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Title: Detection of Wheat Kernels with Hidden Insect Infestations Using an Electrically Conductive Roller Mill

Author
item Pearson, Thomas
item Brabec, Daniel - Dan

Submitted to: Applied Engineering in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/1/2007
Publication Date: 10/1/2007
Citation: Pearson, T.C., Brabec, D.L. 2007. Detection of Wheat Kernels with Hidden Insect Infestations Using an Electrically Conductive Roller Mill. Applied Engineering in Agriculture. 23(5):639-645.

Interpretive Summary: Grain kernels infested by insects may show no indication on their exterior, but often contain hidden larvae. Although grain is always inspected for insect infestations upon shipping and receiving, many infested samples go undetected. Many methods for detecting infested wheat have been developed but none has seen widespread use due to expense or inadequate accuracy, or both. In this study, a laboratory roller mill system was modified to measure and analyze the electrical conductance of wheat as it was crushed. This facilitated detection of wheat kernels with live insects hidden inside of them. Furthermore, the apparatus is low cost (~1500 for parts) and can inspect a one kg sample in less than two minutes.

Technical Abstract: A laboratory roller mill system was modified to measure and analyze the electrical conductance of wheat as it was crushed. The electrical conductance of normal wheat kernels is normally low and fairly constant. In contrast, the electrical conductance of wheat kernels infested with live insects is substantially higher, depending on the size of the larvae and the resulting contact of the crushed larvae between the rolls. This instrument was designed to detect internal insect infestations in wheat that has a moisture content of 13.5% or less. The laboratory mill can test a kilogram (kg) of wheat in less than two minutes and 100g in less than 10 seconds. Hard red winter and soft red winter wheat containing larvae of rice weevils and lesser grain borers of a variety of sizes were tested. On average, the instrument detected 8.3 out of 10 infested kernels per 100g of wheat containing the larger sized insects (fourth instar or pupae). Kernels infested with medium sized larvae (second or third instar) were detected at an average rate of 7.4 out of 10 infested kernels per 100g of wheat. Finally, kernels infested with the small sized larvae (first or second instar) were detected at a rate of 5.9 out of 10 infested kernels per 100g of wheat. Under reasonable grain moisture contents there were no false positive errors, or un-infested kernels classified as insect infested. The cost of the mill is low and can lead to rapid and automated detection of infested wheat.