Microwave Drying Characteristics and Moisture Content Prediction of Hawthorn

HE Fangjian; LI Jing; LIU Mingbao; FU Wenjie; LI Zhenfeng

doi:10.13386/j.issn1002-0306.2020090098

Volume 42 Issue 12

Jun. 2021

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Science and Technology of Food Industry > 2021 > 42(12): 32-38. > DOI: 10.13386/j.issn1002-0306.2020090098

HE Fangjian, LI Jing, LIU Mingbao, et al. Microwave Drying Characteristics and Moisture Content Prediction of Hawthorn[J]. Science and Technology of Food Industry, 2021, 42(12): 32−38. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2020090098.

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Microwave Drying Characteristics and Moisture Content Prediction of Hawthorn

HE Fangjian^1,,
LI Jing^{1, 2},
LIU Mingbao¹,
FU Wenjie¹,
LI Zhenfeng^{1, 2, ,}

1.
School of Mechanical Engineering, Jiangnan University, Wuxi 214122, China
2.
Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology, Wuxi 214122, China

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Received Date: September 09, 2020
Available Online: April 18, 2021

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Abstract

Abstract

This study aimed to explore microwave drying characteristics and realize moisture content prediction of hawthorn during drying process. The effects of drying temperature (50, 60, 70 ℃) and relative humidity (5%, 15%, 30%, 50%, 70%) on the drying characteristics and quality of hawthorn were studied. Extreme Learning Machine (ELM) was established to predict hawthorn moisture content. The results showed that the optimum drying conditions were 60 ℃ and 30% relative humidity. The color changed the least, the content of V_C was the highest, and the content of total flavonoids was higher for hawthorn. The model of ELM with the structure of “3-8-1” was established to predict moisture content. The determination coefficient R² value was 0.996 and root mean square error RMSE was 0.00952 between predicted value and experimental, which could effectively predict the moisture content of hawthorn during microwave drying. The results would provide a theoretical basis for microwave drying application and on-line moisture content prediction of hawthorn.
- hawthorn,
- microwave drying,
- relative humidity,
- extreme learning machine,
- moisture content prediction

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References

[1]	郭婷, 白向丽, 陈益能, 等. 干燥方式对大果山楂粉干燥速率及品质的影响[J]. 食品与机械,2019,35(10):122−125, 188.
[2]	Jurikova Tunde, Sochor Jiri, Rop Otakar, et al. Polyphenolic profile and biological activity of Chinese hawthorn (Crataegus pinnatifida BUNGE) fruits[J]. Molecules (Basel, Switzerland),2012,17(12):14490−14509. doi: 10.3390/molecules171214490
[3]	吕豪, 吕黄珍, 杨炳南, 等. 苦瓜微波-热风振动床干燥湿热特性与表观形态研究[J]. 农业机械学报,2020,51(4):373−381. doi: 10.6041/j.issn.1000-1298.2020.04.043
[4]	Pande R, Mishra H N, Singh M N. Microwave drying for safe storage and improved nutritional quality of green gram seed (Vigna radiata)[J]. Journal of Agricultural & Food Chemistry,2012,60(14):3809−3816.
[5]	唐小闲, 段振华, 任爱清, 等. 即食慈姑片微波干燥特性及动力学模型研究[J/OL]. 食品与机械: 1−11[2020-09-05]. http://kns.cnki.net/kcms/detail/43.1183.TS.20200629.1527.006.html.
[6]	Jing Li, Zhenfeng Li, Lili Li, et al. Microwave drying of balsam pear with online aroma detection and control[J]. Journal of Food Engineering,2020:288.
[7]	Ma X , Luo G , Li Z , et al. Microwave power control scheme for potatoes based on dielectric loss factor feedback[J]. Journal of Food Engineering,2020,288:110134.
[8]	惠菊, 李臻峰, 李静, 等. 排湿风速对微波干燥过程湿度及其干燥特性的影响[J]. 浙江农业学报,2016,28(6):1061−1068.
[9]	李静, 浦宏杰, 宋飞虎, 等. 排湿压力对微波干燥过程的影响[J]. 江苏农业科学,2015,43(5):257−259.
[10]	李静, 宋飞虎, 浦宏杰, 等. 苹果控制排湿压力微波干燥模型研究[J]. 江苏农业科学,2015,43(11):529−532.
[11]	席慧涵, 刘云宏, 王琦, 等. 马铃薯超声强化远红外辐射干燥特性及神经网络模型研究[J]. 食品与机械,2019,35(2):123−128, 152.
[12]	Tavakolipour H, Mokhtarian M. Neural network approaches for prediction of pistachio drying kinetics[J]. International Journal of Food Engineering 2012, 8(3): 1–17.
[13]	张丽丽, 王相友, 张海鹏. 山药切片红外干燥温度神经网络预测[J]. 农业机械学报,2014,45(11):246−249. doi: 10.6041/j.issn.1000-1298.2014.11.038
[14]	Liu Yunhong, Sun Yue, Miao Shuai, et al. Drying characteristics of ultrasound assisted hot air drying of flos lonicerae[J]. Journal of Food Science and Technology,2015,52(8):4955−4964. doi: 10.1007/s13197-014-1612-3
[15]	Ju H Y, Zhao S H, Mujumdar A S, et al. Energy efficient improvements in hot air drying by controlling relative humidity based on Weibull and Bi-Di models[J]. Food and Bioproducts Processing,2018,111:20−29. doi: 10.1016/j.fbp.2018.06.002
[16]	巨浩羽, 肖红伟, 郑霞, 等. 干燥介质相对湿度对胡萝卜片热风干燥特性的影响[J]. 农业工程学报,2015,31(16):296−304. doi: 10.11975/j.issn.1002-6819.2015.16.040
[17]	田华. 生姜微波干燥动力学模型构建[J]. 保鲜与加工,2020,20(1):127−132. doi: 10.3969/j.issn.1009-6221.2020.01.021
[18]	Jian Wu Dai, Jun Quan Rao, Dong Wang, et al. Process-based drying temperature and humidity integration control enhances drying kinetics of apricot halves[J]. Drying Technology,2015,33(12):365−376.
[19]	李文峰, 金欢欢, 肖旭霖. 山楂气体射流冲击干燥特性及干燥模型[J]. 食品科学,2014,35(9):69−73. doi: 10.7506/spkx1002-6630-201409015
[20]	中华人民共和国卫生部. GB 5009.86-2016 食品安全国家标准食品中抗坏血酸的测定[S]. 北京: 中国标准出版社, 2016.
[21]	李文峰, 金欢欢, 肖旭霖. 气体射流冲击干燥对山楂抗坏血酸、还原糖、总酸及总黄酮的影响[J]. 食品与发酵工业,2013,39(7):147−153.
[22]	Mohammad Hossein Nadian, Shahin Rafiee, Mortaza Aghbashlo, et al. Continuous real-time monitoring and neural network modeling of apple slices color changes during hot air drying[J]. Food and Bioproducts Processing,2015,94:263−274. doi: 10.1016/j.fbp.2014.03.005
[23]	白竣文, 田潇瑜, 马海乐. 基于BP神经网络的葡萄气体射流冲击干燥含水率预测[J]. 现代食品科技,2016,32(12):198−203.
[24]	刘品, 刘寅, 张艳, 等. 干燥介质相对湿度对红枣热风干燥特性的影响[J]. 食品与发酵工业,2019,45(11):185−190.
[25]	于海明, 李海源, 张欣悦, 等. 水稻秸秆营养穴盘微波热风耦合干燥动力学模型研究[J]. 农业机械学报,2020,51(5):339−348. doi: 10.6041/j.issn.1000-1298.2020.05.037
[26]	Huang G B, Zhu Q Y, Siew C K. Extreme learning machine: Theory and applications[J]. Neurocomputing,2006,70(1−3):489−501. doi: 10.1016/j.neucom.2005.12.126

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