Optimization on tea carding technology by artificial neural network

Authors

WANG Xiaoyong, Engineering College, Anhui Agricultural University, Hefei, Anhui 230031, China; State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, Anhui 230031, China
LI Bing, Engineering College, Anhui Agricultural University, Hefei, Anhui 230031, China; State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, Anhui 230031, China
ZENG Chen, Engineering College, Anhui Agricultural University, Hefei, Anhui 230031, China; State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, Anhui 230031, China
LI Shangqing, State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, Anhui 230031, China; Tea and Food Science and Technology College, Hefei, Anhui 230031, China
WU Xiankun, Engineering College, Anhui Agricultural University, Hefei, Anhui 230031, China; State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, Anhui 230031, China

Abstract

The influences were studied. from tea carding temperature, tea carding time and the amount of leaves on the processing, taking Lu'an green tea as material. Based on the single factor experiment, the optimum parameters were selected. The optimum parameters were as followed: carding temperature 90 ℃, carding time 5 min, and the amount of leaves 1.0 kg. Experimental data were subjected to multivariate first-order regression and multivariate quadratic regression, and two regressing equations were obtained. A neural network model based on the orthogonal experiment data was established to obtain the optimum parameters, final result for temperature at 93 ℃, tea carding time is 5 minutes, the amount of leaves is 1.0 kg, and the experimental result based on the parameters from the artificial neural network is better than that based on orthogonal experiment.

Publication Date

1-28-2016

First Page

103

Last Page

105,153

DOI

10.13652/j.issn.1003-5788.2016.01.025

Recommended Citation

Xiaoyong, WANG; Bing, LI; Chen, ZENG; Shangqing, LI; and Xiankun, WU (2016) "Optimization on tea carding technology by artificial neural network," Food and Machinery: Vol. 32: Iss. 1, Article 25.
DOI: 10.13652/j.issn.1003-5788.2016.01.025
Available at: https://www.ifoodmm.cn/journal/vol32/iss1/25

References

[1] 周智修,段文华,吴海燕,等.我国名优茶发展现状与趋势[J].茶叶科学,2013,33(2):171-178.
[2] 周智修,段文华,吴海燕,等.中国名优茶消费需求调查分析[J].浙江农林大学学报,2013,30(3):412-416.
[3] 司辉清,庞晓莉,刘建军,等.机制针形名优绿茶工艺研究[J].西南农业大学学报,2003,25(4):370-373.
[4] 钟映富,周正科,胡翔,等.振动理条对针形名茶品质的影响[J].中国茶叶，2002,24(1):32-33.
[5] 余志,杨艳,周继荣,等.机制针形名茶做形工艺研究[J].茶叶科学,2007,27(4):311-315.
[6] 刘二根,王广超,朱旭生.MATLAB与数学实验[M].北京:国防工业出版社,2014.
[7] 田波平,孙秋梅,廖庆喜,等.6CZZ-600型针形名优茶做形机及成型工艺优化[J].农业工程学报,2005,21(4):65-68.
[8] 陈习村.六安瓜片加工工艺研究[D].合肥:安徽农业大学,2001.
[9] 丛爽.神经网络、模糊系统及其及其在运动控制中的应用[M].合肥:中国科学技术大学出版社,2001.
[10] 朱德泉,蒋克荣,王继先,等.干燥过程模糊神经网络控制器的设计与仿真[J].系统仿真学报,2009,21(15):4 768-4 771.
[11] 刘卫国. matlab程序设计与应用[M].2版.北京:高等教育出版社,2002.
[12] 刘海臣,卓金武,吴国光.基于人工神经网络的茶叶咖啡因提取条件的优化[J].应用化学,2007,24(4):457-460.