The potential of different spectroscopic techniques for evaluating potato (Solanum tuberosum L.) quality was investigated. Spectral data in the wavelength range of 400-1750 nm were used to develop quality prediction models. The Partial Least Squares (PLS) regression was used for predicting the water content in potato samples. Water content was predicted with R2 ≥ 0.938. / A further study was conducted to find the best wavelengths for predicting water content using two methods, PLS and multiple linear regression. Wavelength ranges of 910-1020, 1129-1211, 1363-1403 nm were selected for samples without skin, while 700-900, 930-1050, 1100-1300, 1400-1550 nm were selected for samples with-skin. Weight prediction models were established using the predicted water content. / Visible spectroscopy was used for classifying shriveled and non-shriveled potatoes. The wavelength ranges best suited to such a classification were those of 442-452, 456-466, 641-651, and 684-694 nm, with accuracies as high as 94.28% and as low as 80%.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.84074 |
| Date | January 2005 |
| Creators | Singh, Baljinder |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Master of Science (Department of Bioresource Engineering.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 002272386, proquestno: AAIMR22766, Theses scanned by UMI/ProQuest. |
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