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首页> 外文期刊>Acta Horticulturae >Detection of Internal Mold Infection in Tomato by Transmittance Near Infrared Spectroscopy
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Detection of Internal Mold Infection in Tomato by Transmittance Near Infrared Spectroscopy

机译:近红外光谱法检测番茄内部霉菌感染

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Alternaria alternata is the black mold occurring inside tomato. This defect can be normally found by destructive method but it cannot be detected by visible inspection from outside appearance of intact tomato. Therefore, a non-destructive technique for prediction of internal mold infection in tomato is required. Near infrared (NIR) spectroscopy technique was considered in this research. Transmittance NIR spectra in the range of 665-955 nm of tomato were acquired. Partial least squares-discriminant analysis (PLS-DA) was performed to establish the calibration model. Results indicated that combination of the standard normal variate transformation (SNV) and smoothing (Savitzky-Golay) pretreatment appeared the best method to develop the model. The calibration model was cross-validated by a training set (N=140) and used for prediction by a test set (N=60). It obtained 85.0% (corrected 88.7% in normal samples and corrected 81.2% in defected samples) and 91.7% (corrected 100% in normal samples and corrected 83.9% in defected samples) of the total accuracy for calibration and prediction, respectively. Moreover, defected samples were classified in 3 levels of infection severity. The accuracies of cross validation for groups of low, medium and high infection severity were investigated and obtained 82.2, 82.4 and 90.0%, respectively. In conclusion, the calibration model from transmittance NIRS technique can be applied for rapid and non-destructive sorting of internal mold infection in intact tomato.
机译:Alternaria alternata是番茄内部的黑色霉菌。通常可以通过破坏性方法找到该缺陷,但是从完整的西红柿外观上无法通过肉眼检查发现。因此,需要一种用于预测番茄内部霉菌感染的非破坏性技术。在这项研究中考虑了近红外(NIR)光谱技术。获得了番茄在665-955 nm范围内的透射近红外光谱。进行偏最小二乘判别分析(PLS-DA)以建立校准模型。结果表明,标准正态变量转换(SNV)和平滑(Savitzky-Golay)预处理相结合是开发模型的最佳方法。通过训练集(N = 140)对校准模型进行交叉验证,并通过测试集(N = 60)将其用于预测。分别获得了校准和预测总准确度的85.0%(正常样品校正为88.7%,缺陷样品校正为81.2%)和91.7%(正常样品校正为100%,缺陷样品校正为83.9%)。此外,将缺陷样品分为3种感染严重程度等级。对低,中和高感染严重性组的交叉验证准确性进行了研究,分别获得了82.2%,82.4%和90.0%。总之,基于透射近红外光谱技术的校准模型可用于完整番茄内部霉菌感染的快速无损分选。

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