LAUSR

Major qualitative changes during storage of wheat are attributed to infestation by weevils, beetles, and moths. Alteration in inherent macro and micro nutrients and corresponding reduction in grain mass is the ultimate indicator of the deteriorations. Sitophilus oryzae and Ryzopertha dominica are two commonly found insects in stored wheat, which cause the major losses by feeding upon the grain mass and contaminating the grain bulk with their metabolic waste. The current study focused on development of a rapid and non-destructive FT-NIR spectroscopic method for the determination of insect infestation by analyzing the quality changes in grain due to infestation. A total of 128 wheat samples of varying moisture content, insect count, and storage days were analyzed for quality parameters. FT-NIR library was generated and the spectral data were analyzed using partial least squares regression (PLS) with various preprocessing techniques. The best models for properties with lowest root mean square error of cross-validation values for moisture, protein, uric acid, 1000 kernel weight, and hardness were 0.485, 0.248, 2.58, 0.576, and 0.762, respectively. R2 obtained for the abovesaid quality parameters were 0.901, 0.938, 0.895, 0.907, and 0.912 demonstrating good fit of the PLS models. The developed methods will be very much useful for storage godowns, bakery industries, graders, and exporters providing rapid, reliable, and precise quality estimation during reception of the raw material without involvement of hazardous chemicals.