지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2011.1
- 수록면
- 369 - 376 (8page)
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초록· 키워드
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The overall goal of this study was to examine the feasibility of predicting firmness of pear fruit by analyzing laser-induced light backscattering images. Thirty-five image analysis characteristics extracted from the laser-induced light backscattering images were used to build partial least squares regression (PLSR) models for predicting firmness of pear fruit. Experiments were conducted with three sets of pear samples which were in same "Shingo" cultivar, harvested in a same season, but produced in different counties. In every experiments with fruit samples produced in a same county, the correlation coefficients of prediction ($r_p$) and root mean square errors of prediction (RMSEP) of the models were 0.550~0.761 and 4.039~6.154 N, respectively. In an experiment with mixed fruit samples produced in different counties, the $r_p$ and RMSEP of the model were 0.669 and 5.02 N, respectively. The experiment results indicate that the analysis of laser-induced light backscattering images could be a useful tool for predicting firmness of pear fruit nondestructively.
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