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首页> 外文期刊>Sensor Letters: A Journal Dedicated to all Aspects of Sensors in Science, Engineering, and Medicine >Non-Destructive Measurement of Soluble Solids Content and Vitamin C in Gannan Navel Oranges by Vis-NIR Spectroscopy
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Non-Destructive Measurement of Soluble Solids Content and Vitamin C in Gannan Navel Oranges by Vis-NIR Spectroscopy

机译：可见-近红外光谱法无损检测赣南脐橙中可溶性固形物和维生素C

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摘要

The potential of visible and near-infrared (Vis-NIR) spectroscopy was investigated for its ability to non-destructively measurement soluble solids content (SSC) and vitamin C (VC) in intact Gannan navel oranges. A total of 238 navel oranges were used for diffuse reflectance Vis-NIR in 350-1800 nm range. In this study, calibration models relating Vis-NIR spectra to SSC and VC were developed based on partial least squares regression (PLSR) with respect to the standard normal variate (SNV) absorbance spectra. Reasonable prediction results (r_p = 0.77, SEP = 0.65° Brix and RSE = 4.96%) were obtained for SSC, while prediction results (r_p = 0.54, SEP = 4.40 mg/100 g and RSE = 8.50%) for VC could not be unacceptable. Multiple linear regression (MLR) models combined with the fingerprint spectra could obtain better prediction performance for SSC and VC in navel oranges, resulting in r_p of 0.80 and 0.55, and SEP of 0.61° Brix and 4.36 mg/100 g for SSC and VC, respectively. The fingerprint spectra analysis is very useful in the field of food chemistry, and further study on other materials is needed to apply this technique.
机译：研究了可见和近红外（Vis-NIR）光谱技术的潜力，因为它能够无损测量完整甘南脐橙中的可溶性固形物含量（SSC）和维生素C（VC）。总共238个脐橙用于350-1800 nm范围内的漫反射Vis-NIR。在这项研究中，基于偏最小二乘回归（PLSR）相对于标准正态变量（SNV）吸收光谱，开发了将Vis-NIR光谱与SSC和VC相关的校准模型。对于SSC获得了合理的预测结果（r_p = 0.77，SEP = 0.65°糖度和RSE = 4.96％），而VC的预测结果（r_p = 0.54，SEP = 4.40 mg / 100 g和RSE = 8.50％）无法获得不可接受的。多元线性回归（MLR）模型与指纹图谱相结合可以对脐橙中的SSC和VC获得更好的预测性能，得出r_p为0.80和0.55，SEP为0.61°白利糖度，SSC和VC为4.36 mg / 100 g，分别。指纹图谱分析在食品化学领域非常有用，应用此技术还需要对其他材料进行进一步研究。

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