<title>Detection of contamination on selected apple cultivars using reflectance hyperspectral and multispectral analysis</title>

Abstract

Contamination of apples is a food safety concern touching the general public and strongly affecting this commodity market. Accumulations of human pathogens are usually observed on surface lesions of commodities. Detection of lesions and pathogens is essential for assuring the quality and safety of commodities. We are presenting the application of hyperspectral image analysis towards the development of multispectral techniques for the detection of defects on three apple cultivars, Golden Delicious, Red Delicious, and Gala. Separate apple cultivars possess different spectral characteristics leading to different approaches for analysis. General preprocessing analysis with morphological treatments is followed by different image treatments and condition analysis for highlighting lesions and contaminations. Good isolation of scabs, fungal and soil contaminations, and bruises is observed with hyperspectral imaging processing either using principal component analysis or utilizing the chlorophyll absorption peak. Applications of hyperspectral results to a multispectral detection are limited by the spectral capabilities of our RGB camera using either specific band pass filters. Good separation of defects is obtained for Gala (95%) and Golden Delicious (85%) apples. However, separations are limited for Red Delicious (76%). Having an extra near infrared channel will increase the detection level utilizing the chlorophyll absorption band for detection as demonstrated by the present hyperspectral imaging analysis.