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Master Thesis

Utilisation de l'imagerie 3D pour suivre la croissance des vaches laitières, prédire les quantités ingérées et approcher l'efficience alimentaire

Abstract : Three-dimensional imaging (3D) is a technology that allows access to new interesting phenotypes. The objective of this work was to analyze the growth of 16 lactating cows, including 8 primiparous cows, by monitoring daily live weight and monthly body measurements using 3D imaging. A second objective was to estimate the ruminal content of 58 lactating cows, based on daily feed intake data and on the measurement of the volume of the abdomen taken once and the same day for all cows. All morphological indicators had a continuous growth during at least the first 3 lactations, with a greater growth for primiparous cows. The partial volume is a good predictor of live weight (R² = 0.92), with a prediction error of 25.8 kg, which is reduced to 13.7 kg when the prediction is made within cow. Volume of the abdomen estimates feed intake with a low error of 1.79 kg dry matter. For a similar feed intake, the more feed efficient the cows are, the larger their abdominal volume is, and therefore, the longer the residence time of feed (defined by the ratio volume of abdomen on feed intake) is in the rumen. The hypothesis of better digestion is not verified with methane emissions because for a given feed intake, emitted methane is moderately correlated with the volume of the abdomen (r = 0.41). 3D imaging, as a timesaving and low cost method, finally allows access to multiple traits, which are of high interest for dairy livestock farming, with no need to purchase several sensors.
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Master Thesis
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https://dumas.ccsd.cnrs.fr/dumas-02372520
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Submitted on : Wednesday, November 20, 2019 - 2:35:19 PM
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Caroline Xavier. Utilisation de l'imagerie 3D pour suivre la croissance des vaches laitières, prédire les quantités ingérées et approcher l'efficience alimentaire. Sciences du Vivant [q-bio]. 2019. ⟨dumas-02372520⟩

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