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  3. Modeling the kinetics of tea drying using artificial neural networks

Modeling the kinetics of tea drying using artificial neural networks

Number of pages: 96 File Format: word File Code: 31775
Year: 2013 University Degree: Master's degree Category: Chemical - Petrochemical Engineering
Tags/Keywords: Advance publication - Artificial neural networks - Drying tea leaves - Kinetic modeling - Lunberg's algorithm - tea - to dry
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  • Summary of Modeling the kinetics of tea drying using artificial neural networks

    Dissertation

    Master's degree

    Department: Chemical Engineering

    Abstract

    Tea is one of the most popular drinks among the people of the world, especially in Iran. The reason for drying tea leaves is essential for long-term storage. In this research, a tea leaf and a pile of it were examined and dried. Green tea leaves were dried in the temperature range of 35 to 55 degrees Celsius and the inlet air velocities of 0.5 and 0.7 meters per second and the time period of 0 to 140 minutes in a laboratory fixed bed drying process. For this purpose, 4 samples were considered for each temperature. and the effect of parameters such as temperature and speed on the drying rate has been shown by drawing graphs. Then the tea drying process has been modeled by neural networks with four input vectors (time, temperature, speed and humidity) and one output vector (moisture ratio). This procedure has also been done for a mass of tea. The results obtained from the network were compared with experimental data. L?nberg-Marquardt and sigmoid tangent activation function were obtained with four input neurons and eleven neurons in the hidden layer and one output neuron, and the average relative error percentage, coefficient of determination, and mean squared error are 1.30, 0.9998, and 0.000084, respectively, and the best result for drying a mass of tea by the feed back propagation neural network with four input neurons and twenty neurons in the hidden layer and one The output and average relative error percentage and coefficient of determination and mean squared error and mean squared error were obtained respectively 5.42, 0.9996, 0.000082 and 0.000170 respectively, which shows the high accuracy of the neural network. and the predecessor, Lunberg-Marquardt Algorithm

     

    1-1 Introduction:

           Agricultural products are produced in large quantities but are not immediately consumed, however, many of these products can be preserved by using special processes. One of these methods is drying. .]21[

            Drying is the oldest method to prevent food spoilage. Drying is a process to increase the useful life of agricultural products without losing the nutritional properties before consumption. Drying is defined as a practical method of preservation on an industrial scale in order to minimize biochemical, chemical and microbiological spoilage by reducing the amount of water and water activity of materials. In the drying process, the water from inside the food is transferred to the surface of the material by air, and from there it is transferred to the air stream by displacement.]21,22[

           The substance that is studied in this research is tea. Tea is the best drink after water. Nowadays, brewed tea is one of the most popular non-alcoholic drinks in the world and its consumption is almost equal to It is used for coffee (café).]23[

           Tea has a lot of nutritional value because, in addition to caffeine and oxidized polyphenols, it also contains some protein substances and carbohydrates, and for this reason, the real calorific value of a cup of tea is about 4 kilocalories (170 grams). green, black and semi-fermented tea]5 [

            The consumption of theanine in tea is effective in reducing high blood pressure. Tea is a Chinese word and in the Southern Chinese dialect it is pronounced chai and it entered the Persian language with the same pronunciation as chai. In the Northern Chinese dialect it is pronounced t and its height sometimes reaches 8 meters.Tea is almost fat-free and has a slightly bitter taste, and its most important properties are anti-depressant, anti-blood sugar, anti-bacterial, anti-cancer, anti-viral, heart tonic, liver protector, blood pressure reducer, blood fat reducer, triglyceride reducer and tooth decay prevention [4] [

    1-2 Its history Tea

               According to the international laws, herbal nomenclature, the correct scientific name of tea is Camellia sinen sis, thus all types of tea were considered to belong to one species in which two varieties [1] were known as Chinese tea, following these actions Kitamura in 1950 called the Chinese variety Camellia sinen sis Var sinensis and the Assamese variety Camellia sinensis Var assamia. The things cultivated for tea production include Assamese tea, Chinese tea, and Cambodian tea.]1 [

           Tea has been used in China since ancient times and its fame is towards this country. Tea has been known in China before the history of Christ, the story of the accidental discovery of tea is as follows: once an ancient scholar was boiling water for his afternoon meal, while putting firewood (branches of a tea plant) into the fire, some of the leaves of the branch fell into the water container. The discovery was passed from hand to hand until it became popular all over the country. For the first time by King Long in the 4th century, the medicinal properties of this plant were discovered and investigated. At first, tea was not popular among the common people and was used as a kind of medicine in the upper classes of society. It was transferred from the upper classes to the common people. The world's annual consumption is about four million tons, of which 70% is black tea and 30% is green tea. [5] [

    1-3 botanical features

           Tea is a plant from the Nahandangan branch [2], a base and from the dicotyledons and order Partial and from the family Thyaceae and the genus Camellia, indestructible and evergreen, which in its natural state is diploid. Tea grows in areas with warm weather, from this point of view, tea can be considered a tropical plant in terms of its adaptability to the climate. Tea, which is called tea in English and chai in Chinese, is in the form of a tree or shrub and is specific to tropical regions or its surroundings. The tea flower shown in Figure 1-2 is single or double and sometimes in the form of Groups of five are seen. The color of the flowers is white and the calyx is shiny and has 5-7 sepals. The petals are 5-7 in number and are oval and convex outward and are connected at the base with a stamen. There are many stamens and ovaries.

    Tea is one of the most popular drinks amount in the world especially in Iran because of this drying tea leaves for a long period of storage is required. In this research both a tea leaf and bulk of tea is under investigation and drying process. Tea green leaves in air temperature range from 35 to 55 degrees Celsius and input air velocities 0.5 and 0.7 meters per second and time range 0 to 140 minutes were dried in an experimental dryer process. For this purpose, four samples were considered for each temperature. In each experiment, the weight of samples has been recorded continuously during the drying process until the mass change of samples becomes zero. 

     

    The kinetic of drying tea is investigated and the effect of such parameters like temperature and velocity on the rate of drying is shown by drawing some graphs. Then the process of drying tea by neural network method with four input vector (time, temperature, velocity and moisture) and one output vector (moisture ratio) has been modeled. This method is also done for an amount of tea. The obtained results of neural network were compared with the experimental data.

  • Contents & References of Modeling the kinetics of tea drying using artificial neural networks

    List:

    List of tables. Botanical characteristics. 4

    1-4 tea ingredients. 5

    1-5 How to cultivate tea in Iran. 5

    1-6 Cultivable tea numbers in Iran. 6

    1-7 Tea planting.. 6

    1-8 Effective factors in tea plant growth. 6

    1-8-1 Temperature. 6

    1-8-2 light..7

    1-8-3 amount of water..7

    1-8-4 fertilizer..7

    1-9 harvest (Chinese leaf). 7

    1-9-1 types of harvest (Chinese). 9

    1-9-2 length of harvest (Chinese leaf period). 9

    1-10 tips for having good tea. 11

    1-11 drying. 13

    1-11-1 types of tea according to drying. 14

    1-11-2 tea production methods. 15

    1-11-3 stages of tea drying in the factory. 16

    1-11-3-1 plus. 16

    1-11-3-2 rubbing.18

    1-11-3-3 fermentation.19

    1-11-3-4 drying.19

    1-12 how to work with a laboratory dryer.24

    1-13 artificial neural network.26

    1-14 statement of the problem.27

    15-1 research objectives.27

    16-1 steps of research.28

    1-17 research structure.29

    Chapter two: literature and research background 30

    2-1 research background.31

    Chapter three: method Research 36 3-1 Introduction 37 3-2 History of Artificial Neural Networks 37 3-3 Advantages of using neural networks 40 3-4 Multilayer neural network 41 3-4-1-1 Error Backpropagation Algorithm 42

    3-4-2 Modeling tea drying by perceptron neural network.44

    3-4-2-1 Selection of input data to the network.45

    3-4-2-2 Neural network configuration.45

    3-4-3 Activation functions.48

    3-4-4 Topology.49

    3-4-5 Lunberg-Marquardt algorithm method 49

    3-5 Review of network performance. 49 3-6 Summary..50

    Chapter 4: Calculations and research findings 52

    4-1 Introduction..53

    4-2 Effect of variables on drying. 53

    4-3 Results of modeling by forward and forward neural network.63

    4-4 Summary..84

    Chapter Five: Conclusion and suggestions 85

    5-1 Introduction..86

    5-2 Research results.86

    5-3 Suggestions for research Atti. 87. References: 88. English abstract: 93. Source: Dr. Moazzam Hasanpour Asil, "Tea making and tea technology", Gilan University Publications, (1377) [2] Laurent Faust, Basics. Neural Networks, Structures, Algorithms, Applications" Nass Scientific and Cultural Institute, (2013) 3. Hasan Pehlvanzadeh, "Drying, Principles of Application and Design" (by Stramilo Vacoder), Publications of Tarbiat Modares University, Tehran (2014) 4. Rosita Salari, "Comparison of the Physicochemical Characteristics of Three Main Types of Imported Tea Available in Mashhad during 1388" Scientific Journal, Food Science and Technology Research/Year 2/Number 2/Autumn (1389)

    ]5["Dryer Design" Thesis of Gilan University (1378)

    ] 6[Reza Amiri Chaijan, Mohammad Hadi Khosh-Madara, Gholam Ali Montazer, Saeed Minaei and Mohammad Reza Alizadeh "Estimation of Rice Conversion Coefficient Using Artificial Neural Networks Making the fluid bed shine" Journal of Agricultural Sciences and Arts and Natural Resources, Year 13, Number 48, (1388)

    ]7 [Mohammed Sharifi, Shahin Rafi, Alireza Kayhan, Mahmoudamid, "Simulation of the thin bed drying kinetic model of Thomson variety orange using artificial neural networks", Quarterly Journal of Food Science and Industry, (1389)

    ]8 [Mohsen Mukhtaryan, Fatemeh Koshki, "Estimating tomato drying parameters with the help of artificial neural networks" and the publicationEstimation of tomato drying parameters with the help of artificial neural networks" and Journal of Research and Innovation in Food Sciences and Industries, (1391)

    ]9 [Amiri Sofi, Mohammad Reza; Mohabi, Mohbet "Mass transfer modeling during the osmotic drying process of potatoes using artificial neural networks", Khorasan Razavi Food Sciences and Industries, (1387)

    ] 10 [Reza Rai Networks Nervous: A new approach in management decisions" Madras, Volume 5, Number 2, (2009) pp. 133-154 [p>

    ]11 [Hossein Nabizadeh "Algorithm and programming languages, reasoning tools, network

    ] 12 [Bromand Salahi, Seyed Asad Hosseini, Hossein Shayghi, Behrouz Sobhani "Prediction of maximum temperatures using "Artificial Neural Network Model" Geographical Research Quarterly 794(1384)

    ]13 [Fariba Esfandiari Dar Abad, Seyed Asad Hosseini, Mohammad Azadi Mobaraki, Zahra Hejazizadeh "Prediction of average monthly temperature of Sanandaj synoptic station using multilayer perceptron neural network model (MLPGeography (Quarterly Journal of the Iranian Geographical Society)) new volume, year 8, no. 27, Winter (1389)

    ] 14 [Reza Amiri Chaijan, Mohammad Hadi Khosh-Madara" Prediction of qualitative variables, energy and kinetics of paddy drying under fluidized bed conditions with the help of HYPS Diffusion Network" 5th National Congress of Agricultural Machinery and Mechanization Engineering 588 (1388)

    ] 15 [Reza Amiri Chaijan, Mohammad Hadi Khosh-Madara, Jaafar Amiri Peryan. "Estimating variables and investigating the importance of effective factors in the drying process of paddy fixed bed with the help of artificial neural networks", Journal of Food Industry Research, (1388)

    ]16 [Syed Mohammad Taghi al-Madrasi, Mohammad Reza Taban, Javad Abdi "Using neural network to increase the accuracy of single-frequency receivers from the elimination of the SA effect" 9th Conference on Power Distribution Networks (1383)

    ]17 [Mehsa Rafii "Artificial Neural Networks" Iran Doc, Winter (1385)

    ]18 [Sohrab Saeb Taheri, Aydin Farjid Or, Seyed Ali Seyed Salehi "Comparison of gradient-based methods for the training of dynamic basinapse artificial neural network" Iran Telecommunication Research Center, (1384)

    ] 19 [Ruholah Rezaei Arshad, Gholamabas Sayad, Masoud Mazloum, Mehdi Sharafav Alireza Jafaranjadi "Comparison of Artificial Neural Network and Regression Methods for Predicting Hydraulic Conductivity of Saturated Soils in Khuzestan Province" Journal of Agricultural Science and Technology and Natural Resources, Water and Soil Sciences / Year 16 / Number 60 / Summer (2013)

    ] 20 [Hasan Taherkhani, Amir Ebrahimi Moghadam "Prediction of Fatigue Life of Asphalt Mixes Using Neural Networks. Transportation Engineering, 4th Year First issue, autumn (2011) [21] Gulsah Cakmak, Cengiz Y?ld?z, "The prediction of seedy grape drying rate using a neural network method", Computers and Electronics in Agriculture 75 132-138 (2011) [22] Kamyar Movagharnejhad, Maryam Nikzad "Modeling of tomato drying using artificial neural network "Computers and Electronics in Agriculture 5978-85(2007)

    [23] Yongsheng Ding, Hong Yu, Shifen Mou"Direct determination of free amino acids and sugars in green tea by anion-exchange chromatography with integrated pulsed amperometric detection", journal of chromatography A, 982237-244.(2002)

    [24] P.C. Panchariya, D. Popovic, A.L. Sharma "Thin-layer modeling of black tea drying process", Journal of Food Engineering, 52 349-357(2002) [25] M. Khanali, Sh. Rafiee, A. Jafari, S.H. Hashemabadi and A. Banisharif. "Mathematical modeling of fluidized bed drying of rough rice (Oryza sativa L.) grain" Journal of Agricultural Technology Vol. 8(3): 795-810(2012)

    [26]E. Akpinar, A. Midilli, Y. Bicer "Single layer drying behavior of potato slices in a convective cyclone dryer and mathematical modeling" Energy Conversion and Management 44 1689–1705(2003)

    [27] Hossein Ghanadzadeh Gilani, PhD. Katia Ghanadzadeh Samper. Reza Khodaparast Haghi ''Advanced process control and simulation for chemical engineers'', Taylor & Francis group (2013)

    [28] I. Farkas, P. Reme´nyi & A.b. Biro, Modeling aspects of grain drying with aneural network. Computers and Electronics in Agriculture, 29, 99-113, (2000)

    [29] K.Erenturk, S.Erenterk, L.G.Tabil,"A comparative study for the estimation of dynamical drying behavior of Echinacea angustifolia: regression analysis and neural network" Computer Electron. Agriculture, 45, 71-90, (2004)

    [30] M.R. Islam, S. S. Sabalani and A.

Modeling the kinetics of tea drying using artificial neural networks
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