利用光密度法对掺假豆浆的定性判别研究

蛋白质含量是豆浆品质评价的主要指标，实验运用近红外光谱技术获得83 个真伪豆浆的光谱，并对光谱图和光密度值进行统计分析，研究以蛋白质为主要定性指标的豆浆品质等级划分的可行性，建立豆浆品质定性判别的标准。结果显示：在波长742.59～810.96 nm范围内，随着豆浆样品蛋白质含量的升高，吸收光谱峰值变化越大。实验选取OD810.96 nm与OD742.59 nm做光密度差值分布图，根据83 个校正集样品的光密度差值分布图，确定豆浆两级判别的检测标准为：ΔOD742.59～810.96 nm大于0.062 9时，豆浆为不合格豆浆；ΔOD742.59～810.96 nm小于或等于0.062 9时，豆浆为合格豆浆。根据该判别标准对37 个预测集样品进行判别，17 个不合格豆浆全部被判别，正确判别率100%，20 个合格豆浆中有2 个被误判成不合格，误判率10%，预测结果准确率较高。实验应用光密度法进行豆浆品质的评价是可行的，方法简明、结果可靠，可为豆浆品质快速检测技术的应用提供一种参考方法。

Qualitative Discrimination of Adulterated Soymilk Using Optical Density Method

Soymilk protein content is a major index for quality evaluation. In this study, near infrared spectra were obtained
for 83 adulterated soymilk samples and then the spectra and optical density of these adulterated samples were analyzed
by statistical methods. The feasibility for qualitative discrimination of soymilk quality was studied by using protein as the
major qualitative index. At last, qualitative discrimination standard was established. The experimental results indicated
that the spectral peak changed obviously in the wavelength range from 742.59 to 810.96 nm with an increase in soymilk
protein content. The optical density OD810.96 nm and OD742.59 nm were used to plot distribution diagram. Based on optical
density distribution diagram of 83 calibration samples, the soymilk classification model of OD difference was confirmed as
following: when its value of ΔOD742.59-810.96 nm was more than 0.062 9, the soymilk sample was classified into adulterated
sample, otherwise it was normal soymilk sample. Totally 37 prediction set samples were classified according to the model;
100% of adulterated soymilk in the prediction set were classified as adulterated samples, and 2 of 20 normal soymilk
samples were classified wrongly into adulterated samples. The preferable prediction results indicated that the accuracy of the
developed method was superior. The feasibility of soymilk quality evaluation based on optical density combined with near
infrared spectral data was confirmed. The method was simple and reliable, and could provide certain references for the rapid
detection of soymilk quality.