蚁群和遗传算法优化花茶花青素近红外光谱预测模型的比较  

Optimization of NIR Spectroscopy Based on Ant Colony Optimization and Genetic Algorithm for the Anthocyanin Content in Scented Tea

作　　者：李艳肖[1] 黄晓玮[1] 邹小波[1] 赵杰文[1] 石吉勇[1] 张小磊[1] 

机构地区：[1]江苏大学食品与生物工程学院,江苏镇江212013

出　　处：《食品与生物技术学报》2015年第6期575-583,共9页Journal of Food Science and Biotechnology

基　　金：国家自然科学基金项目(60901079);国家863计划项目(2011AA108007);江苏省杰出青年基金项目(BK2013010);江苏特聘教授基金项目(201205)

摘　　要：以建立花茶花青素含量的最优近红外光谱模型为目标,对比研究了蚁群算法(Ant ColonyOptimization,ACO)和遗传算法(Genetic Algorithm,GA)优化近红外光谱谱区的效果。ACO-i PLS将全光谱划分为12个子区间时,优选出第1、9、10共3个子区间,所建的校正集和预测集相关系数分别为0.901 3和0.864 2;交互验证均方根误差(RMSECV)和预测均方根误差(RMSEP)分别为0.160 0 mg/g和0.202 0 mg/g;GA-i PLS将全光谱划分为15个子区间时,优选出第1、5共2个子区间,所建模型的校正集和预测集相关系数分别为0.906 3和0.879 3,交互验证均方根误差(RMSECV)和预测均方根误差(RMSEP)分别为0.156 0 mg/g和0.206 0 mg/g。研究结果表明:ACO-i PLS和GA-i PLS均可以有效选择近红外光谱特征波长,其中GA-i PLS模型的精度更高。Optimization of Near infrared （NIR） spectroscopy for quantitative analysis of the anthocyanin content in scented tea was discussed by selecting the optimal spectra intervals from the whole NIR spectroscopy using two variable models： Ant colony optimization interval partial least squares （ACO-iPLS） and Genetic Algorithm interval partial least squares （GA-iPLS）. The ACO-iPLS full-spectrum was split into 12 intervals. The optimal intervals selected were the 1st interval, 9th interval and 10th interval. The calibration and prediction correlation coefficient of ACO-iPLS model were 0.901 3 and 0.864 2, in which the root mean square error of cross validation （RMSECV） of 0.160 0 mg/g and the root mean square error of prediction （RMSEP） of 0.206 0 mg/g were achieved.As in the GA-iPLS model, the data set was split into 15 intervals for optimization where 1st and 5th intervals were selected. The calibration and prediction correlation coefficient of GA-iPLS model were 0.901 3 and 0.864 2, and the RMSECV and RMSEP of GA-iPLS models based on these intervals were 0.156 0 mg/g and 0.206 0 mg/g, respectively. The results showed that both ACO-iPLS and GA-iPLS models could efficiently select spectrum intervals for quantitative analysis of anthocyanin in scented tea. The optimal GA-iPLS model had better performance with higher accuracy.

关 键 词：蚁群算法 遗传算法 区间偏最小二乘法 花茶 花青素 定量分析模型 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]