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Dry Matter Intake Prediction from Milk Spectra in Sarda Dairy Sheep

Authors :
Antonello Ledda
Silvia Carta
Fabio Correddu
Alberto Cesarani
Alberto Stanislao Atzori
Gianni Battacone
Nicolò Pietro Paolo Macciotta
Source :
Animals, Vol 13, Iss 4, p 763 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Individual dry matter intake (DMI) is a relevant factor for evaluating feed efficiency in livestock. However, the measurement of this trait on a large scale is difficult and expensive. DMI, as well as other phenotypes, can be predicted from milk spectra. The aim of this work was to predict DMI from the milk spectra of 24 lactating Sarda dairy sheep ewes. Three models (Principal Component Regression, Partial Least Squares Regression, and Stepwise Regression) were iteratively applied to three validation schemes: records, ewes, and days. DMI was moderately correlated with the wavenumbers of the milk spectra: the largest correlations (around ±0.30) were observed at ~1100–1330 cm−1 and ~2800–3000 cm−1. The average correlations between real and predicted DMI were 0.33 (validation on records), 0.32 (validation on ewes), and 0.23 (validation on days). The results of this preliminary study, even if based on a small number of animals, demonstrate that DMI can be routinely estimated from the milk spectra.

Details

Language :
English
ISSN :
20762615
Volume :
13
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Animals
Publication Type :
Academic Journal
Accession number :
edsdoj.31ddb11814088aabe0c1669d7835a
Document Type :
article
Full Text :
https://doi.org/10.3390/ani13040763