Near infrared reflectance spectroscopy analysis (NIRA) to predict quality parameters in whole-plant corn forage was investigated. Quality parameters studied included acid detergent fiber (ADF), in vitro dry matter digestibility (IVDMD) and crude protein (CP). Samples of whole-plant corn forage were collected during three growing years (1984, 1985, 1986) across six geographical locations in Ontario, Canada and were harvested at an average 35% dry matter content. Samples were randomly divided into two sets: a calibration (CAL) set to develop NIRA equations and a testing (TEST) set to validate these equations. NIRA calibrations for ADF, IVDMD and CP percent were performed for each growing season across locations. A multi-year calibration was also developed with samples drawn from the three growing years. The accuracy of the NIRA predictions was assessed by the standard error of the estimate (SEE), bias or the mean difference between laboratory and NIRA data, the coefficient of determination (r2) and the slope (b) of the regressions between laboratory and NIRA data. The single year calibrations showed good predictions for all quality parameters in samples drawn within the year. The SEE values in the TEST sets for single year calibrations varied from 1.6 to 1.9% for ADF, 1.5 to 2.3% for IVDMD and 0.3 to 0.5% for CP, respectively. However, recalibration was necessary every year because calibrations based on a single year failed to account for variances introduced by samples drawn from other years. The multi-year calibration predicted ADF, IVDMD and CP percent accurately regardless of year. The SEE and bias for ADF, IVDMD and CP percent for the TEST set were 1.6 and 0.1, 2.2 and 0.3, and 0.5 and 0.1, respectively. The success of the multi-year calibration encourage the possibility to develop a standard calibration for whole-plant corn.Key words: Near infrared reflectance analysis, calibrations, whole-plant corn forage, year, multi-year quality parameters
The Application of Near Infrared Reflectance Spectroscopy as A Fast and Non-Destructive Method to Determine Inner Quality Parameters of Intact Mango