Amylose content is an important determinant of rice quality. Its accurate, non-destructive assessment is a challenge to the industry. We examined whether the automatic quality inspection system accurately measured the amylose content. Brown and milled rice models were calibrated with 902 samples produced between 2008 and 2017 in Hokkaido, Japan, and validated individually by samples collected in 2018 (n = 33) and 2019 (n = 71) from several grain elevators within the region. Models were developed by processing the automatic system data comprising of a near-infrared spectrometer, a visible light grain segregator, combined analysis of chemometrics, and by merging low and ordinary amylose variety validation results. The lower standard error of prediction (<0.52%) and a higher ratio of performance deviation (>4.0) in both models enabled accurate non-destructive assessment of amylose content. Hence, the automatic quality inspection system is a useful tool for meeting the demands of higher quality and palatability of rice.
Keywords: Amylose content; Industrial setting; Near-infrared spectroscopy; Oryza sativa subsp. japonica; Rice quality.
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