-2.

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Berckmans, D. "1.2. Smart farming for Europe: value creation through precision livestock farming." In Precision livestock farming applications, 25–36. The Netherlands: Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_1.2.

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Berckmans, D. "1.2. Smart farming for Europe: value creation through precision livestock farming." In Precision livestock farming applications, 25–36. The Netherlands: Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_2.

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Bewley, J. M., R. A. Russell, K. A. Dolecheck, and M. R. Borchers. "1.1. Precision dairy monitoring: what have we learned?" In Precision livestock farming applications, 13–24. The Netherlands: Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_1.

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Bewley, J. M., R. A. Russell, K. A. Dolecheck, and M. R. Borchers. "1.1. Precision dairy monitoring: what have we learned?" In Precision livestock farming applications, 13–24. The Netherlands: Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_1.1.

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Lehr, H., J. van den Bossche, M. Mergeay, and D. Rosés. "3.3. Developing SmartFarming entrepreneurship – II preparing precision lifestock farming spin-offs." In Precision livestock farming applications, 95–104. The Netherlands: Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_10.

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Banhazi, T., E. Vranken, D. Berckmans, L. Rooijakkers, and D. Berckmans. "3.4. Word of caution for technology providers: practical problems associated with large scale deployment of PLF technologies on commercial farms." In Precision livestock farming applications, 105–12. The Netherlands: Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_11.

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Johnston, D., D. A. Kenny, S. M. Waters, M. McCabe, A. K. Kelly, M. McGee, and B. Earley. "4.1. The effect of gradual weaning on haematological profiles and leukocyte relative gene expression levels of Holstein-Friesian and Jersey bull calves." In Precision livestock farming applications, 119–34. The Netherlands: Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_13.

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Liboreiro, D. N., K. S. Machado, M. I. Endres, and R. C. Chebel. "4.3. Investigating the use of rumination sensors during the peripartum period in dairy cows." In Precision livestock farming applications, 143–48. The Netherlands: Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_15.

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Scheel, C., I. Traulsen, and J. Krieter. "2.1. Detecting lameness in sows using acceleration data from ear tags." In Precision livestock farming applications, 37–44. The Netherlands: Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_2.1.

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Conference papers on the topic "Precision livestock farming"

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Andonovic, Ivan, Craig Michie, Philippe Cousin, Ahmed Janati, Congduc Pham, and Mamour Diop. "Precision Livestock Farming Technologies." In 2018 Global Internet of Things Summit (GIoTS). IEEE, 2018. http://dx.doi.org/10.1109/giots.2018.8534572.

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Gomes, Jonas S., José Maria N. David, Regina Braga, Victor Ströele, Wagner Arbex, Bryan Barbosa, Wneiton Luiz Gomes, and Leonardo M. Gravina Fonseca. "Architecture for Decision Support in Precision Livestock Farming." In Brazilian e-Science Workshop. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/bresci.2021.15787.

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The use of sensors in the agricultural domain generates a massive volume of heterogeneous data that must be treated, stored, and processed for decision-making. These decisions must be taken considering the diversity of devices and contextual information, which is often not considered but is important to the decision-making process. This paper presents an architecture to integrate data from sensors related to precision livestock farms. The integration and processing of these data can support decision-making, lead to more accurate results and enhance agribusiness sustainability.
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Milan, Hugo FM, Kristen M. Perano, and Kifle G. Gebremedhin. "Survey and future prospects in precision dairy farming." In 10th International Livestock Environment Symposium (ILES X). St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2018. http://dx.doi.org/10.13031/iles.18-053.

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Lopes, S. I., R. Bexiga, J. P. Araújo, J. L. Cerqueira, C. Abreu, C. Paredes, and J. M. Alonso. "90. Precision livestock farming for reproductive performance optimization: a survey." In 13th Congress of the European Society for Agricultural and Food Ethics. The Netherlands: Wageningen Academic Publishers, 2016. http://dx.doi.org/10.3920/978-90-8686-834-6_90.

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Niloofar, Parisa, Sanja Lazarova-Molnar, Deena P. Francis, Alexandru Vulpe, George Suciu, and Mihaela Balanescu. "Modeling and Simulation for Decision Support in Precision Livestock Farming." In 2020 Winter Simulation Conference (WSC). IEEE, 2020. http://dx.doi.org/10.1109/wsc48552.2020.9383975.

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Qiao, Yongliang, Daobilige Su, He Kong, Salah Sukkarieh, Sabrina Lomax, and Cameron Clark. "BiLSTM-based Individual Cattle Identification for Automated Precision Livestock Farming." In 2020 IEEE 16th International Conference on Automation Science and Engineering (CASE). IEEE, 2020. http://dx.doi.org/10.1109/case48305.2020.9217026.

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Vaughan, John, Peter M. Green, Michael Salter, Bruce Grieve, and Krikor B. Ozanyan. "Floor sensors of animal weight and gait for precision livestock farming." In 2017 IEEE SENSORS. IEEE, 2017. http://dx.doi.org/10.1109/icsens.2017.8234202.

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Csiba, Anita, and Arpad Ferencz. "THE EFFECT OF CIRCULAR FARMING APPLICATION IN LIVESTOCK FARMING FOR THE REDUCTION OF HARMFUL EMISSION." In 22nd SGEM International Multidisciplinary Scientific GeoConference 2022. STEF92 Technology, 2022. http://dx.doi.org/10.5593/sgem2022/4.1/s18.31.

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The Green Deal declares that climate change and environmental degradation means a threat to Europe and the whole world. In order to be able to respond effectively to the challenges in this context in the European Union, we need a new growth strategy that will transform the EU economy into a modern, resource-efficient and the economic growth is independent for the resource utilization economic. This research is a very timely issue in the livestock farming sector, because the livestock farming sector has a highest emission of ammonia and greenhouse gasses among all the agricultural sectors. The possible effective solution for this problem is the application of the circular farming in the manure management. The methodology of the test is to contact different precision technology applying companies, to assess the methods of the technologies and the assessment of the efficiency of the technologies used as far as production and the reduction of harmful emissions are concerned. In the course of research, we are assessing the achievement of the strategic goals set out the Digital Agricultural Strategy, the Common Agricultural Policy and the Green Deal in the case of the model livestock farms.
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Qiao, Yongliang, Daobilige Su, He Kong, Salah Sukkarieh, Sabrina Lomax, and Cameron Clark. "Data Augmentation for Deep Learning based Cattle Segmentation in Precision Livestock Farming." In 2020 IEEE 16th International Conference on Automation Science and Engineering (CASE). IEEE, 2020. http://dx.doi.org/10.1109/case48305.2020.9216758.

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Alexy, Merta, and Tames Haidegger. "Precision Solutions in Livestock Farming – feasibility and applicability of digital data collection." In 2022 IEEE 10th Jubilee International Conference on Computational Cybernetics and Cyber-Medical Systems (ICCC 2022). IEEE, 2022. http://dx.doi.org/10.1109/iccc202255925.2022.9922883.

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