Robustness and sensitivity of a blueprint for on-farm estimation of dairy cow energy balance
| Autor: | M G G Chagunda, Vivi M. Thorup, Nicolas Friggens, Amélie Fischer, Martin Riis Weisbjerg |
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| Přispěvatelé: | Modélisation Systémique Appliquée aux Ruminants (MoSAR), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Auning Data, Scotland's Rural College (SRUC), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Institut de l'élevage (IDELE), Department of Animal Science, AU Foulum, Aarhus University [Aarhus], Scotland's Rural College (SCUR), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), Institut de l'Elevage, Aarhus University, AgroParisTech-Institut National de la Recherche Agronomique (INRA) |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences condition scoring Energy balance état corporel body reserve robustness bilan énergétique Lactation dairy cows Mathematics 2. Zero hunger Animal biology precision agriculture [SDV.BA]Life Sciences [q-bio]/Animal biology modèle d'estimation food and beverages 04 agricultural and veterinary sciences weight mass Body reserve Decision support On-farm Precision livestock agriculture de précision Agricultural sciences Milk medicine.anatomical_structure réserve corporelle vache laitière Female exploitation agricole poids Smoothing Farms decision support Milking modelling 03 medical and health sciences Animal science Body condition score Robustness (computer science) Biologie animale Genetics medicine Animals modélisation holdings Body Weight 0402 animal and dairy science Automatic milking 040201 dairy & animal science energy balance robustesse 030104 developmental biology Scotland Herd Cattle Animal Science and Zoology precision livestock Energy Metabolism Sciences agricoles outil d'aide à la décision analyse de sensibilité on-farm Food Science |
| Zdroj: | Journal of Dairy Science 7 (101), 6002-6018. (2018) Journal of Dairy Science Journal of Dairy Science, American Dairy Science Association, 2018, 101 (7), pp.6002-6018. ⟨10.3168/jds.2017-14290⟩ Thorup, V M, Chagunda, M G G, Fischer, A, Weisbjerg, M R & Friggens, N C 2018, ' Robustness and sensitivity of a blueprint for on-farm estimation of dairy cow energy balance ', Journal of Dairy Science, vol. 101, no. 7, pp. 6002-6018 . https://doi.org/10.3168/jds.2017-14290 |
| ISSN: | 0022-0302 |
| DOI: | 10.3168/jds.2017-14290⟩ |
| Popis: | Excessive negative energy balance (EB) has been associated with decreased reproductive performance and increased risk of lameness and metabolic diseases. On-farm, automated EB estimates for individual cows would enable dairy farmers to detect excessive negative EB early and act to minimize its extent and duration by altering feeding. Previously, we have shown that EB can be estimated from frequent measurements of body weight (BW) and body condition score (BCS) changes, referred to as EBbody. In this study, we investigated the robustness and sensitivity of the EBbody method to assess its genericity and on-farm applicability. We used 5 data sets with BW of lactating cows (name of data set in parenthesis): 65 Holstein cows in a French feeding trial (INRA); 6 Holstein cows in a British feeding trial (Friggens); 31 Holstein cows and 17 Jersey cows in a Danish feeding trial (DCRC); 140 Holstein cows in a British feeding trial (Scotland's Rural College, SRUC); and 1,592 Holstein cows on 9 Danish farms with milking robots (automatic milking system). We used the INRA and Friggens data sets to develop a dynamic formula to correct BW for increasing residual gut-fill (RGF) during early lactation. With the DCRC data, we tested the effect of smoothing parameters and weighing frequency on EBbody. Also, 2 robustness tests were performed using the SRUC data to test the effect of diet change on BW and the automatic milking system data to test the effect of farm on BW variation. Finally, we combined the results into a blueprint describing different ways to calculate EBbody depending on the purpose and on the availability of BCS. The dynamic RGF adjustment resulted in a lower empty BW during early lactation than that obtained with the previously used constant RGF. The double-exponential smoothing method used to correct for meal-related gut-fill was robust to choice of smoothing parameters. Cows should be weighed at least once every 4 d during early lactation to capture the duration of negative EBbody. Our EBbody method proved robust to diet changes. Finally, although cow BW varied significantly between farms, the quantile regression smoothing of BW did not bias the estimation of weight differences between herds. In conclusion, these results validate the applicability of the EBbody method to estimate EB across a range of farm conditions, and we provided a blueprint that enables the estimation of EBbody for individual cows on-farm using only frequent BW, in combination with BCS when available. |
| Databáze: | OpenAIRE |
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