Advancements in Non-Destructive Detection of Biochemical Traits in Plants Through Spectral Imaging-Based Algorithms: A Systematic Review

This paper provides a comprehensive overview of the state of the art non-destructive methods for detecting plant biochemical traits through spectral imaging of leafy greens. It offers insights into the various detection techniques and their effectiveness. The review emphasizes the algorithms used for spectral data analysis, highlighting advancements in computational methods that have contributed to improving detection accuracy and efficiency. This systematic review, following the PRISMA 2020 guidelines, explores the applications of non-destructive measurements, techniques, and algorithms, including hyperspectral imaging and spectrometry for detecting a wide range of chemical compounds and elements in lettuce, basil, and spinach. This review focuses on studies published from 2019 onward, focusing on the detection of compounds such as chlorophyll, carotenoids, nitrogen, nitrate, and anthocyanin. Additional compounds such as phosphorus, vitamin C, magnesium, glucose, sugar, water content, calcium, soluble solid content, sulfur, and pH are also mentioned, although they were not the primary focus of this study. The techniques used are showcased and highlighted for each compound, and the accuracies achieved are presented to demonstrate effective detection.