Analysis and Estimate of Corn Quality by Near Infrared Reflectance (NIR) Spectroscopy

The objective of this study was to investigate the feasibility of predicting the composition of corn by near infrared reflectance spectroscopy. The partial least square (PLS) regression method, second derivative and Norris derivative filter were applied in the NIRS prediction of composition of corn. For Dry matter, crude protein, ash, fat, starch, neutral-detergent fiber and acid-detergent fiber, the determination coefficients were 0.9743, 0.9683, 0.9478, 0.9098, 0.9777, 0.9354 and 0.9269, and the SD/RMSEP values for them were 3.96, 4.78, 3.75, 4.25, 4.13, 3.88 and 3.12, respectively. The determination coefficient and SD/RMSEP value were 0.8575 and 3.06 for soluble protein, but low determination coefficients of 0.5319 and 0.6833 with SD/RMSEP values of 5.50 and 2.85 were observed for acid-detergent insoluble protein and neutral-detergent insoluble protein. The results of this study indicated that corn nutritive values could be fast and accurately predicted by NIRS.