Submitted to: Meeting Abstract
Publication Type: Abstract only
Publication Acceptance Date: 7/30/2008
Publication Date: 7/30/2008
Citation: Wicklow, D.T. 2008. NIR spectroscopy as a tool for optimizing sorting of white maize kernels contaminated with mycotoxins.. Meeting Abstract. Interpretive Summary:
Technical Abstract: Maize kernels highly contaminated by aflatoxin and fumonisin are unevenly distributed in a grain lot and may be concentrated in a very small percentage of the product. Near-infrared (NIR) reflectance spectra (500-1,700 nm) were analyzed to select the pair of absorbance bands (filters) giving the lowest classification error rate for removing whole white maize kernels contaminated with aflatoxin or fumonisin in a single pass through a commercial high speed sorter (@7,000 kg/hr). It was found that using the wavelength pair of 500nm and 1200nm, approximately 87% and 93% of kernels having high levels of aflatoxin (>100ppb) and high levels of fumonisin (>40ppm), respectively, were correctly classified. Additionally, approximately 96% of the kernels having low levels of aflatoxin (<10ppb) and fumonisn (<2 ppm) were correctly classified as uncontaminated. Kernels having minor symptoms (25% to 50% discolorations) had lower classification accuracies (80%), than those with discolorations covering more than 75% of the kernel (88%), or discolored BGYF kernels (91%). A commercial sorting machine (Satake DE) was set up to sort corn using light at 500 and 1200nm and reject 4% to 9% of the incoming corn in three lots ranging from 23 to 150 ppb aflatoxin and 0.4 to 0.6 ppm fumonisin. Because some kernels with minor symptoms of discoloration had very high contamination levels of aflatoxin, two passes through the sorter were required to reduce aflatoxin below the regulatory limit of 20 ppb. In earlier sorting experiments with commercially harvested yellow corn contaminated with equivalent levels of aflatoxin (average 75 ppb), we were able to reduce aflatoxin below 20 ppb with a single pass through the same Satake DE machine. Differences in pericarp thickness, kernel vitreosity and the presence or absence of carotenoids, could influence both kernel symptom expression and the ability of NIR light to detect fungal damaged endosperm.