Abstract
Imaging spectroscopy has emerged as a reliable analytical method for effectively characterizing and quantifying quality attributes of agricultural products. By providing spectral information relevant to food quality properties, imaging spectroscopy has been demonstrated to be a potential method for rapid and non-destructive classification, authentication, and prediction of quality parameters of various categories of tubers, including potato and sweet potato. The imaging technique has demonstrated great capacities for gaining rapid information about tuber physical properties (such as texture, water binding capacity, and specific gravity), chemical components (such as protein, starch, and total anthocyanin), varietal authentication, and defect aspects. This paper emphasizes how recent developments in spectral imaging with machine learning have enhanced overall capabilities to evaluate tubers. The machine learning algorithms coupled with feature variable identification approaches have obtained acceptable results. This review briefly introduces imaging spectroscopy and machine learning, then provides examples and discussions of these techniques in tuber quality determinations, and presents the challenges and future prospects of the technology. This review will be of great significance to the study of tubers using spectral imaging technology.
Highlights
As plant foods grown worldwide, both potato and sweet potato tubers belong to the family of solanales
The results showed that the supervised multiple threshold segmentation model (SMTSM) coupled with Canny edge detector was effective in detection of potato germination with a high accuracy (89.85%), which demonstrated that the precision of the proposed methods
Based on the chemical-free evaluation approaches, the sample preparation time has been greatly reduced and the errors emerging during subjective judgement decreased
Summary
As plant foods grown worldwide, both potato and sweet potato tubers belong to the family of solanales. Soybean, and dairy products [3,4,5], potatoes and sweet potatoes are important sources of carbohydrates and are rich in protein, calcium, and vitamin C. They can be used as staple foods, animal feeds, and for other purposes [6,7,8]. Imaging spectroscopy can obtain the continuous spectral response of each point of an image in the visible (Vis) and near/mid infrared (NIR/MIR) ranges [24,30,31] This technology can provide detailed characteristic parameters for non-destructive quality evaluation of foods [32,33,34]. This article will analyze the application of the technology in intelligent determination of potato and sweet potato tubers
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