Hyperspectral imaging in Penicillium spp. infection detection

Apple fruit production in recent years has greater demands on postharvest quality of apples. The main problem is detecting physical changes in the tissue texture or chemical changes of colour, smell and taste which can cause rejection by consumers. Quality mechanization and automatization of production in areas of harvest, quality control and selection of the fruits can ensure reduction of production cost and higher quality product. The main problem with visual identification of physical changes on apple fruit is that changes on fruit are not visible days after it gets infected or injured. One of many concerns for fruit growers are pathogens especially Penicillium expansum CBS 325.48 that can cause mycotoxin damages. They are widely spread biological toxins which contaminate fruit. There are many non-invasive techniques and methods that can successfully detect pathogens. Recent progress of the development in image technology came up with wide range of image analysis as great non-destructive technique for detecting quality of fruit. One of them is hyperspectral imaging that can be used for detection as an analytical tool to get spectral information from different objects such as detection of fruit properties and internal damages. Hyperspectral images were taken with a sensor working in the visible and near-infrared wavelength ranges from 400 to 1000 nm. Identifying the wavelengths at which damage of infection by P. expansum it can be detected early. The research was conducted under different temperatures on 5 traditional apple cultivars and 2 commercial apple cultivars. It is important to research early detection of damage and infections on fruit during postharvest, which can reduce costs and prevent quality issues during storage.