Potential of milk mid-infrared spectra to predict nitrogen use efficiency of individual dairy cows in early lactation

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dc.contributor.authorGrelet, C.
dc.contributor.authorFroidmont, E.
dc.contributor.authorFoldager, L.
dc.contributor.authorSalavati, M.
dc.contributor.authorHostens, M.
dc.contributor.authorFerris, Conrad P.
dc.contributor.authorIngvartsen, K.L.
dc.contributor.authorCrowe, M.A.
dc.contributor.authorSorensen, M.T.
dc.contributor.authorFernandez Pierna, J.A.
dc.contributor.authorVanlierde, A.
dc.contributor.authorGengler, N.
dc.contributor.authorGplusE Consortium
dc.contributor.authorDehareng, F.
dc.date.accessioned2021-03-26T11:39:31Z
dc.date.available2021-03-26T11:39:31Z
dc.date.issued2020-03-15
dc.descriptionPublication history: Accepted - 6 January 2020; Published online - 5 Marc 2020en_US
dc.description.abstractImproving 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.en_US
dc.description.sponsorshipThe Genotype Plus Environment (GplusE) Project has received funding from the European Union's Seventh Framework Programme for research, technological development, and demonstration under grant agreement no. 613689.en_US
dc.identifierhttp://hdl.handle.net/20.500.12518/222
dc.identifier.citationGrelet, C., Froidmont, E., Foldager, L., Salavati, M., Hostens, M., Ferris, C. P., Ingvartsen, K. L., Crowe, M. A., Sorensen, M. T., Fernandez Pierna, J. A., Vanlierde, A., Gengler, N. and Dehareng, F. (2020) ‘Potential of milk mid-infrared spectra to predict nitrogen use efficiency of individual dairy cows in early lactation’, Journal of Dairy Science. American Dairy Science Association, 103(5), pp. 4435–4445. doi: 10.3168/jds.2019-17910en_US
dc.identifier.issn1525-3198
dc.identifier.urihttps://doi.org/10.3168/jds.2019-17910
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2020, The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.subjectFourier-transform mid-infrared spectrometryen_US
dc.subjectnutritionen_US
dc.subjectenvironmenten_US
dc.subjectmodelingen_US
dc.titlePotential of milk mid-infrared spectra to predict nitrogen use efficiency of individual dairy cows in early lactationen_US
dc.typeArticleen_US
dcterms.dateAccepted2020-01-06
dcterms.dateSubmitted2019-11-14

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