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

摘要

The objective of this study was to compare midinfraredreflectance spectroscopy (MIRS) analysis ofmilk and near-infrared reflectance spectroscopy (NIRS)analysis of feces with regard to their ability to predictthe dry matter intake (DMI) of lactating grazing dairycows. A data set comprising 1,074 records of DMI from457 cows was available for analysis. Linear regressionand partial least squares regression were used to developthe equations using the following variables: (1)milk yield (MY), fat percentage, protein percentage,body weight (BW), stage of lactation (SOL), and parity(benchmark equation); (2) MIRS wavelengths; (3)MIRS wavelengths, MY, fat percentage, protein percentage,BW, SOL, and parity; (4) NIRS wavelengths;(5) NIRS wavelengths, MY, fat percentage, proteinpercentage, BW, SOL, and parity; (6) MIRS and NIRSwavelengths; and (7) MIRS wavelengths, NIRS wavelengths,MY, fat percentage, protein percentage, BW,SOL, and parity. The equations were validated bothwithin herd using animals from similar experimentsand across herds using animals from independent experiments.The accuracy of equations was greater forwithin-herd validation compared with across-herdsvalidation. Across-herds validation was deemed themore suitable method to assess equations for robustnessand real-world application. The benchmark equationwas more accurate [coefficient of determination(R~2) = 0.60; root mean squared error (RMSE) = 1.68kg] than MIRS alone (R~2 = 0.30; RMSE = 2.23 kg)or NIRS alone (R~2 = 0.16; RMSE = 2.43 kg). Thecombination of the benchmark equation with MIRS (R~2= 0.64; RMSE = 1.59 kg) resulted in slightly superiorfitting statistics compared with the benchmark equationalone. The combination of the benchmark equationwith NIRS (R~2 = 0.58; RMSE = 1.71 kg) did notresult in a more accurate prediction equation than thebenchmark equation. The combination of MIRS andNIRS wavelengths resulted in superior fitting statisticscompared with either method alone (R~2 = 0.36; RMSE= 2.15 kg). The combination of the benchmark equationand MIRS and NIRS wavelengths resulted in themost accurate equation (R~2 = 0.68; RMSE = 1.52 kg).A further analysis demonstrated that Holstein-Friesiancows could predict the DMI of Jersey × Holstein-Friesian crossbred cows using both MIRS and NIRS.Similarly, the Jersey × Holstein-Friesian animals couldpredict the DMI of Holstein-Friesian cows using bothMIRS and NIRS. The equations developed in this studyhave the capacity to predict DMI of grazing dairy cows.From a practicality perspective, MIRS in combinationwith variables in the benchmark equation is the mostsuitable equation because MIRS is currently used on allmilk-recorded milk samples from dairy cows.