| Abstract: | Insect infestations in stored wheat affect the chemical characteristics and baking qualities of wheat flour, and insect‐infested flours are unacceptable in the baking industry. The efficiency of the soft X‐ray method to detect infestations caused by Cryptolestes ferrugineus (Stephens), Tribolium castaneum (Herbst), Plodia interpunctella (Hübner), Sitophilus oryzae (L.), and Rhyzopertha dominica (F.) in wheat kernels was determined in this study. Wheat kernels infested by different insects were prepared by artificial implantation of insect eggs or by introducing adult insects in wheat samples. Kernels infested by different stages of the insects were X‐rayed until the adults emerged from the kernels. A total of 57 features using histogram groups, histogram and shape moments, and textural features were extracted from the X‐ray images and a linear‐function parametric classifier was used to identify the insect‐infested kernels. The parametric classifier identified more than 84% of infestations due to C. ferrugineus and T. castaneum larvae. The infestations by C. ferrugineus pupae‐adults and P. interpunctella larvae were identified with >96% accuracy. Kernels infested by different stages of S. oryzae and R. dominica larvae were identified with >98% accuracy. Using the Berlese funnel method, 67, 51, and 81% of first, second, and third instars of C. ferrugineus, respectively, were extracted in 6 hr. The same infested kernels were all categorized as infested by the parametric classifier. When kernels infested by different insects were pooled together, the parametric classifier correctly identified 74% of uninfested and 94% of infested kernels by the internal and external grain feeders. The 26% false positives identified from the independent test was caused by one sample infested by T. castaneum. When that sample was removed from the training set, the false positives were reduced to 16%, and 92.7% of infested kernels by different insects were correctly identified. |
