Hyperspectral and multispectral imaging for evaluating food safety and quality

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Non-Destructive Prediction of Moisture Content and Freezable Water Content of Purple-Fleshed Sweet Potato Slices during Drying Process Using Hyperspectral Imaging Technique (2017, methodology): “rapidly, non-destructively, and efficiently (Qin et al. 2013).”
Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review (2021, background): “However, it has some disadvantages owing to which LED lights are gaining prominence now-a-days (Qin et al., 2013).”
Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and Forestry (2017, background): “In fact, both multi- and hyperspectral imagery have the potential to take data mining to a whole new exploration level in many areas, including food quality assessment [11] and agriculture [12].”
Recent Developments in Hyperspectral Imaging for Assessment of Food Quality and Safety (2014, methodology): “For quantitative analysis prediction, multivariate analytical tools such as PCA, PLSR, stepwise multi-linear regression (SMLR), are usually employed for chemical content prediction [27,63].”