Abstract
In order to study drying characteristics of contact ultrasound strengthened far-infrared radiation drying on potato slices, a far-infrared radiation with ultrasound assistance was applied to study the effects of different ultrasound power and far-infrared radiation drying temperature on drying process and effective moisture diffusivity values of potato. The results showed that the rise of both ultrasound power and radiation temperature could promote the mass and heat transfer in the material, shorten the drying time, and enhance the drying rate effectively of potato slices. The enhancing effect of ultrasound is weakened gradually with the decrease of water content of material and strengthened with the increase of ultrasonic power. The ultrasound strengthening phenomenon of first strengthening and then weakening with the increase of radiation temperature indicates that excessive radiation temperature will weaken the internal mass transfer effect. The effective moisture diffusion coefficient values are in the range of 1.15×10-10～3.18×10-10 m2/s, and the increases of both ultrasound power and radiation temperature could promote the flow and diffusion of water, and therefore, improve the corresponding Deff values. According to the drying process of potato, three neural network models, Elman, RBF and BP, were constructed to predict the material moisture content. The results showed that all the three neural networks could achieve good prediction performance. The BP network model, which using the optimization algorithm could reach the highest fitting precision between the predicted and real values, which indicates that the model could quickly and accurately predict the moisture content of potato during ultrasonic enhanced far-infrared radiation drying process.
Publication Date
2-28-2019
First Page
123
Last Page
128,152
DOI
10.13652/j.issn.1003-5788.2019.02.024
Recommended Citation
Huihan, XI; Yunhong, LIU; Qi, WANG; Huiyang, LI; Gongwei, LI; and Lanxin, ZHAO
(2019)
"Drying characteristics and neural network model of ultrasoundstrengthened far-infrared radiation drying on potato,"
Food and Machinery: Vol. 35:
Iss.
2, Article 24.
DOI: 10.13652/j.issn.1003-5788.2019.02.024
Available at:
https://www.ifoodmm.cn/journal/vol35/iss2/24
References
[1] SHEWRY P R. Tuber storage proteins[J]. Annals of Botany, 2003, 91(7): 755-769.
[2] 吕巨智, 染和, 姜建初. 马铃薯的营养成分及保健价值[J]. 中国食物与营养, 2009(3): 51-52.
[3] 木泰华, 李鹏高. 马铃薯中生物活性成分及其功能[J]. 食品科学, 2016, 37(19): 269-276.
[4] FRAS A, CLEMENTE G, MULET A. Potato shrinkage during hot air drying[J]. Food Science and Technology International, 2010, 16(4): 337-41.
[5] FAISAL S, TABASSUM R, KUMAR V. Performance evaluation and process optimization of potato drying using hot air oven[J]. Journal of Food Processing & Technology, 2013, 4(10): 273-281.
[6] 易婕, 刘云宏, 李海登, 等. 紫薯远红外辐射干燥及品质特性[J]. 食品科学, 2018, 39(7): 160-167.
[7] 万江静, 郑霞, 高振江, 等. 红枣片远红外辐射干燥的干燥特性及VC变化[J]. 食品工业科技, 2016, 37(8): 110-115.
[8] TOGRUL H. Suitable drying model for infrared drying of carrot[J]. Journal of Food Engineering, 2006, 77(3): 610-619.
[9] 潘永康, 王喜忠, 刘相东. 现代干燥技术[M]. 北京: 化学工业出版社, 2007: 549-582.
[10] NATHAKARANAKULE A, JAIBOON P, SOPONRONNARIT S. Far-infrared radiation assisted drying of longan fruit[J]. Journal of Food Engineering, 2010, 170: 108-118.
[11] CARCEL J A, GARCIA-PEREZ J V, RIERA E, et al. Influence of high-intensity ultrasound on drying kinetics of persimmon[J]. Drying Technology, 2007, 25(1): 185-193.
[12] OZUNA C, ALVAREZ-ARENAS T G, RIERA E, et al. Influence of material structure on air-borne ultrasonic application in drying[J]. Ultrasonics Sonochemistry, 2014, 21(3): 1 235-1 243.
[13] FERNANDES F A N, RODRIGUES S, GARCIA-PEREZ J V, et al. Effects of ultrasound-assisted air-drying on vitamins and carotenoids of cherry tomatoes[J]. Drying Technology, 2016, 34(8): 986-996.
[14] LIU Yun-hong, SUN Yue, MIAO Shuai, et al. Drying characteristic of ultrasound assisted hot air drying of Flos Lonicerae[J]. Journal of Food Science and Technology, 2015, 52(8): 4 955-4 964.
[15] SCHSSLER K, JGER H, KNORR D. Novel contact ultrasound system for the accelerated freeze-drying of vegetables[J]. Innovative Food Science & Emerging Technolo-gies, 2012, 16(39): 113-120.
[16] 张京平, 王会. 神经网络和线性回归在苹果含水率预测中的应用[J]. 农业机械学报, 2008, 39(2): 198-200.
[17] 彭桂兰, 吴文福, 陈晓光, 等. 萝卜丝薄层干燥试验及其数学模型的建立[J]. 农业机械学报, 2005, 36(3): 79-81.
[18] POONNOY P, TANSAKUL A, CHINNAN M. Artificial neural network modeling for temperature and moisture content prediction in tomato slices undergoing microwave-vacuum drying[J]. Journal of Food Science, 2010, 72(1): 42-47.
[19] NADIANM H, RAFIEE S, AGHBASHLO M, et al. Continuous real-time monitoring and neural network modeling of apple slices color changes during hot air drying[J]. Food & Bioproducts Processing, 2015, 94: 263-274.
[20] 白竣文, 周存山, 蔡健荣, 等. 南瓜片真空脉动干燥特性及含水率预测[J]. 农业工程学报, 2017, 33(17): 290-297.
[21] 刘云宏, 李晓芳, 苗帅, 等. 南瓜片超声-远红外辐射干燥特性及微观结构[J]. 农业工程学报, 2016, 32(10): 277-286.
[22] KEK S P, CHIN N L, YUSOF Y A. Direct and indirect power ultrasound assisted pre-osmotic treatments in convective drying of guava slices[J]. Food & Bioproducts Processing, 2013, 91(4): 495-506.
[23] CORREA J L G, BRAGE A M P, HOCHHEIM M, et al. The influence of ethanol on the convective drying of unripe, ripe, and overripe bananas[J]. Drying Technology, 2012, 30(8): 817-826.
[24] CHEMAT F, ZILLE HUMA, KHAN M K. Applications of ultrasound in food technology: Processing, preservation and extraction[J]. Ultrasonics Sonochemistry, 2011, 18(4): 813-835.
[25] GALLEGO-JUAREZ J A, RIERA E, BLANCO S D F, et al. Application of high-power ultrasound for dehydration of vegetable: processes and devices[J]. Drying Technology, 2007, 25(11): 1 893-1 901.
[26] ORTUO C, PREZ-MUNUERA I, PUIG A, et al. Influence of power ultrasound application on mass transport and microstructure of orange peel during hot air drying[J]. Physics Procedia, 2010, 3(1): 153-159.
[27] SHARMA G P, VERMA R C, PATHARE P B. Thin-layer infrared radiation drying of onion slices[J]. Journal of Food Engineering, 2005, 67(3): 361-366.
[28] 葛哲学. 神经网络理论与MATLAB R2007实现[M]. 北京: 电子工业出版社, 2007: 136-141.
[29] 林喜娜, 王相友, 丁莹. 双孢蘑菇远红外干燥神经网络预测模型建立[J]. 农业机械学报, 2010, 41(5): 110-114.
[30] 陆琼瑜, 童学锋. BP算法改进的研究[J]. 计算机工程与设计, 2007, 28(3): 648-650.