Informative selection of spectra obtained from an online sugar content prediction system of sugarcane by using statistical index

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Kittisak Phetpan
Vasu Udompetaikul
Panmanas Sirisomboon


The aim of this research is to optimize the spectral filtration in an online soluble solids content measuring system of sugarcane. Assessment of the application of principal component analysis (PCA) and cluster analysis for filtering out non-sugarcane (floor and slat) spectra was first performed. Besides, the presentation and evaluation of the statistical index in keeping up the sugarcane detection were then performed. Screening out non-sugarcane spectra using both the PCA and cluster analysis was still not perfect because they could handle with the floor responses only not a slat one. For the proposed statistical index, the index value of -0.6 was used as an effective threshold to distinguish between sugarcane and non-sugarcane detections. As the result, only sugarcane responses were kept up. Importantly, no kidnapping the spectral sets after the filtration by using this index.


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Post-harvest and food engineering


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