Thesis Abstract

Abstract
This research project focuses on the statistical modeling and optimization of the drying characteristics of Musa paradisiaca, specifically unripe plantain. Drying is a critical process in food preservation and the quality of the dried product is influenced by various factors such as drying temperature, air velocity, and slice thickness. In this study, an experimental investigation was conducted to analyze the drying kinetics of unripe plantain slices using a convective hot air dryer. The experimental design was based on Response Surface Methodology (RSM) to optimize the drying process and to determine the effects of independent variables on the drying characteristics. The drying experiments were carried out at different combinations of air temperature (50-70°C), air velocity (1-3 m/s), and slice thickness (3-7 mm). The moisture content of the plantain slices was measured at regular intervals until a constant weight was achieved. Statistical analysis of the experimental data was performed using Design Expert software to develop mathematical models that describe the drying kinetics of unripe plantain. The models were validated using statistical tests to assess their accuracy in predicting the moisture content of the dried product. A quadratic polynomial model was found to best fit the experimental data, indicating a good correlation between the independent variables and the drying characteristics. Furthermore, the optimized drying conditions were determined through numerical optimization techniques to minimize the drying time and maximize the drying efficiency. The results showed that a drying temperature of 60°C, air velocity of 2 m/s, and slice thickness of 5 mm were the optimal conditions for drying unripe plantain slices. Under these conditions, the drying time was reduced significantly while maintaining the quality of the dried product. In conclusion, this research project demonstrates the application of statistical modeling and optimization techniques to analyze the drying characteristics of Musa paradisiaca (unripe plantain). The developed models provide valuable insights into the drying process and offer a systematic approach to optimize the drying conditions for improved efficiency and quality of the dried product. The findings of this study can be beneficial for food processors and researchers in the field of food engineering for the development of efficient drying processes for plantain and other agricultural products.

Thesis Overview

INTRODUCTION

Drying is probably the oldest and the most important method of
food preservation practiced by humans. This process improves the food
stability, since it reduces considerably the water and microbiological activity
of the material and minimizes physical and chemical changes during its storage.

Musa paradisiacal (unripe
plantain) is an important staple food in Central and West Africa, which along
with bananas provides 60 million people with 25% of their calories. According
to FAO, (2004), over 2.11 million metric tons of plantain is produced in
Nigeria annually. Plantain for local consumption, plays a role in food and
income security and has the potential to contribute to national food security
and reduce rural poverty.

Unripe
plantain has rich iron nutrient content (Aremu, et al., 1990). However, they
are highly perishable and subject to fast deteriorations, as their moisture
contents and high metabolic activity persist after harvest (Demirel, et al.,
2003).

Moreso, about 35-60%
post-harvest losses had been reported and attributed to lack of storage facilities
and inappropriate technologies for food processing. Air drying alone or
together with sun drying is largely used for preserving unripe plantain.
Besides helping preservation, drying adds value to plantain.

1.2
PROBLEM STATEMENT

Drying consists of a critical step
by reducing the water activity of the products being dried. Hot air drying of
agricultural products is one of the most popular preservation methods because
of its simplicity and low cost. Thin layer drying is a common method and widely
used for fruits and vegetables to prolong their shelf life.

However, drying of any food
substance is an energy intensive operation with grave industrial consequences,
and must be performed with optimal energy utilization.

This project work seeks to
ascertain the best thin layer model and the temperature and slice thickness
that optimizes time.

1.3.
OBJECTIVE OF STUDY

The objectives of this work are to;

Ascertain the type of thin-layer model that best fits the
moisture ratio/time data during the drying of unripe plantain.

To
determine the temperature and slice thickness that optimizes time (i.e. gives
the shortest drying time).

1.4
JUSTIFICATION

Production
of plantain is seasonal while consumption is all year round and therefore there
is the need to cut down on post-harvest losses by processing them into forms
with reduced moisture content.

This
agricultural product has high moisture content at harvest and therefore cannot
be preserved for more than some few days under ambient conditions of 20oC – 25oC (Chua, et al., 2001). This
post-harvest loss results in seasonal unavailability and limitations on the use
by urban populations. Plantain has however been having an increasing surplus
production since 2001 (Dankye, et al.,
2007). It is estimated that in 2015, there will be a surplus of about
852,000 Mt. This means that these surpluses have to be exported, processed or
go to waste.

A
reduction in moisture content potentially increases shelf life and hence
prevents excessive post-harvest loss and that drying is an alternative to
developing nations, where there is deterioration due to poor storage, weather
conditions and processing facilities

1.5
SCOPE OF STUDY

The
scope of this project work includes the following:

Using
the ten selected thin layer models to investigate the one that best fits the
data generated from drying of unripe plantain at specified temperatures, slice
thicknesses, and drying time.

Using
regression analysis to obtain the slice thickness and temperature for the
optimum (minimum) drying time.