mlsanityData to 14 Oct 2026

A Guide to Employ Hyperspectral Imaging for Assessing Wheat Quality at Different Stages of Supply Chain in Australia: A Review

arXiv 2209.05727 ↗First posted 13 Sep 2022cs.CV cs.AIcited by 1

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Abstract (arXiv)

Wheat is one of the major staple crops across the globe. Therefore, it is mandatory to measure, maintain and improve the wheat quality for human consumption. Traditional wheat quality measurement methods are mostly invasive, destructive and limited to small samples of wheat. In a typical supply chain of wheat, there are many receival points where bulk wheat arrives, gets stored and forwarded as per the requirements. In this receival points, the application of traditional quality measurement methods is difficult and often very expensive. Therefore, there is a need for non-invasive, non-destructive real-time methods for wheat quality assessments. One such method that fulfils the above-mentioned criteria is hyperspectral imaging (HSI) for food quality measurement and it can also be applied to bulk samples. In this paper, we have investigated how HSI has been used in the literature for assessing stored wheat quality. So that the required information to implement real-time digital quality assessment methods at the different stages of Australian supply chain can be made available in a single and compact document.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 1 of its 112 references that are in the map. First posted on arXiv 13 Sep 2022.

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1 of 112 references.

References · 1

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096

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