Tag Archives: dairy cattle

39-48 J. Frorip, E. Kokin, J. Praks, V. Poikalainen, A. Ruus, I. Veermäe, L.Lepasalu, W. Schäfer, H. Mikkola, J. Ahokas
Energy consumption in animal production – case farm study
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Energy consumption in animal production – case farm study

J. Frorip¹, E. Kokin¹, J. Praks¹, V. Poikalainen¹, A. Ruus¹, I. Veermäe¹, L.Lepasalu¹, W. Schäfer², H. Mikkola³, J. Ahokas³

¹Estonian University of Life Sciences, Kreutzwaldi 1, EE51014, Tartu, Estonia;
e-mail: juri@monte.ee
²MTT Agrifood Research Finland, Agricultural Engineering Research
(MTT/VAKOLA), Vakolantie 55, FI-03400 Vihti, Uusimaa, Finland;
e-mail: winfried.schafer@mtt.fi
³Department of Agrotechnology, University of Helsinki, P.O. Box 28 (Koetilantie 3),
FI-00014 Helsinki, Finland;
e-mail: Jukka.ahokas@helsinki.fi; hannu.j.mikkola@helsinki.fi


The objective of this study was to analyse the energy use by the dairy case-farm with un-insulated cowsheds in Estonia for the period of 2009-2010. The energy balance calculation includes the direct energy input of fuel, lubricants and electricity and the indirect input of forage, cereals, concentrates for young stock, dairy cattle and buildings. Energy outputs are milk, meat, and manure. The energy values were calculated multiplying the quantities of inputs and outputs by their energy conversion factors. The quantitative parameters of the inputs and outputs are based on book-keeping data, the energy conversion factors of feed were measured. The energy output-input ratio of the case-farm was 1.88 in 2009 and 1.85 in 2010. Energy input of milk was 5.4 and 5.3 per MJ kg-1, respectively. Our study indicated that the case farm energy consumption is generally higher than that of comparable European dairy farms. The further research is needed to find the reason of mentioned differences.

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216-225 V. Poikalainen, J. Praks, E. Kokin, A. Aland, I. Veermäe, S. Peets, J. Ahokas, M. Pastell, M. Hautala, D. Berckmans, C. Bahr, and D. Miljkovic
Elaboration of Basic Methods for Automatic Analysis of Cows’ Gait
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Elaboration of Basic Methods for Automatic Analysis of Cows’ Gait

V. Poikalainen¹, J. Praks¹, E. Kokin¹, A. Aland¹, I. Veermäe¹, S. Peets¹, J. Ahokas², M. Pastell², M. Hautala², D. Berckmans³, C. Bahr³, and D. Miljkovic³

1 Estonian University of Life Sciences, 1 Kreutzwaldi Str., EE51014 Tartu, Estonia
e-mail: vaino.poikalainen@emu.ee
² University of Helsinki, Department of Agrotechnology, P.O. Box 28 (Koetilantie 3),
00014 Helsinki, Finland; e-mail: Jukka.ahokas@helsinki.fi
³ Division Measure, Model & Manage Bioresponses (M3-BIORES), Katholike Universiteit
Leuven, Kasteelpark Arenberg 30, B-3001 Leuven, Belgium
e-mail: Claudia.Bahr@biw.kuleuven.be


Two different methods for automatic registration and analysis were used to produce data for comparison and analysis of lame and healthy animals’ gait in Estonia. A walk over mat with two quazi-piezoelectric sensors was elaborated and tested in co-operation with University of Helsinki. Preliminary analysis indicates that lameness can be seen as asymmetric gait and thus the quazi-piezoelectric walk-over mat is a promising tool for automatic leg problem detection.
A video-system was introduced to record walking pattern of cows in co-operation with Catholic University of Leuven. For video recordings three cameras were used to obtain top, side and leg views with StreamPix software video-signal capture. Possibilities of image based separation of dairy cows with real time vision system and preliminary settlement of this was developed. A model-based motion scoring system is proposed for derivation of image parameters needed for lameness detection.
About 600 cows once a week were investigated in a large dairy farm during four months’ period.
Dairy cows’ gait pattern was recorded with the aid of quazi-piezoelectric walk-over mat and video-system. Preliminary lameness scoring was performed in the cowshed visually by two experts. These scoring results were later specified by expert commission on the basis of video-recordings. Lameness scores (according to Sprecher et al) were assigned as follows: 1–6,012 cases, 2–1,181 cases, 3–522 cases, 4–105 cases and 5–37 cases from total 10,653 cases. The database of cows’ identification numbers, lameness scores and disordered legs description was created, that allows synchronization of walk-over mat signals data and video files.

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