为了探索一种简捷、 快速、 高效的西红柿品质检测方法， 应用近红外光谱技术与光纤传感技术相结合的新方法， 快速测量西红柿果浆样品中营养成分的含量。 实验所用的主要仪器为近红外光纤光谱仪， 波长范围为900～2　500 nm。 以164个西红柿样品为标准样品， 进行了光谱采集及相应的化学值测定。 实验数据采用偏最小二乘法（PLS）进行回归，　建立西红柿果浆中总酸及可溶性糖含量的数学模型， 并对回归方法进行统计分析。 结果为： 西红柿果浆中总酸验证集的决定系数（R2）为0.967， 均方根误差（RMSEC）为0.133， 预测均方根误差（RMSEP）为0.103； 总糖验证集的决定系数（R2）为0.976， 均方根误差（RMSEC）为0.463， 预测均方根误差（RMSEP）为0.460。 均达到了较好的预测结果， 表明该方法对定量分析西红柿果浆中多组分含量是可行的。 基于该方法快速、 简便及可对同一样品多组分含量同时分析的优点,它是一种极具发展前途的传感器， 正在逐渐成为国际传感器领域的研究热点。

In order to explore a simple, rapid and efficient tomato quality detection method, in the present experiment near infrared spectroscopy and optical fiber sensing technology were applied to quickly measure the nutrition ingredient content in tomato juice samples. The main instrument used in this experiment was near infrared optical fiber spectrometer in a wavelength range from 900 to 2 500 nm, which measured the absorbance of the tomato juice samples; A collection of one hundred and sixty-four tomato juice samples were selected as the standard samples, the spectra and the corresponding chemical value were measured. Partial least squares (PLS) was adopted to establish the mathematical model of the total acid and soluble sugar content in tomato juice samples, and the regression equation was statistically analysed. The total acid in tomato juice prediction correlation coefficient was 0.967, calibration standard deviation (RMSEC) was 0.133, standard error of prediction (RMSEP) was 0.103; the soluble sugar prediction correlation coefficient is 0.976, calibration standard deviation (RMSEC) was 0.463, and the standard error of prediction (RMSEP) was 0.460. The above data achieved better forecasting results, which showed that the method of quantitative analysis of tomato fruit multicomponent content was feasible. The method is rapid, simple and can do multicomponent analysis on the same sample simultaneously. It is a promising sensor and gradually becoming a international research focus in sensor field.