Evaluation of National Academies of Sciences, Engineering, and Medicine (NASEM, 2021) feed evaluation model on predictions of milk protein yield on Québec commercial dairy farms
A recent study assessed the ability of 4 feed evaluation models to predict milk protein yield (MPY) in a commercial context, with data of 541 cows from 23 dairy herds in the province of Québec, Canada. However, the recently published Nutrient Requirements of Dairy Cattle from the National Academies...
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Elsevier
2024-11-01
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| Series: | JDS Communications |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666910224000747 |
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| author | S. Binggeli H. Lapierre R. Martineau D.R. Ouellet E. Charbonneau D. Pellerin |
| author_facet | S. Binggeli H. Lapierre R. Martineau D.R. Ouellet E. Charbonneau D. Pellerin |
| author_sort | S. Binggeli |
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| description | A recent study assessed the ability of 4 feed evaluation models to predict milk protein yield (MPY) in a commercial context, with data of 541 cows from 23 dairy herds in the province of Québec, Canada. However, the recently published Nutrient Requirements of Dairy Cattle from the National Academies of Sciences, Engineering, and Medicine (NASEM, 2021) was not released at that time. Thus, the current study evaluated NASEM using the same dataset. To be consistent with the previous study, predicted DMI was used. Therefore, MPY was predicted using the 2 estimations of DMI proposed by NASEM: one based on animal characteristics only (DMIAo) and one also including ration characteristics (DMIA&R). For each type of DMI estimates, 2 MPY predictions were made, using (1) the multivariate equation directly published in NASEM and (2) a variable efficiency of utilization of MP predicted using inputs and outputs from NASEM, published a posteriori. With the 2 approaches, multivariate and variable efficiency, the DMIA&R yielded the best MPY predictions. The multivariate equation showed a regression bias between observed and predicted MPY with both DMI estimations. The estimated variable efficiency allowed for MPY predictions without mean and regression biases. With DMIA&R, concordance correlation coefficients (CCC) were 0.72 and 0.78 for MPY predicted using the multivariate and variable efficiency equations, respectively. In comparison, DMIAo CCC were 0.60 and 0.71, respectively. In conclusion, on commercial farms, where dairy rations are usually optimized for a group of cows, estimates of DMI based on animal and rations characteristics yielded the best MPY predictions. The multivariate equation from NASEM predicted MPY with a regression bias, whereas the variable efficiency of utilization of MP based on MP and energy supplies resulted in no bias in MPY predictions. |
| format | Article |
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| institution | Kabale University |
| issn | 2666-9102 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | JDS Communications |
| spelling | doaj-art-2d2497ba9c0149d297d549905371e4db2024-11-22T07:39:17ZengElsevierJDS Communications2666-91022024-11-0156543547Evaluation of National Academies of Sciences, Engineering, and Medicine (NASEM, 2021) feed evaluation model on predictions of milk protein yield on Québec commercial dairy farmsS. Binggeli0H. Lapierre1R. Martineau2D.R. Ouellet3E. Charbonneau4D. Pellerin5Département des sciences animales, Université Laval, Québec, QC, Canada G1V 0A6; Corresponding authorSherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC, Canada, J1M 0C8Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC, Canada, J1M 0C8Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC, Canada, J1M 0C8Département des sciences animales, Université Laval, Québec, QC, Canada G1V 0A6Département des sciences animales, Université Laval, Québec, QC, Canada G1V 0A6A recent study assessed the ability of 4 feed evaluation models to predict milk protein yield (MPY) in a commercial context, with data of 541 cows from 23 dairy herds in the province of Québec, Canada. However, the recently published Nutrient Requirements of Dairy Cattle from the National Academies of Sciences, Engineering, and Medicine (NASEM, 2021) was not released at that time. Thus, the current study evaluated NASEM using the same dataset. To be consistent with the previous study, predicted DMI was used. Therefore, MPY was predicted using the 2 estimations of DMI proposed by NASEM: one based on animal characteristics only (DMIAo) and one also including ration characteristics (DMIA&R). For each type of DMI estimates, 2 MPY predictions were made, using (1) the multivariate equation directly published in NASEM and (2) a variable efficiency of utilization of MP predicted using inputs and outputs from NASEM, published a posteriori. With the 2 approaches, multivariate and variable efficiency, the DMIA&R yielded the best MPY predictions. The multivariate equation showed a regression bias between observed and predicted MPY with both DMI estimations. The estimated variable efficiency allowed for MPY predictions without mean and regression biases. With DMIA&R, concordance correlation coefficients (CCC) were 0.72 and 0.78 for MPY predicted using the multivariate and variable efficiency equations, respectively. In comparison, DMIAo CCC were 0.60 and 0.71, respectively. In conclusion, on commercial farms, where dairy rations are usually optimized for a group of cows, estimates of DMI based on animal and rations characteristics yielded the best MPY predictions. The multivariate equation from NASEM predicted MPY with a regression bias, whereas the variable efficiency of utilization of MP based on MP and energy supplies resulted in no bias in MPY predictions.http://www.sciencedirect.com/science/article/pii/S2666910224000747 |
| spellingShingle | S. Binggeli H. Lapierre R. Martineau D.R. Ouellet E. Charbonneau D. Pellerin Evaluation of National Academies of Sciences, Engineering, and Medicine (NASEM, 2021) feed evaluation model on predictions of milk protein yield on Québec commercial dairy farms JDS Communications |
| title | Evaluation of National Academies of Sciences, Engineering, and Medicine (NASEM, 2021) feed evaluation model on predictions of milk protein yield on Québec commercial dairy farms |
| title_full | Evaluation of National Academies of Sciences, Engineering, and Medicine (NASEM, 2021) feed evaluation model on predictions of milk protein yield on Québec commercial dairy farms |
| title_fullStr | Evaluation of National Academies of Sciences, Engineering, and Medicine (NASEM, 2021) feed evaluation model on predictions of milk protein yield on Québec commercial dairy farms |
| title_full_unstemmed | Evaluation of National Academies of Sciences, Engineering, and Medicine (NASEM, 2021) feed evaluation model on predictions of milk protein yield on Québec commercial dairy farms |
| title_short | Evaluation of National Academies of Sciences, Engineering, and Medicine (NASEM, 2021) feed evaluation model on predictions of milk protein yield on Québec commercial dairy farms |
| title_sort | evaluation of national academies of sciences engineering and medicine nasem 2021 feed evaluation model on predictions of milk protein yield on quebec commercial dairy farms |
| url | http://www.sciencedirect.com/science/article/pii/S2666910224000747 |
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