Dry Matter Intake Prediction from Milk Spectra in Sarda Dairy Sheep

SIMPLE SUMMARY: On livestock farms, measuring individual intake is difficult to assess, but is a very important value for evaluating the feed efficiency of livestock. Feed efficiency has an impact on farm efficiency and, thus, on the economic balance sheet. The purpose of this work was to predict the intake of lactating Sarda ewes from milk spectra using multivariate approaches. Individual intake was found to be moderately correlated with the wavenumbers of the milk spectra. The preliminary results of this study showed that individual intake and, thus, feeding efficiency can be routinely estimated from milk spectra. Further large-scale studies may allow for a rapid, low-cost indicator to be used to keep constant tabs on feeding and farm efficiency. 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.