Identification of watermelon varieties and forecast for sugar content of watermelon based on vibration characteristics

Authors

ZHUANG Wei, School of Mechanical Engineering of Jiangnan University, Wuxi, Jiangsu 214122, China
LI Zhenfeng, School of Mechanical Engineering of Jiangnan University, Wuxi, Jiangsu 214122, China; Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology, Wuxi, Jiangsu 214122, China
SONG Feihu, School of Mechanical Engineering of Jiangnan University, Wuxi, Jiangsu 214122, China; Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology, Wuxi, Jiangsu 214122, China
LI Jing, School of Mechanical Engineering of Jiangnan University, Wuxi, Jiangsu 214122, China; Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology, Wuxi, Jiangsu 214122, China
WANG Disong, School of Mechanical Engineering of Jiangnan University, Wuxi, Jiangsu 214122, China
ZHU Guanyu, School of Mechanical Engineering of Jiangnan University, Wuxi, Jiangsu 214122, China

Abstract

In order to solve the problem of consumers misjudgment by hitting watermelon because of different watermelon varieties, a vibration detection system was built to get the frequency response functions of “Huang guan”, “Zaojia8424”, “Jng xin” and “Xisha” watermelon. Using the PNN neural network model achieved the identification of watermelon varieties, and the accuracy was more than 92%.At the same time,according to the relationship between the sugar content and the main resonant peak frequency, the prediction model of the sugar content of each variety of watermelon was established by stepwise multivariate linear regression analysis, and the coefficient were all above 0.86.The prediction set samples were identified and then predicted the sugar content. The measurement error of the sugar content of the watermelons which were identified accurately was less than 6.2%. The measurement error of the sugar content was larger for the watermelon which was identified mistakenly because of error prediction model. On the above basis, the unknown watermelons in the market could be identified, and then the appropriate corresponding model was selected automatically to measure the sugar content.

Publication Date

4-28-2018

First Page

140

Last Page

145,179

DOI

10.13652/j.issn.1003-5788.2018.04.029

Recommended Citation

Wei, ZHUANG; Zhenfeng, LI; Feihu, SONG; Jing, LI; Disong, WANG; and Guanyu, ZHU (2018) "Identification of watermelon varieties and forecast for sugar content of watermelon based on vibration characteristics," Food and Machinery: Vol. 34: Iss. 4, Article 29.
DOI: 10.13652/j.issn.1003-5788.2018.04.029
Available at: https://www.ifoodmm.cn/journal/vol34/iss4/29

References

［1］ 王琛, 张琳, 赵姜, 等. 中国西瓜市场形势分析与展望［J］. 农业展望, 2013, 9(4): 27-30.
［2］ 吕飞玲. 基于声学特性的西瓜品质无损检测方法研究［D］. 杭州: 浙江大学, 2003: 10.
［3］ NOURAIN Jamal, YING Yi-bin, WANG Jian-ping, et al. Firmness evaluation of melon using its vibration characteristic and finite element analysis［J］. Journal of Zhejiang University Science, 2005(6): 483-490.
［4］ ABBASZADEH R, RAJABIPOUR A, DELSHAD M, et al. Evaluation of watermelons texture using their vibration responses［J］. Biosystems Engineering, 2013, 115(1): 102-105.
［5］ ABBASZADEH R, RAJABIPOUR A, AHMADI H, et al. Prediction of watermelon quality based on vibration spectrum［J］. Postharvest Biology and Technology, 2013, 86: 291-293.
［6］ MAO Jian-hua, YU Yong-hua, RAO Xiu-qin, et al. Firmness prediction and modeling by optimizing acoustic device for watermelons［J］. Journal of Food Engineering, 2016, 168: 1-6.
［7］ TANIWAKI M, TOHRO M, SAKURAI N. Measurement of ripening speed and determination of the optimum ripeness of melons by a nondestructive acoustic vibration method［J］. Postharvest Biology and Technology, 2010, 56(1): 101-103.
［8］ TANIWAKI M, TAKAHASHI M, SAKURAI N. Determina-tion of optimum ripeness for edibility of postharvest melons using nondestructive vibration［J］. Food Research International, 2009, 42(1): 137-141.
［9］ 方汉良, 任志英, 郑志强, 等. 西瓜成熟度测试仪设计研究［J］. 赤峰学院学报: 自然科学版, 2015, 31(12): 53-54.
［10］ 浦宏杰, 汪迪松, 李臻峰. 基于振动频谱子带质心的西瓜内部品质检测［J］. 农业机械学报, 2017, 48(1): 281-288.
［11］ 陆勇, 李臻峰, 浦宏杰, 等. 基于声振法的西瓜贮藏时间检测［J］. 浙江农业学报, 2016, 28(4): 682-687.
［12］ 高宗梅, 张文, 任梦佳, 等. 西瓜品质LDV测振响应影响因素分析［J］. 农业机械学报, 2015, 46(S1): 134-140.
［13］ 魏巍. 西瓜振动特性及振动对其品质影响研究［D］. 呼和浩特市: 内蒙古农业大学, 2015: 24-32.
［14］ 屠康, 马龙, 潘秀娟. 敲击振动无损检测3种梨果实品质参数的研究［J］. 安徽农业大学学报, 2005(1): 50-53.
［15］ 王书茂, 焦群英, 籍俊杰. 西瓜成熟度无损检验的冲击振动方法［J］. 农业工程学报, 1999, 15(3): 241-245.
［16］ 危艳君, 饶秀勤, 漆兵. 基于声学特性的西瓜糖度检测系统［J］. 农业工程报, 2012, 28(3): 283-287.
［17］ 汪迪松, 浦宏杰, 李臻峰, 等. 基于声振法的西瓜内部糖度检测研究［J］. 上海农业报, 2017, 33(2): 125-130.
［18］ 赵洪卫, 韩东海, 宋曙辉, 等. 小型西瓜果实成熟度表征因子筛选［J］. 农业工程学报, 2012, 28(17): 281-286.
［19］ 任毅. 西瓜果实含糖量QTL定位及糖转运蛋白基因功能初析［D］. 北京: 中国农业科学院, 2016: 6.
［20］ 孙菊华, 陈春雷, 陈建才. 甜瓜品比试验简报［J］. 上海农业科技, 2011(1): 50-51.
［21］ 朱迎春, 刘君璞, 邓云, 等. 河南地区中、小果型西瓜品种比较试验［J］. 中国瓜菜, 2016, 29(12): 51-54.