Influence of forage particle size and residual moisture on near infrared reflectance spectroscopy (NIRS) calibration accuracy for macro-mineral determination

Abstract

Near infrared reflectance spectroscopy (NIRS) is routinely used for the determination of nutrient components of forages. However, little is known about the impact of sample preparation on the accuracy of the calibration to predict minerals. Three types of forages, hay (n = 117), grass (n = 109) and haylage (n = 119) were used to determine the impact of different sample preparation procedures: particle size (1.0 mm and 0.5 mm) and presence or absence of residual moisture (dried and re-dried) on resultant NIRS prediction statistics. All forages were scanned using a total of four combinations of sample pre-treatments (1 mm dried, 1 mm re-dried, 0.5 mm dried and 0.5 mm re-dried). Each sample preparation combination was subjected to spectra pre-processing methods such as standard normal variate (SNV), detrending (DT), combination of SNV and DT (SNV&DT) and None (log1/R) together with mathematical treatments (1,4,4,1; 2,4,4,1; 2,6,4,1; 3,5,5,1 and 2,4,4,2). Reduction of particle size from 1 mm to 0.5 mm slightly improved calibration statistics for the prediction of macro-minerals in hay and haylage samples. However, for the grass samples, improved calibration statistics was observed at a particle size of 1 mm for most of the minerals studied. Furthermore, the removal of residual moisture through additional oven drying improved calibration statistics for all minerals examined in the hay, haylage and grass samples. These results highlight the importance of the reduction in particle sizes for the improvement of calibration statistics for the determination of macro-minerals. In addition, re-drying of samples will improve calibration statistics for macro-minerals at particle sizes of 1 mm and/or 0.5 mm.