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Detection of Scab-Damaged Hard Red Spring Wheat Kernels by Near-Infrared Reflectance

¹USDA/ARS, Beltsville Agricultural Research Center, Instrumentation and Sensing Laboratory, Building 303, BARC-East, Beltsville, MD 20705-2350. Names are necessary to report factually on available data; however, the USDA neither guarantees nor warrants the standard of the product, and the use of the name by the USDA implies no approval of the product to the exclusion of others that may also be suitable. ²Corresponding author. E-mail: delwiche@ba.ars.usda.gov ³USDA/ARS, Hard Red Spring and Durum Wheat Quality Laboratory, Fargo, ND.

Scab (Fusarium head blight) is a fungal disease that has become increasingly prevalent in North American wheat during the past 15 years. It is of concern to growers, processors, and the consumers because of depressed yields, poor flour quality, and the potential for elevated concentrations of the mycotoxin, deoxynivalenol (DON). Both wheat breeder and wheat inspector must currently deal with the assessment of scab in harvested wheat by manual human inspection. The study described herein examined the accuracy of a semi-automated wheat scab inspection system that is based on near-infrared (NIR) reflectance (1,000–1,700 nm) of individual kernels. Using statistical classification techniques such as linear discriminant analysis and nonparametric (k-nearest-neighbor) classification, upper limits of accuracy for NIR-based classification schemes of ≈88% (cross-validation) and 97% (test) were determined. An exhaustive search of the most suitable wavelength pairs for the spectral difference, [log(1/R)_λ1 - log(1/R)_λ2], revealed that the slope of the low-wavelength side of a broad carbohydrate absorption band (centered at ≈1,200 nm) was very effective at discriminating between healthy and scab-damaged kernels with test set accuracies of 95%. The achieved accuracy levels demonstrate the potential for the use of NIR spectroscopy in commercial sorting and inspection operations for wheat scab.