Hyperspectral imaging based kinetic approach to assess quality deterioration in fresh mushrooms (Agaricus bisporus) during postharvest storage

Hyperspectral imaging (HSI) is a non-destructive analytical tool that can be used for sensing multiple quality attributes for fresh commodities, but is usually constrained by complex data processing. Here, we report the development of HSI based simple kinetic models to assess quality deterioration in A. bisporus mushrooms. The commercially available fresh mushroom packages kept at constant refrigeration temperature (4 °C) were selected for HSI analysis in the visible and near infrared (VNIR) wavelengths (400–1000 nm) for a postharvest storage of 11 d. The observed HSI reflectance patterns clearly showed two sensitive wavelength regions: i) 450–700 nm and ii) 800–900 nm, which were termed as HSI index-I and HSI index-II, respectively. Alongside this, physicochemical and microbiological characterization of mushrooms were carried out and were related to HSI quality indices. The kinetic analysis showed that the HSI index-I is a useful quality indicator for the assessment of storage time for A. bisporus mushrooms. Furthermore, the physical quality attributes such as color and texture, which were changed significantly (p < 0.05) during the storage were linked to HSI index-I through linear regression models. The data processing approach presented in this study is quite useful that will facilitate the application of HSI in quality assessments of fresh commodities.