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在Android平台上对C11708MA微型近红外光谱仪进行系统开发,实现光谱仪控制、样品指标测量、调用模型文件并显示样品可溶性固形物的预测结果等功能。利用近红外漫反射无损检测技术对镇江句容果园水蜜桃样品的可溶性固形物含量进行相关研究,运用化学计量学方法建立了水蜜桃可溶性固形物含量的近红外模型,并对模型的性能进行了评价。结果表明,采用偏最小二乘法(PLS)建立模型,光谱预处理的最佳条件为:移动窗口平滑(MAF)和Savitzky-Golay一阶导数。所建模型的校正相关系数(R_c)和预测相关系数(R_p)分别为0.931 1和0.880 2,校正标准偏差(RMSEC)和预测标准偏差(RMSEP)分别为0.441 0和0.531 0。开发的App程序运行稳定,预测结果准确,可应用于水蜜桃内部品质可溶性固形物含量的快速、无损、活体检测。
On the Android platform C11708MA micro-NIR spectrometer system development, to achieve the spectrometer control, sample measurement indicators, call the model file and display the results of the sample of soluble solids and other functions. Near infrared diffuse reflectance nondestructive testing technique was applied to study the soluble solids content of peach peaches in Jurong orchard of Zhenjiang. The near infrared model of soluble solids content of peaches was established by using chemometrics method. The performance of the model Evaluation. The results show that the optimal conditions for spectral preprocessing are the moving window smoothing (MAF) and the Savitzky-Golay first-order derivative using partial least squares (PLS) modeling. The calibration correlation coefficient (R_c) and prediction correlation coefficient (R_p) of the model were 0.931 1 and 0.880 2, respectively. The RMSEC and RMSEP were 0.441 0 and 0.531 0 respectively. The developed App program is stable and predictable. It can be applied to the rapid, nondestructive and in vivo detection of the soluble solid content of the inner quality of peaches.