Non-Destructive Estimation of Firmness of Strawberries (Fragaria*ananassa Duch.) Using NIR Hyperspectral Imaging
Non-Destructive Estimation of Firmness of Strawberries (Fragaria*ananassa Duch.) Using NIR Hyperspectral Imaging
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DOI：
10.2525/ecb.44.245
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发表时间：
2006-12
影响因子：
--
通讯作者：
J. Tallada;M. Nagata;Kobayashi Taichi
中科院分区：
文献类型：
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作者：
J. Tallada;M. Nagata;Kobayashi Taichi
对水果内在品质进行无损在线分级，以实现更高的产品一致性和增强的安全性，将极大地惠及消费者和整个水果行业。本研究旨在建立草莓(Fragaria×ananassa Duch.)硬度预测模型。使用近红外高光谱成像。以三个成熟度水平的“明清”草莓为材料，拍摄了近红外高光谱图像(650~1000 nm，间隔5 nm)，并用逐步多元线性回归建立了校正模型。3个波长(685、865和985 nm)的硬度预测模型的预测相关性和标准误差分别为0.786和0.350 Mpa(对全熟组的预测为50%)。同时也证实了叶绿素吸收峰在680 nm附近和水峰在980 nm附近的重要性。
The non-destructive estimation of internal quality of fruits for on-line grading to achieve higher product consistency and enhanced safety will greatly benefit the consumer and the fruit industry as a whole. This research was aimed at developing prediction models for firmness in strawberries (Fragaria × ananassa Duch.) using NIR hyperspectral imaging. From freshly harvested strawberries of “Akihime” variety at three levels of ripeness maturity, NIR (near infrared) hyperspectral images (650 to 1000 nm at 5 nm intervals) were taken and calibration models were developed using stepwise multiple linear regression. The three-wavelength (685, 865, and 985 nm) prediction model for firmness had a correlation and standard error for prediction of 0.786 and 0.350 MPa, respectively (50% to full-ripe group) . The importance of chlorophyll absorbance peak at around 680 nm and peak of water at 980 nm was also confirmed.