Document Type

Article

Rights

This item is available under a Creative Commons License for non-commercial use only

Disciplines

1.6 BIOLOGICAL SCIENCES, 2. ENGINEERING AND TECHNOLOGY

Publication Details

Gaston E, Frias JM, Cullen PJ, O'Donnell CP, Gowen AA. (2010) Visible-near infrared hyperspectral imaging for the identification and discrimination of brown blotch disease on mushroom (Agaricus bisporus) caps. Journal of Near Infrared Spectroscopy Volume 18 Issue 5, Pages 341–353 (2010)

Abstract

Brown blotch, caused by pathogenic Pseudomonas tolaasii (P. tolaasii), is the most problematic bacterial disease in Agaricus bisporus mushrooms. Although it does not cause any health problems, it reduces the consumer appeal of mushrooms in the market place, generating important economical losses worldwide. Hyperspectral imaging (HSI) is a non-destructive technique that combines imaging and spectroscopy to obtain information from a sample. The objective of this study was to investigate the use of HSI for brown blotch identification and discrimination from mechanical damage on mushrooms. Hyperspectral images of mushrooms subjected to i) no treatment, ii) mechanical damage or iii) microbiological spoilage were taken during storage and spectra representing each of the classes were selected. Partial least squares- discriminant analysis (PLS-DA) was carried out in two steps: i) discrimination between undamaged and damaged mushrooms and ii) discrimination between damage sources (i.e. mechanical or microbiological). The models were applied at a pixel level and a decision tree was used to classify mushrooms into one of the aforementioned classes. A correct classification of >95% was achieved. Results from this study could be used for the development of a sensor to detect and classify mushroom damage of mechanical and microbial origin, which would facilitate the industry to make rapid and automated decisions to discard produce of poor marketability.