光谱学与光谱分析, 2020, 40 (2): 543, 网络出版: 2020-05-12  

近红外光谱结合变量优选和GA-ELM模型的干制哈密大枣水分含量研究

Study on the Moisture Content of Dried Hami Big Jujubes by Near-Infrared Spectroscopy Combined with Variable Preferred and GA-ELM Model
作者单位
1 石河子大学机械电气工程学院, 新疆 石河子 832003
2 农业农村部西北农业装备重点实验室, 新疆 石河子 832003
3 石河子大学食品学院, 新疆 石河子 832003
摘要
水分含量是哈密大枣干制过程中的重要指标, 对其外观、 口感、 贮藏和运输具有重要的影响。 因此, 为实现哈密大枣水分含量的准确预测, 采用近红外光谱结合变量优选方法, 建立干制哈密大枣水分含量的GA-ELM预测模型。 为提高模型的稳定性和预测精度, 开展并讨论了核函数和神经元个数对GA-ELM预测模型的影响。 采用多种预处理方法对全波段光谱进行处理, 对比分析发现标准正态变换方法(SNV)效果最佳。 对标准正态变换处理后的光谱利用连续投影算法(SPA)、 联合区间偏最小二乘(si-PLS)和遗传算法(GA)及其组合算法分别从全波段927.77~2 501.14 nm范围内筛选特征波长, 并建立对应GA-ELM预测模型, 同时与全波段的GA-ELM模型效果相比较, 采用SNV+SPA筛选的14个特征波长建立的GA-ELM模型效果最佳, 预测结果Rc和Rp分别为0.984 2和0.967 5, RMSEC和RMSEP分别为0.006 1和0.007 9, RPD为3.678 8。 研究结果表明: SNV+SPA+GA-ELM方法可实现干制哈密大枣水分含量的准确预测, 为近红外光谱技术应用于干制哈密大枣在线检测提供了参考。
Abstract
Moisture content is an important index in the drying process of Hami big jujubes which has an important influence on its appearance, taste, storage and transportation. Therefore, in order to realize the accurate prediction of the moisture content of Hami big jujubes, GA-ELM prediction model of the moisture content of dried Hami big jujubes was studied by using Near-Infrared spectroscopy combined with variable preferred method. In order to improve the stability and prediction accuracy of the model, the effects of kernel function and the number of neurons on the GA-ELM prediction model were discussed. Various pretreatment methods were used to deal with the spectrum of the whole band. The comparison analysis denoted that the standard normal variation (SNV) method was the best. The characteristic wavelengths were screened from the range of 927.77~2 501.14 nm by combining with successive projection algorithm (SPA), the synergy interval partial least squares (si-PLS, genetic algorithm (GA) and their combination algorithms after processing of SNV. Respectively, the corresponding GA-ELM prediction model was established. The GA-ELM model with 14 characteristic wavelengths screened by SNV and SPA had the best effect while compared with the full-band GA-ELM model. Furthermore, the predicted results could be given as follows: Rc and Rp are 0.984 2 and 0.967 5, RMSEC and RMSEP are 0.006 1 and 0.007 9 while RPD is 3.678 8. The results denoted that the SNA+SPA+GA-ELM method can realize the accurate prediction of moisture content of dried Hami big jujubes and provide a reference for the application of near-infrared spectroscopy in the on-line detection of dried Hami big jujubes.

王文霞, 马本学, 罗秀芝, 李小霞, 雷声渊, 李玉洁, 孙静涛. 近红外光谱结合变量优选和GA-ELM模型的干制哈密大枣水分含量研究[J]. 光谱学与光谱分析, 2020, 40(2): 543. WANG Wen-xia, MA Ben-xue, LUO Xiu-zhi, LI Xiao-xia, LEI Sheng-yuan, LI Yu-jie, SUN Jing-tao. Study on the Moisture Content of Dried Hami Big Jujubes by Near-Infrared Spectroscopy Combined with Variable Preferred and GA-ELM Model[J]. Spectroscopy and Spectral Analysis, 2020, 40(2): 543.

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