Whole grain amylose analysis in maize using near-infrared transmittance spectroscopy

The development of genetically modified starches has relied on the use of maize (Zea mays L.) endosperm mutant alleles that alter starch structural and physical properties. A rapid method for predicting amylose content would benefit breeders and commercial handlers of specialty starch corn. For this reason, a study was conducted to investigate the use of near-infrared transmittance spectroscopy (NITS) as a rapid and nondestructive technique for predicting grain amylose content (GAC) in maize. Many single- and double-mutant inbreds and hybrids were used to create a calibration set for the development of a predictive model using partial least squares analysis. A validation set composed of similar genetic material was used to test the prediction model. A coefficient of correlation (r) of 0.94 was observed between GAC values determined colorimetrically and those predicted by NITS; however, the predicted values were associated with a large standard error of prediction (SEP = 3.5). Overall, NITS discriminated well among high amylose and waxy genotypes. The NITS calibration was used to determine levels of contamination by normal kernels in waxy and high-amylose (Amy VII) grain samples intended for wet milling. In both cases, a 5% contaminated sample could be detected from pure samples according to predicted NITS values.