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Non-destructive measurement of tomato quality using visible and near-infrared reflectance spectroscopy.

机译:使用可见光和近红外反射光谱仪对番茄质量进行无损检测。

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摘要

Experiments were conducted to assess the feasibility of determining the quality attributes of tomato (Lycopersicon esculentum Mill cv 'DRK 453' and 'Trust') based upon visible/near-infrared reflectance (VIS/NIR) spectroscopy. A partial least squares regression (PLS) method was used to build prediction models.;Further, a model built by the PLS2 method showed good performance in simultaneously predicting a*/b* ratio, TCI, firmness, and LC of tomato, with R2 values of 099, 0.99, 0.97, and 0.92, and RMSEP of 0.06, 1.75, 1.44, and 3.03, respectively. Once again here all the R2 values were significant at 1% level.;Excellent prediction performance was achieved for lycopene content (LC), colour value a*/b* ratio, tomato colour index (TCI), and firmness. Coefficient of determination (R2) for each of the parameters was respectively 0.96, 0.99, 0.99, and 0.97. All these R2 were significant at 1% level. The root mean square errors of prediction (RMSEP) for all the parameters were low indicating the high quality of the fit of the prediction models. The values were 2.15, 0.06, 1.52, and 1.44 for LC, a*/b* ratio, TCI, and firmness, respectively. However, the models for prediction of titratable acidity, soluble solids content (SSC) and acid-Brix ratio showed relatively poor reliability, with R2 value of 0.49, 0.03 and 0.65, and RMSEP of 0.43, 0.15 and 0.08, respectively.
机译:进行了实验以评估基于可见/近红外反射(VIS / NIR)光谱确定番茄(番茄番茄(Lycopersicon esculentum Mill cv'DRK 453'和'Trust'))质量属性的可行性。使用偏最小二乘回归(PLS)方法来建立预测模型。此外,通过PLS2方法建立的模型在用R2同时预测番茄的a * / b *比,TCI,硬度和LC方面表现出良好的性能。值分别为099、0.99、0.97和0.92,RMSEP分别为0.06、1.75、1.44和3.03。在此,所有R2值均再次达到1%的水平。番茄红素含量(LC),色值a * / b *比率,番茄色指数(TCI)和硬度均达到了出色的预测性能。每个参数的测定系数(R2)分别为0.96、0.99、0.99和0.97。所有这些R2均在1%的水平上显着。所有参数的预测均方根误差(RMSEP)低,表明预测模型的拟合质量很高。 LC,a * / b *比,TCI和硬度分别为2.15、0.06、1.52和1.44。但是,可滴定酸度,可溶性固形物含量(SSC)和酸-白利糖度比率的预测模型显示出相对较差的可靠性,R2值分别为0.49、0.03和0.65,RMSEP分别为0.43、0.15和0.08。

著录项

  • 作者

    Chen, Limei.;

  • 作者单位

    McGill University (Canada).;

  • 授予单位 McGill University (Canada).;
  • 学科 Agriculture Food Science and Technology.
  • 学位 M.Sc.
  • 年度 2009
  • 页码 82 p.
  • 总页数 82
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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