Alan M. Lefcourt

TL;DR: In this article, a recently developed hyperspectral imaging system with a range of 450 to 851 nm was used to examine reflectance images of experimentally contaminated apples and found that contamination could be identified using either three wavelengths in the green, red, and NIR regions, or using two wavelengths at the extremes of the NIR region under investigation.

TL;DR: A novel method that combines principal component analysis (PCA) and Fisher’s linear discriminant (FLD) method to show that the hybrid PCA-FLD method maximizes the representation and classification effects on the extracted new feature bands is presented.

TL;DR: It is suggested that use of multispectral fluorescence techniques for detection of fecal contamination on apples in a commercial setting may be feasible and delineation of an optimal detection scheme is beyond the scope of the current study.

TL;DR: In this paper, a dual-band ratio (Q725/811) algorithm was used to identify fecal contaminated apples in the 675-950 nm visible/NIR region.

TL;DR: In this paper, the authors used a fluorine detector to determine whether detection of fecal contamination on cantaloupes is possible using fluorine mine whether it is possible to detect the presence of coliform coliform in cantaloupe surfaces.