Environmental assessment of soluble solids contents and pH of orange using hyperspectral method and machine learning

Abstract

Progress in non-destructive methods to detect the characteristics of fruits is a new and attractive process for researchers and specialists in this field. On the other hand, these researchers move toward identifying their impacts on their surroundings in line with diagnostic efficiency. One of these essential impacts is the environmental impact of the non-destructive detection process of fruits. Navel oranges are one of the most popular and widely consumed fruits, whose maturity indices such as soluble solids contents (SSC) values and acidity are considered as parameters in determining the quality of this product. This study used the hyperspectral method in the vis-NIR range to evaluate and measure navel oranges' SSC and acidity values. In the following, by applying the life cycle assessment method, the environmental impacts of measuring and evaluating these two parameters of the characteristics of navel oranges were investigated. The Impact2002+ method was used to evaluate the impact of the life cycle list. Based on the findings, the environmental impacts of SSC measurement are about 40, 42, 20, and 18 % higher than those of the environmental impacts of pH measurement from the point of view of endpoint impacts for Human Health, Ecosystem quality, climate change, and resources, respectively. The random forest modeling results showed a suitable and acceptable correlation and relationship (over 90 %) between the wavelengths selected from the feature selection stage and environmental impacts.