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PROJECT TOPIC: STATISTICAL MODELLING AND OPTIMIZATION OF THE DRYING CHARACTERISTICS OF MUSA PARADISIACA (UNRIPE PLANTAIN)

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CHAPTER ONE

INTRODUCTION

1.1. BACKGROUND OF STUDY

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.


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