Analysis for soluble solid contents in pineapples using NIR spectroscopy
This research investigates the use of predictive models and a low cost spectroscopy in non-invasive Soluble Solids Content (SSC) assessment. The challenge is to model complex and high-dimensional spectral data. Results indicate that the SSC prediction of pineapples harvested on different days using...
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Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Penerbit UTM
2014
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Online Access: | http://eprints.utm.my/id/eprint/51824/1/HerlinaAbdulRahim2014_Analysisforsolublesolidcontents.pdf http://eprints.utm.my/id/eprint/51824/ http://dx.doi.org/10.11113/jt.v69.3288 |
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Summary: | This research investigates the use of predictive models and a low cost spectroscopy in non-invasive Soluble Solids Content (SSC) assessment. The challenge is to model complex and high-dimensional spectral data. Results indicate that the SSC prediction of pineapples harvested on different days using the proposed approach is promising. The second study evaluates common pre-processing practices. Findings indicate that the best accuracy would be achieved when visible spectrum was excluded, second order Savitzky-Golay derivative with the optimal filter length was used, and the absorbance transformation was avoided |
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