Determination of Protein and Starch Content in Whole Maize Kernel by Near Infrared Reflectance Spectroscopy

摘要

Using 128 bulk-kernel samples of inbred lines and hybrids, a study was conducted to investigate the feasibility and method of measuring protein and starch contents in intact seeds of maize by near infrared reflectance spectroscopy (NIRS). The chemometric algorithms of partial least square (PLS) regression was used. The results indicated that the calibration models developed by the spectral data pretreatment of first derivative + multivariate scattering correction within the spectral region of 10 000-4 000 cm~(-1), and first derivative + straight line subtraction in 9 000 - 4 000 cm~(-1) were the best for protein and starch, respectively. All these models yielded coefficients of determination of calibration (R_(cal)~2) above 0.97, while R_(cv)~2 and R_(val)~2 of cross and external validation ranged from 0.92 to 0.95, respectively; however, the root of mean square errors of calibration, cross and external validation (RMSEE, RMSECV and RMSEP) were below 1 (ranged 0.3 - 0.7), respectively. This study demonstrated that it is feasible to use NIRS as a rapid, accurate, and none-destructive technique to predict protein and starch contents of whole kernel in the maize quality improvement program.