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http://dx.doi.org/10.5307/JBE.2013.38.3.185

Prediction of Soluble Solids Content of Chestnut using VIS/NIR Spectroscopy  

Park, Soo Hyun (Department of Biosystems and Biomaterials Science and Engineering, Seoul National University)
Lim, Ki Taek (Department of Biosystems and Biomaterials Science and Engineering, Seoul National University)
Lee, Hoyoung (Environmental Microbiology and Food Safety Laboratory, Animal and Natural Resources Institute, Agricultural Research Service, U.S. Department of Agriculture)
Lee, Soo Hee (Life & Technology CO. LTD.)
Noh, Sang Ha (Department of Biosystems and Biomaterials Science and Engineering, Seoul National University)
Publication Information
Journal of Biosystems Engineering / v.38, no.3, 2013 , pp. 185-191 More about this Journal
Abstract
Purpose: The present study focused on the estimation of soluble solids content (SSC) of chestnut using reflectance and transmittance spectra in range of VIS/NIR. Methods: Four species intact/peeled chestnuts were used for acquisition of spectral data. Transmittance and reflectance spectra were used to develop the best PLS model to estimate SSC of chestnut. Results: The model developed with the transmitted energy spectra of peeled chestnuts rather than intact chestnuts and with range of NIR rather than VIS performed better. The best $R^2$ and RMSEP of cross validation were represented as 0.54 and $1.85^{\circ}Brix$. The results presented that the reflectance spectra of peeled chestnuts by species showed the best performance to predict SSC of chestnut. $R^2$ and RMSEP were 0.55 and $1.67^{\circ}Brix$. Conclusions: All developed models showed RMSEP around $1.44{\sim}2.54^{\circ}Brix$, which is considered not enough to estimate SSC accurately. It was noted that $R^2$ of cross validation that we found were not high. For all that, grading of the fruits in two or three classes of SSC during postharvest handling seems possible with an inexpensive spectrophotometer. Furthermore, the development of estimation of SSC by each chestnut species could be considered in that SSC distribution is clustering in different range by species.
Keywords
Cross validation; Chestnut; NIR spectroscopy; PLS; Prediction of SSC;
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