Predicting dry matter intake of grazing dairy cows using near infrared reflectance spectroscopy

摘要

Genetic improvements in feed efficiency require phenotypic records on thousands of animals. Tools to predict dry matter intake (DMI) should be accurate, low-cost, facilitate prediction at multiple timepoints and be amenable for use in a very large population of commercial animals. The aim of this study was to evaluate the potential of Near Infrared Reflectance Spectroscopy (NIRS) analysis of faeces in combination with parity to predict the DMI of grazing dairy cows. Faecal samples were obtained fromthree different grazing experiments where DMI was available from 142 cows with 380 DMI estimates. Dried and milled faecal samples were scanned at 2 nm intervals over a wavelength range of 1,100-2,500 nm to measure NIRS absorbance. Partial least squares regression was used to develop an equation to predict DMI using n-alkane predicted DMI values. The developed equations were moderately accurate with a mean bias of 0.06 kg, slope between true and predicted values of DMI of 0.88 and a coefficient of determination between true and predicted values of DMI of 0.53. Equations developed using faecal NIRS wavelengths and parity show potential at predicting the DMI of grazing dairy cows.