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Prediction of Soluble Solids Content of Chestnut using VIS/NIR Spectroscopy
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  • Prediction of Soluble Solids Content of Chestnut using VIS/NIR Spectroscopy
  • Prediction of Soluble Solids Content of Chestnut using VIS/NIR Spectroscopy
저자명
Park. Soo Hyun,Lim. Ki Taek,Lee. Hoyoung,Lee. Soo Hee,Noh. Sang Ha
간행물명
바이오시스템공학
권/호정보
2013년|38권 3호|pp.185-191 (7 pages)
발행정보
한국농업기계학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

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.