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首页> 外文期刊>Biosystems Engineering >Non-destructive measurement of soluble solids content of three melon cultivars using portable visible/near infrared spectroscopy
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Non-destructive measurement of soluble solids content of three melon cultivars using portable visible/near infrared spectroscopy

机译：使用便携式可见/近红外光谱法不破坏性测量三种甜瓜品种的可溶性固体含量

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In this study, a non-destructive method using visible/near infrared (Vis/NIR) spectroscopy was investigated to predict the soluble solids content (SSC) of intact melons (Cucumis melo L.) cv. 'Manao', 'Jinhongbao', 'Xizhoumi'. A set of 360 samples (120 melons of each cultivar) was used to develop the calibration model, and two location (stylar-end and equatorial locations) models were investigated independently. The samples' spectra were obtained by a portable Vis/NIR photo-diode array spectrometer operated in reflectance mode. Multiplicative scatter correction (MSC), first derivative and Savizky-Golay (SG) smoothing in turn were applied to the obtained spectra. The region from 750 to 950 nm was selected to develop NIR models combined with the partial least squares (PLS) regression method. The results indicated that the stylar-end of the intact melon was the proper location to evaluate the SSC in the intact melon due to its suitable and exclusive physiological structure. A competitive adaptive reweighted sampling (CARS) algorithm was used to select effective wavelengths. Results showed that the CARS algorithm had great potential for simplifying the variables. Furthermore, another 195 samples were used for external prediction to evaluate the CARS-PLS model's accuracy and stability, which resulted in a high determination coefficient (R-p(2) = 0.83) and a low root mean square error (RMSEP = 0.73 degrees Brix). (C) 2019 IAgrE. Published by Elsevier Ltd. All rights reserved.
机译：在该研究中，研究了使用可见/近红外线（VI / NIR）光谱法的非破坏性方法，以预测完整瓜（Cucumis Melo L.）Cv的可溶性固体含量（SSC）。 '曼海'，“金宏宝”，'锡州米'。使用一组360个样品（每种品种的120个甜瓜）来开发校准模型，并独立研究了两个位置（Stylar-End和赤道地点）模型。通过以反射模式操作的便携式VIR / NIR光电二极管阵列光谱仪获得样本光谱。乘法散射校正（MSC），第一个导数和SAVIZKY-GOLAY（SG）依次平滑施加到所获得的光谱。选择从750到950nm的区域开发与局部最小二乘（PLS）回归方法组合的NIR模型。结果表明，由于其合适且专属的生理结构，完整甜瓜的智光末端是评价完整甜瓜中的SSC的适当位置。使用竞争性的自适应重新重量的采样（CARS）算法用于选择有效波长。结果表明，汽车算法对简化变量有很大的潜力。此外，另一个195个样本用于外部预测，以评估汽车-PLS模型的准确性和稳定性，从而导致高测定系数（RP（2）= 0.83）和低根均方误差（RMSEP = 0.73度BRIX） 。 （c）2019年IAGRE。 elsevier有限公司出版。保留所有权利。

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