Automated Detection of Single Wheat Kernels Containing Live or Dead Insects Using Nearinfrared Reflectance Spectroscopy

An automated nearinfrared (NIR) reflectance system was used over a twomonth storage period to detect singlewheat kernels that contained live or dead internal rice weevils at various stages of growth. Correct classification of soundkernels plus kernels containing live pupae, large larvae, mediumsized larvae, and small larvae averaged 94%, 93%, 84%,and 63%, respectively. Pupae + large larvae calibrations were developed for live (day 1) and dead (days 7, 14, 28, 42, and56) internal insects. Validation results showed that the live pupae +live large larvae calibration correctly classified 86% to96% of dead pupae + dead large larvae validation samples. The dead pupae + dead large larvae calibration correctly detectedthe presence of live pupae + live large larvae with an accuracy of 92% to 93%. Thus, wheat kernels containing either liveor dead insects can be used to develop calibrations for detecting both live and dead insects in wheat. These findings willimpact how calibration sample sets can be handled. Results indicated that immediate sample processing for creatingcalibrations may no longer be necessary; internal insects can be killed and calibrations created at a later time withoutsacrificing accuracy. Additionally, laboratories can share these same calibration samples to save time and resources.