The challenge for insect detection is finding two infested kernels among the 25,000 kernels in a 500 gram rice sample (Throne and Pearson 2008). As many as 98% of internal feeding Rhyzopertha dominica may be missed when sieving to separate insects from the grain (Perez-Mendoza et al. 2005). Holding samples until adults emerge exposes internal feeding insects, or holding immatures until they become adults make species identification easier but this delays pest management decision.
Once a representative sample of commodity has been taken, a method of determining the number of insects in the samples is needed. Table 2.2 in Fundamentals of Stored Product Entomology gives 9 destructive and 15 non-destructive methods for extraction and detection insects. Throne and Pearson (2008) discuss some more recent insect detection methods including acoustic impact for insect damaged kernels (IDK) only, single kernel characterization system, digital x-ray and tomography and the cost of these as well as older methods. They also characterize the ideal detection method as quick (processing large sample in minute or two), automated, 80-100% accurate for all stages and species of insects (dead and live), rare false positives (classifying uninfested sample as infested) and cost effective. None of methods meet all criteria for an ideal detection method and only x-ray meets accuracy criteria. None of the rapid, automated methods can detect dead and live insects accurately, although, combining the single kernel characterization technologies (resistance and video imaging) may be useful. Processing time may be less important with long-term storage where follow-up is possible for questionable samples.
We provide many citations for more recent studies on insect detection. There were as many studies on acoustic detection between 2011 and 2021 as during the previous 100 years (Mankin et al. 2021).
References
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Mankin, Richard, David Hagstrum, Min Guo, Panagiotis Eliopoulos, and Anastasia Njoroge. 2021. Automated Applications of Acoustics for Stored Product Insect Detection, Monitoring, and Management. Insects 12(3), 259.
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