2. OUTLINES
• Title page
• Introduction
• Introduction to Artificial neural network
• Statement of problem
• Aim and objective of the study
• Significance of study
• Why sun drying
• Materials used in the study
• Sample preparation
• Drying process (Experimental procedure)
• Why ANN
3. INTRODUCTION
Drying is a method employed to remove the water contents of any agricultural products thereby
prolonging the life-span of that products. It is a chemical engineering unit operation/processes. The major
aim associated with water removal in any agricultural products is to reduce microbial activities which at
the same time will prolong the life span of that product.
The aim of this work is to predict the drying parameter of afang leaves using artificial neural
network.
Afang (gnetum africanum) leaves are used as vegetable for soup and other health benefit
purposes. Afang is a good source of protein and is strong in essential and non-essential amino acids.
4. INTRODUCTION TO ANN
Artificial neural network is a machine learning method evolved from the idea of simulating
the human brain because of this artificial neural network is modeled on the concept of biological
neural network.
Artificial neural network has three major components namely: the nodes character, network
topology and learning rules. The smallest element of a network is the node were signals are received
and summed together before being applied to the transfer function to produce the output. A typical
ANN topology has three layers which are: input layer, hidden layer and output layer.
5. STATEMENT OF PROBLEM
The problem this research work will address is highlighted below:
• Constant deterioration of agricultural products.
• Loss of nutritional qualities of food products due to chemical and
enzymatic changes during processing.
• Suitable drier for a particular agricultural product.
6. AIM AND OBJECTIVE OF THE STUDY
This work will base on developing a mathematical model for
predicting drying parameter of afang.
• Will validate the model using experimental data.
• Will predict the drying behaviour using simulation model.
• Will compare the develop model with an existing model in terms of
the moisture content removal efficiency.
7. SIGNIFICANCE OF STUDY
This study will give an accurate understanding of the characteristic
behaviour of the water content in afang leaf during sun drying. Simulation and
description of the drying process under different drying condition will help
improve the quality of the final product.
8. LITERATURE REVIEW
• M.A. Ali et al. 2014
• Garavand et al. 2018
• Khawas et al. (2016
• Aktaş et al. 2015
9. WHY SUN DRYING?
Drying prolong the life span of any perishable agricultural products but it’s worth noting that factor’s
such as shape, size, surface area and drying method could influence the drying rate of that product.
In this work, sun will be use as method of drying because of it low capital cost, low running cost,
independence from fuel supplies and is not limited in terms of quantities of product to be dry. Just like every
other drying method, sun drying also has its own drawdown such as slow drying rate or attack from micro-
organism during but it’s worth noting that increasing the temperature of the drying device just to speed up the
drying rate in the case of afang leaves with it small size thickness may either charred or cause shrinkage of the
products which may lead to loss in nutritional value or change in colour of the product.
10. MATERIALS USED IN THE STUDY
The materials to be used in this study are;
• Afang leaves
• Mat
• Net
• Electronic weighing balance
• Stop Watch
• Thermometer etc.
11. SAMPLE PREPARATION
Sample will be collected from a near-by local market same day
after harvesting. After washing and removal of water, sample will be
chopped into piece before weighing to obtain the initial mass before
being transferred to an open field to be dried under direct sunlight.
12. SAMPLE PREPARATION
Sample will be collected from a near-by local market same
day after harvesting. After washing and removal of water,
sample will be chopped into piece before weighing to
obtain the initial mass before being transferred to an open
field to be dried under direct sunlight.
13. DRYING PROCESS (EXPERIMENTAL
PROCEDURE)
The drying experiment will be conducted at different temperature for each
drying interval. The temperature of the sun will be recorded for each day to know
the temperature variation. After drying for each day, sample will be weigh to obtain
its mass at that particular drying period.
This experimental procedure will continue sequentially till the particular drying
period at which the drying parameter is constant.
14. WHY ANN?
Empirical mathematical correlation are usually used to describe the drying behaviour of natural
materials . This correlations usually give very accurate results for each specific experiment. But the
equation is not valid for other conditions and there is no way to obtain a general equation for a range
of drying parameters. This problem may be avoided by use of analytical drying models but the final
result using analytical model are usually complicated. On this note, ANN will be use to predict the
drying parameters of afang due to it ability to accept data process its in the form of training and the
then bring out a simplified output which the user will understand.
