Sensing the Invisible: A Critical Review of NIR and Hyperspectral Analysis for Crop and Food-Quality Assessment

This review critically appraises the methodological foundations of near-infrared (NIR) spectroscopy and hyperspectral imaging (HSI) for crop and food-quality analysis. Eighteen original figures accompany the text, tracing the field from its historical and physical foundations through chemometric modelling, in-situ and on-machine sensing, UAV-based crop-quality sensing and image-processing frameworks, and a FAIR data-principles framework for spectral datasets. Each strand of literature examined here, the historical and physical basis of NIR/HSI, chemometric calibration and transfer, and in-situ applications such as on-harvester grain sensors and variable-rate nitrogen sensing, is checked directly against independently published, peer-reviewed sources rather than taken at face value. The underlying sensing and chemometric techniques are found to be technically sound and well established, but a recurring weakness emerges in how they are communicated: worked examples, named commercial products, and preliminary or in-preparation findings are frequently presented with the same degree of confidence as validated, independently reproduced results, without distinguishing one evidentiary tier from another. Building on this pattern, the review develops a cross-cutting synthesis showing that the calibration-generalisation caution recurring across laboratory, in-situ and UAV-based deployments of NIR/HSI is, in substance, a single methodological concern: a calibration model is only ever as trustworthy as the independent validation standing behind it, regardless of the confidence with which it is presented. This synthesis is made quantitative in a dedicated cross-cutting section that audits the evidentiary tier of every independently selected source, consolidates the field's validation-statistics equations, and maps the recurring gap across all sections of the review.

NIR spectroscopy; hyperspectral imaging; chemometrics; food and crop quality; calibration transfer

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