Estimation of dry matter, crude protein and starch values in mixed feeds by near-infrared reflectance (NIR) spectroscopy

Abstract

This study aims to determine the levels of dry matter, crude protein, and starch widely used in ruminant feeding, in dairy and beef cattle mixed feeds based on the measurements taken from two different Near-Infrared Reflectance (NIR) devices. The chemical analyses of the mixed feed samples used in the study were performed and the reference values (REF) were determined. In the research, two different NIR devices, a Benchtop-NIR and a Portable-NIR, were used and the nutrient values of mixed feeds were analyzed with these devices. It was determined that there were statistically significant differences between the reference method and NIR results for protein and starch content. Although the differences between the mean values were significant, the reference analyses results and NIR measurements were similar in some ways. According to the correlation coefficients calculated between the reference analyses with Benchtop-NIR and Portable-NIR devices, there was a weak correlation in the dry matter content, while a strong positive correlation existed in the protein (r = 0.72 for Portable, r = 0.93 for Benchtop NIR) and starch content. In the study, 30 different mixed feed (dairy cattle feed, beef cattle feed) values that are commonly used in ruminant feeding were measured.

NIR Instruments and Prediction Methods for Rapid Access to Grain Protein Content in Multiple Cereals

“…Additionally, the inclusion of five cereal species extended the range of protein content variability compared to the range found in any of the individual species. Also, both of the instruments tested in this study (FOSS-DS2500, with a spectral range of 400–2498 nm, and HL-EVT5, with a spectral range of 1350–2550 nm) encompassed the spectrum ranges relevant to protein determination in grain samples ( Section 3.2 ) [ 2 , 26 , 28 , 48 , 54 , 65 , 69 , 84 , 91 ], and sufficiently justified the next step, i.e., building the algorithms to infer the protein content from these two types of spectra ( Section 2.5 and 4.3).…”

“…Therefore, a multi-cereal species calibration could be a convenient alternative. Most of the reported multi-crop calibrations focus on forage and feed analysis [ 81 , 82 , 83 , 84 , 85 , 86 , 87 ]. Very few reports have documented robust calibration models for grain across multiple species using the classical statistical modelling methods.…”