Detection of Callosobruchus maculatus (F.) infestation in soybean using soft X-ray and NIR hyperspectral imaging techniques

Soybean (Glycine max L.) is a major oilseed crop grown throughout the world and, total post-harvest losses of soybean are approximately 10%, and 3% of produced soybean is lost during storage. Cowpea weevil (Callosobruchus maculatus (F.)) is the major storage pest which causes extensive storage losses of legumes. Detection of early stages of cowpea weevil infestation could assist farmers and storage facility managers in implementing suitable control practices for insect disinfestations. Soft X-ray and near-infrared (NIR) hyperspectral imaging techniques were used to acquire images of soybeans infested by egg, larval, and pupal stages of C. maculatus along with uninfested and completely damaged (hollowed-out after emergence of adults) soybeans. From soft X-ray images, totally, 33 features (12 histogram and 21 textural features) were extracted and from hyperspectral data 48 features were extracted (30 histogram and 18 spectral features) for analysis. Linear and quadratic discriminant analysis (LDA and QDA) models were developed using these extracted features to classify different stages of infestation. The LDA classifier for soft X-ray images correctly identified more than 86% of uninfested soybeans and 83% of soybeans infested with all developmental stages of C. maculatus except the egg stage. Pair-wise LDA classification models developed from NIR hyperspectral data yielded more than 86 and 87% classification accuracy for uninfested and infested seeds, respectively. The QDA pair-wise classifiers positively differentiated more than 79% uninfested seeds from infested seeds. The principal component analysis of NIR hyperspectral data identified the wavelengths of 960 nm, 1030 nm and 1440 nm being responsible for more than 99% of spectral variability. Combining soft X-ray features with hyperspectral features increased the classification accuracies for egg and larvae compared to either imaging system used alone. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.