Tag Archives: precision livestock farming

482-493 F. Kurras, L.S. Gravemeier, A. Dittmer, D. Kümper and M. Jakob
Automatic Monitoring of dairy cows’ lying behaviour using a computer vision system in open barns
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Automatic Monitoring of dairy cows’ lying behaviour using a computer vision system in open barns

F. Kurras¹, L.S. Gravemeier², A. Dittmer², D. Kümper³ and M. Jakob¹*

¹Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Department of Technological Assessment and Substance Cycles, Max-Eyth-Allee 100, DE14469 Potsdam, Germany
²German Research Center for Artificial Intelligence GmbH, Smart Enterprise Engineering, Parkstr. 40, DE49080 Osnabrück, Germany
³iotec GmbH, Albert-Einstein-Straße 1, 49076 Osnabrück, Germany
*Correspondence: fkurras@atb-potsdam.de

Abstract:

Precision Livestock Farming offers opportunities for automated, continuous monitoring of animals, their productivity, welfare and health. The video-based assessment of animal behaviour is an automated, non-invasive and promising application. The aim of this study is to identify possible parameters in dairy cows’ lying behaviour that are the basis for a holistic computer vision-based system to assess animal health and welfare. Based on expert interviews and a literature review, we define parameters and their optimum in form of gold standards to evaluate lying behaviour automatically. These include quantitative parameters such as daily lying time, lying period length, lying period frequency and qualitative parameters such as extension of the front and hind legs, standing in the lying cubicles, or total lateral position. The lying behaviour is an example within the research context for the development of a computer vision-based tool for automated detection of animal behaviour and appropriate housing design.

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1300–1306 K. Grausa, V. Komasilovs, L. Brossard, N. Quiniou, M. Marcon, M. Querne, A. Kviesis, N. Bumanis and A. Zacepins
Usability improvements of the Thermipig model for precision pig farming
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Usability improvements of the Thermipig model for precision pig farming

K. Grausa¹, V. Komasilovs¹, L. Brossard², N. Quiniou³, M. Marcon³, M. Querne³, A. Kviesis¹, N. Bumanis¹ and A. Zacepins¹*

¹University of Life Sciences and Technologies, Faculty of Information Technologies, Department of Computer Systems, Liela iela 2, LV-3001 Jelgava, Latvia
²PEGASE, INRAE, Agrocampus Ouest, 35590 Saint-Gilles, France
³IFIP-Institut du Porc, BP35104, 35651 Le Rheu cedex, France
Correspondence: aleksejs.zacepins@llu.lv

Abstract:

Pig livestock farming systems encounter several economic and environmental challenges, connected with meat price decrease, sanitary norms, emissions etc. To deal with these issues, methods and models to assess the performance of a pig production system have been developed. For instance, Thermipig model represents the pig fattening room and simulates performances of pigs at the batch level, taking into account interactions between the individual variability of pigs, farmer’s practices, room characteristics and outdoor climate conditions. The model requires some static basic inputs fulfilled in several spreadsheets (such as rooms, pigs, and dietary characteristics) but also data files for voluminous variable inputs (such as outdoor temperature or climate control box parameters) for further modelling and outcome producing. This leads to challenges in data providing by the farmers and have to be improved. This paper deals with the implementation of the separate modules of the developed data warehouse system for usability improvements of the Thermipig model. The idea is to substitute input from the data files with online data input and automated variable processing by the model using the python script for connection to the remote data warehouse. The data warehouse system is extended with ‘Property Sets’ section dealing with all the operations that can be performed to a set of input variables. This approach demonstrates the ability of the data warehouse to act as data supplier for the remote model. As well the outcome of the model is also transferable back to the data warehouse for evaluation. This work is done within the Era-Net SuSan PigSys project – Improving pig system performance through a whole system approach.

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187-194 V. Poikalainen, J. Praks, I. Veermäe and E. Kokin
Infrared temperature patterns of cow’s body as an indicator for health control at precision cattle farming
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Infrared temperature patterns of cow’s body as an indicator for health control at precision cattle farming

V. Poikalainen, J. Praks, I. Veermäe and E. Kokin

Estonian University of Life Sciences, Kreutzwaldi 1, EE51014, Tartu, Estonia

Abstract:

Cows’ infrared radiation temperature study was carried out at experimental cowshed (120 cows) of Estonian University of Life Sciences. Thermal image scanner Fluke TiS was used for obtaining 640×480 pixels thermal images with resolution of 0.1°C. The temperature distribution pattern of different parts of cow’s body was estimated and analysed with SmartView software. Special attention was paid to udder, feet and areas with skin injuries. It was estimated that the temperature varies considerably at different parts of the body. Radiation temperature of healthy udder did not change considerably after milking. It means that automatic monitoring of udder temperature is possible not only in milking parlour or milking robot but also in other places where cows are identified. The udder thermograms enable to assess the milking hygiene, as the cleanliness of udder surface influences the measurement results, especially average temperature. The temperature of legs was lowest at the hoofs and highest at coronary band. Differences from this distribution may be used for estimation of leg disorders. Thermal images can be also successfully used for detection of skin injuries. Radiation temperature of injured and depilous locations was higher by several degrees than their surroundings. The study showed that thermal images analysis is promising method to be implemented at precision cattle farming.

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