Abstract
The aim of this work was to fulfill the objective and rapid assessment of quality and flavor of fresh orange juice with different storage time. An electronic tongue system that based on virtual instrument technology was developed and used to the qualitative and quantitative analysis of fresh orange juice samples with six kinds of storage time. According to the characteristics of electronic tongue respond signal, it was first preprocessed by the principal component analysis (PCA) method and discrete wavelet transform (DWT) method, respectively. According to the classification result, the DWT was selected as a recommended feature extraction method. Then the linear discriminant analysis (LDA) was used to the qualitative analysis of fresh orange juice samples with different storage time. Moreover, the least squared-support vector machines based on particle swarm optimization method (PSO-LSSVM) was applied to quantitative forecast the different storage time. The results showed that the cumulative contribution rate of LD1 and LD2 was reached 95.7% when the linear discriminant analysis was employed, and the fresh orange juice samples with the six kinds of storage time were effectively discriminated; The PSO-LSSVM prediction model had high prediction precision for different storage time of fresh orange juice, the correlation coefficient (R2) root mean square error (RMSE), mean absolute error (MAE) were 0.999 1, 0.287 7, and 0.232 8, respectively. This study could provide technical reference for quality evaluation and monitoring of fresh fruit juice.
Publication Date
11-28-2017
First Page
137
Last Page
142,203
DOI
10.13652/j.issn.1003-5788.2017.11.029
Recommended Citation
Qingrui, SHI; Tingting, GUO; Tingjia, YIN; Zhiqiang, WANG; Caihong, LI; Yemin, GUO; and Xia, SUN
(2017)
"Research on detection for the storage quality of orange juice based on the electronic tongue,"
Food and Machinery: Vol. 33:
Iss.
11, Article 29.
DOI: 10.13652/j.issn.1003-5788.2017.11.029
Available at:
https://www.ifoodmm.cn/journal/vol33/iss11/29
References
[1] 陈学红, 贺菊萍. 草莓采后生理和品质变化及保鲜技术[J]. 河北农业科学, 2008, 12(9): 19-22.
[2] 马清河, 胡常英, 刘丽娜, 等. 葡萄糖氧化酶在果汁保鲜中的应用[J]. 中国食品添剂, 2005(1): 83-85.
[3] 吴燕华, 刘文力, 阎红, 等. 高效液相色谱法测定苹果中的酚类物质[J]. 分析化学, 2002, 30(7): 826-828.
[4] 王海佳. 紫外分光光度法研究维生素C的稳定性及蔬果和果汁中含量的测定[D]. 太原: 山西医科大学, 2015: 1-5.
[5] 赵煜, 韦真博, 王俊. 电子舌信号与理化指标的信息融合区分不同养殖水的研究[J]. 农业工程学报, 2012， 28（1）: 153-160.
[6] 曹仲文, 张晓燕, 周晓燕. 电子舌对鸡汤和人工勾兑高汤及其混合样品的识别[J]. 食品与机械, 2015, 31(1): 14-17.
[7] 易宇文, 范文教, 贾洪峰, 等. 基于电子舌的微冻鲢鱼新鲜度识别研究[J]. 食品与机械, 2014, 30(2): 142-145.
[8] LORENZ J K, REO J P, HENDL O, et al. Evaluation of a taste sensor instrument (electronic tongue) for use in formulation development[J]. International Journal of Pharmaceutics, 2009, 367(1/2): 65-72.
[9] 杜瑞超, 王优杰, 吴飞, 等. 电子舌对中药滋味的区分辨识[J]. 中国中药杂志, 2013, 38(2）: 154-160.
[10] 王志强, 王辉, 张志豪, 等. 基于电化学和虚拟仪器的土壤重金属检测系统研究[J]. 农业机械学报, 2015, 46(1）: 119-126.
[11] KIRSANOV D, ZADOROZHNAYA O, KRASHENINNIKOV A, et al. Water toxicity evaluation in terms of bioassay with an Electronic Tongue[J]. Sensors & Actuators B Chemical, 2013, 179(4): 282-286.
[12] 高利萍, 王俊, 崔绍庆. 电子舌检测不同冷藏时间草莓鲜榨汁的品质变化[J]. 农业工程学报, 2012, 28（23）: 250-256.
[13] 张淼, 贾洪锋, 李燮昕, 等. 电子舌在鲜榨橙汁掺假识别中的应用研究[J]. 食品与机械, 2015 (6): 92-94.
[14] BALDEN E O, ALCANIZ M, MASOT R, et al. Voltamme-try pulse array developed to determine the antioxidant activity of camu-camu ( Myrciariadubia, ﹝H.B.K.﹞ McVaug) and tumbo ( Passiflora mollisima, ﹝Kunth﹞ L.H. Bailey) juices employing voltammetric electronic tongues[J]. Food Control, 2015, 54: 181-187.
[15] HADDI Z, MABROUK S, BOUGRINI M, et al. E-Nose and e-Tongue combination for improved recognition of fruit juice samples[J]. Food Chemistry, 2014, 150(2): 246-253.
[16] 王茹. 智舌中智能模式识别单元的实现与应用研究[D]. 杭州: 浙江工商大学, 2009: 7-8.
[17] 邵婷婷, 白宗文, 周美丽. 基于离散小波变换的信号分解与重构[J]. 计算机技术与发展, 2014(11): 159-161.
[18] 蒋梅城, 陆继东, 姚顺春, 等. 小波变换在激光诱导击穿光谱压缩中的应用[J]. 光谱学与光谱分析, 2010, 30(10): 2 797-2 801.
[19] GHOSH A, TUDU B, TAMULY P, et al. Prediction of the-aflavin and thearubigin content in black tea using a voltammetric electronic tongue[J]. Chemometrics & Intelligent Laboratory Systems, 2012, 116(7): 57-66.
[20] CET X, GUTIRREZ-CAPITN M, CALVO D, et al. Beer classification by means of a potentiometric electronic tongue[J]. Food Chemistry, 2013, 141(3): 2 533-2 540.
[21] 熊萧萧, 王鲁峰, 徐晓云, 等. 基于电子舌技术对不同年份的化橘红的识别[J]. 宁波大学学报: 理工版, 2012, 25(3): 21-24.
[22] GUTIRREZ J M, HADDI Z, AMARI A, et al. Hybrid electronic tongue based on multi-sensor data fusion for discrimination of beers[J]. Sensors & Actuators B Chemical, 2013, 177(1): 989-996.
[23] 冯学军. 最小二乘支持向量机的研究与应用[J]. 安庆师范学院学报: 自科版, 2009, 15(1): 112-113.
[24] 刘双印, 徐龙琴, 李振波, 等. 基于PCA-MCAFA-LSSVM的养殖水质pH值预测模型[J]. 农业机械学报, 2014, 45(5): 239-246.
[25] WEI Zhen-bo, WANG Jun. Tracing floral and geographical origins of honeys by potentiometric and voltammetric electronic tongue[J]. Computers & Electronics in Agriculture, 2014, 108: 112-122.
[26] 吴瑞梅, 赵杰文, 陈全胜, 等. 基于电子舌技术的绿茶滋味品质评价[J]. 农业工程学报, 2011, 27(11): 378-381.
[27] LU Lin, HU Xian-qiao, TIAN Shi-yi， et al. Visualized attribute analysis approach for characterization and quantification of rice taste flavor using electronic tongue[J]. Analytica Chimica Acta, 2016, 919: 11-19.