Article (Scientific journals)
Potential of milk mid-infrared spectra to predict nitrogen use efficiency of individual dairy cows in early lactation
Grelet, Clément; Froidmont, Éric; Foldager, Leslie et al.
2020In Journal of Dairy Science, 103 (5), p. 4435-4445
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Keywords :
Fourier-transform mid-infrared spectrometry; nutrition; environment; modeling
Abstract :
[en] Improving nitrogen use efficiency (NUE) at both the individual cow and the herd level has become a key target in dairy production systems, for both environmental and economic reasons. Cost-effective and large-scale phenotyping methods are required to improve NUE through genetic selection and by feeding and management strategies. The aim of this study was to evaluate the possibility of using mid-infrared (MIR) spectra of milk to predict individual dairy cow NUE during early lactation. Data were collected from 129 Holstein cows, from calving until 50 d in milk, in 3 research herds (Denmark, Ireland, and the UK). In 2 of the herds, diets were designed to challenge cows metabolically, whereas a diet reflecting local management practices was offered in the third herd. Nitrogen intake (kg/d) and nitrogen excreted in milk (kg/d) were calculated daily. Nitrogen use efficiency was calculated as the ratio between nitrogen in milk and nitrogen intake, and expressed as a percentage. Individual daily values for NUE ranged from 9.7 to 81.7%, with an average of 36.9% and standard deviation of 10.4%. Milk MIR spectra were recorded twice weekly and were standardized into a common format to avoid bias between apparatus or sampling periods. Regression models predicting NUE using milk MIR spectra were developed on 1,034 observations using partial least squares or support vector machines regression methods. The models were then evaluated through (1) a cross-validation using 10 subsets, (2) a cow validation excluding 25% of the cows to be used as a validation set, and (3) a diet validation excluding each of the diets one by one to be used as validation sets. The best statistical performances were obtained when using the support vector machines method. Inclusion of milk yield and lactation number as predictors, in combination with the spectra, also improved the calibration. In cross-validation, the best model predicted NUE with a coefficient of determination of cross-validation of 0.74 and a relative error of 14%, which is suitable to discriminate between low- and high-NUE cows. When performing the cow validation, the relative error remained at 14%, and during the diet validation the relative error ranged from 12 to 34%. In the diet validation, the models showed a lack of robustness, demonstrating difficulties in predicting NUE for diets and for samples that were not represented in the calibration data set. Hence, a need exists to integrate more data in the models to cover a maximum of variability regarding breeds, diets, lactation stages, management practices, seasons, MIR instruments, and geographic regions. Although the model needs to be validated and improved for use in routine conditions, these preliminary results showed that it was possible to obtain information on NUE through milk MIR spectra. This could potentially allow large-scale predictions to aid both further genetic and genomic studies, and the development of farm management tools. © 2020 American Dairy Science Association
Disciplines :
Animal production & animal husbandry
Author, co-author :
Grelet, Clément ;  Walloon Agricultural Research Center (CRA-W), Gembloux, B-5030, Belgium
Froidmont, Éric;  Walloon Agricultural Research Center (CRA-W), Gembloux, B-5030, Belgium
Foldager, Leslie;  Department of Animal Science, Aarhus University, Tjele, Dk-8830, Denmark, Bioinformatics Research Centre, Aarhus University, Aarhus, Dk-8000, Denmark
Salavati, Mazdak;  Royal Veterinary College (RVC), London, NW1 0TU, United Kingdom
Hostens, Miel;  Ghent University, Merelbeke, 9820, Belgium
Ferris, Conrad P.W.;  Agri-Food and Biosciences Institute (AFBI), Belfast, BT9 5PX, Ireland
Ingvartsen, Klaus Lønne;  Department of Animal Science, Aarhus University, Tjele, Dk-8830, Denmark
Crowe, Mark A.;  UCD School of Veterinary Medicine, University College DublinDublin 4, Ireland
Sorensen, Martin Tang;  Department of Animal Science, Aarhus University, Tjele, Dk-8830, Denmark
Fernandez Pierna, Juan Antonio ;  Université de Liège - ULiège > Département GxABT > Département GxABT
Vanlierde, Amélie ;  Walloon Agricultural Research Center (CRA-W), Gembloux, B-5030, Belgium
Gengler, Nicolas  ;  Université de Liège - ULiège > Département GxABT > Ingénierie des productions animales et nutrition
Dehareng, Frédéric  ;  Walloon Agricultural Research Center (CRA-W), Gembloux, B-5030, Belgium
More authors (3 more) Less
Other collaborator :
GplusE Consortium
Language :
English
Title :
Potential of milk mid-infrared spectra to predict nitrogen use efficiency of individual dairy cows in early lactation
Publication date :
May 2020
Journal title :
Journal of Dairy Science
ISSN :
0022-0302
eISSN :
1525-3198
Publisher :
Elsevier Inc.
Volume :
103
Issue :
5
Pages :
4435-4445
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
Seventh Framework Programme, FP7: 613689
Available on ORBi :
since 28 April 2020

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