Improved sampling and detection for proactive management of mycotoxins in grain.

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Addresses three mycotoxin-related problems associated with the grain corn industry; (1) Improve sampling accuracy: the inability to rapidly and reliably collect a representative grain sample from a truck load for mycotoxin testing. Currently this is being done by several random grain probes for each load at the grain receiving point; and there is no confidence in the sample for either sellers or buyers. We propose to develop and validate a simple, grain dust-aspirating protocol for grain corn applied during grain transfer to estimate total deoxynivalenol (DON) content of a grain lot; (2) Mycotoxin profiling: the concern that the ratio of DON measured in the by-products (DDGs) to DON measured in the grain, is not consistent and often higher than expected, or the sample is more bioactive than the sample test predicts. We propose to determine the profile and identify the major contributing forms of DON and their conjugates plus the newly discovered mycotoxin NXs in corn entering, and DDG leaving the ethanol process and develop a mass balance of these various mycotoxins throughout the process; (3) Rapid mycotoxin testing. Current rapid test kits are incapable of measuring all the various forms of DON and their masked conjugates in grain and DDGS, and therefore total DON is being underestimated. We propose to compare the main commercial lateral flow devices for estimating DON and related compounds in corn, corn dust and DDGs with the objective to better identify the bioactivity potential of contaminated sample to livestock. A user friendly water based extraction for testing DON in dust will also be developed and validated.