便携式番茄多品质参数可见/近红外检测装置研发

Development of portable device for simultaneous detection on multi-quality attributes of tomato by visible and near-infrared

该文针对番茄独特的囊室结构及整体成熟度不均等问题,基于可见/近红外全透射光谱,研发了便携式番茄内外品质快速无损实时检测装置。该装置的硬件系统主要包括光源模块、信号采集模块、信号处理模块、电源模块、散热模块和打印模块,基于该硬件系统,采集了番茄630~1 100 nm范围内可见/近红外透射光谱,选取650~1 100 nm范围的光谱进行SG卷积平滑(savitzky-Golay smooth,SG-smooth)、标准正态变量变换(standard normal variable transformation,SNV)和多元散射校正(muliplication scattering correction,MSC)等预处理,建立了番茄颜色、硬度、总酸、总糖含量的偏最小二乘预测模型。基于QT开发框架编写了番茄多品质无损检测实时分析控制软件,植入番茄多品质参数预测模型,实现了番茄多品质参数检测一键式操作。为了测试该装置的检测精度和稳定性,选取与建模无关的20个同品种样品对每个样品的内外品质重复检测8次,结果表明:番茄颜色预测值与实测值相关系数为0.952 8,均方根误差为2.703 8,硬度预测值与实测值相关系数为0.940 5,均方根误差为0.448 6 kg/cm^2,总酸含量的预测值与实测值相关系数为0.953 7,均方根误差为0.326 3%,总糖含量预测值与实测值相关系数为0.9610,均方根误差为0.197 4%。番茄样品颜色、硬度、总酸和总糖重复检测最大相对误差分别为2.9%、1.9%、2.0%和1.6%。该便携式检测装置基于可见近红外全透射光谱,实现了番茄颜色、硬度、总酸、总糖含量的同时快速无损实时检测,预测精度及稳定性较好,可以满足实时评价番茄品质的市场需求。

In order to meet the demand of quality control in the process of fruit and vegetable processing, a portable fast non-destructive testing device for portable tomato was developed based on the visible / near-infrared transmission spectrum. Based on the analysis of the difficulties in the development of portable devices with near infrared transmission spectra, a portable design system of tomato quality was proposed. The system of the device mainly included the light source, the signal acquisition module, the signal processing module, the power, the heat dissipation module and the printer. The light source consists of 8 5 W halogen lamps that provide a light source for the sample. The spectrometer is connected to the focusing lens and collects the spectral curve through the sample. In order to solve the volumetric problem of the transmission spectrum detection scheme, the spectrometer and the coupling lens are mounted on the hand-held member. The development board has a tomato multi-quality parameter prediction model, the curve collected by the spectrometer is processed, and the prediction results are displayed on the LCD （liquid crystal display）. This device can print the test results in real time through the print module. Based on this device, the visible and near-infrared total transmission spectra of tomato in the range of 650-1100 nm were collected, and the collected spectra were pretreated by Savitzky-Golay Smooth （SG-Smooth）, standard normal variable transformation （SNV）, first derivative （FD）, multiplication scattering correction （MSC） and Normalization （NOR）. The partial least squares prediction model of color and hardness, total acid and total sugar content of the tomato was established. In addition, based on QT development tools, tomato multi-quality non-destructive testing real-time analysis and control software was prepared. The multi-quality parameter prediction model of tomato was implanted into the device to predict the quality of the tomatoes. Finally, the stability and detection accuracy of the portable fast and non-destructive testing device of tomato were tested, and 20 samples were selected for repeated detection of the internal and external quality of tomato. The results showed that the correlation coefficient of tomato color between the predicted value and the measured value was 0.952 8, and the root mean square error was 2.703 8; the correlation coefficient of firmness between the predicted value and the measured value was 0.940 5, and the root mean square error is 0.448 6 kg/cm2; the correlation coefficient of the total acid content was 0.953 7, and the mean square error was 0.326 3%; the correlation coefficient of total sugar of tomato between the predicted value and the measured value was 0. 961 0 and the root mean square error was 0.197 4%. The maximum relative errors of red color, hardness, total acid and total sugar under repeated detection for tomato samples were 2.9%, 1.9%, 2.0% and 1.6%, respectively. In conclusion, the field application results indicate that this portable device can satisfy the requirements of tomato quality detection with high accuracy and good performance. The results provide the reference for rapid, non-destructive, and on-site detection technology and equipment of fruit internal quality.