Statistical modelling and optimization of the drying characteristics of musa paradisiaca (unripe plantain) – complete project material | Blazingprojects Postgraduate Thesis
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Statistical modelling and optimization of the drying characteristics of musa paradisiaca (unripe plantain) – complete project material

 

Table Of Contents


Chapter ONE

INTRODUCTION

  • 1.1Introduction
  • 1.2Background of Study
  • 1.3Problem Statement
  • 1.4Objective of Study
  • 1.5Limitation of Study
  • 1.6Scope of Study
  • 1.7Significance of Study
  • 1.8Structure of the Research
  • 1.9Definition of Terms

Chapter TWO

LITERATURE REVIEW

  • 2.1Overview of Drying Process
  • 2.2Importance of Drying in Food Preservation
  • 2.3Factors Affecting Drying Characteristics
  • 2.4Mathematical Modelling of Drying Process
  • 2.5Optimization Techniques in Drying
  • 2.6Studies on Drying Characteristics of Musa Paradisiaca
  • 2.7Review of Statistical Modelling in Drying Studies
  • 2.8Comparative Analysis of Drying Techniques
  • 2.9Challenges in Drying Musa Paradisiaca
  • 2.10Summary of Literature Review

Chapter THREE

RESEARCH METHODOLOGY

  • 3.1Research Design
  • 3.2Selection of Research Method
  • 3.3Data Collection Methods
  • 3.4Sampling Techniques
  • 3.5Variables and Measurements
  • 3.6Data Analysis Procedures
  • 3.7Quality Control Measures
  • 3.8Ethical Considerations

Chapter FOUR

DATA PRESENTATION AND ANALYSIS

  • 4.1Overview of Research Findings
  • 4.2Analysis of Drying Characteristics of Musa Paradisiaca
  • 4.3Statistical Modelling Results
  • 4.4Optimization Results
  • 4.5Comparison with Previous Studies
  • 4.6Discussion on Factors Influencing Drying Process
  • 4.7Implications of Findings
  • 4.8Recommendations for Future Research

Chapter FIVE

SUMMARY, CONCLUSION AND RECOMMENDATIONS

  • 5.1Conclusion
  • 5.2Summary of Research
  • 5.3Contributions to Knowledge
  • 5.4Practical Implications
  • 5.5Areas for Further Exploration

Thesis Abstract

Statistical modelling and optimization of the drying characteristics of musa paradisiaca (unripe plantain) – Abstract
Drying is a crucial process in food preservation, affecting the quality, shelf life, and overall acceptability of the final product. In this study, the drying characteristics of musa paradisiaca (unripe plantain) were investigated using statistical modelling and optimization techniques. The study aimed to develop mathematical models to describe the drying kinetics of unripe plantain slices and to optimize the drying process for improved efficiency. The drying experiments were conducted using a convective hot air dryer at different temperatures (50°C, 60°C, and 70°C) and air velocities (1 m/s, 1.5 m/s, and 2 m/s). The moisture content of the samples was measured at regular intervals until a constant weight was achieved. The experimental data were fitted to various thin-layer drying models, including the Page, Henderson & Pabis, and Logarithmic models, using nonlinear regression analysis to determine the model with the best fit. The results showed that the drying rate increased with higher drying temperatures and air velocities. The Page model was found to best describe the drying kinetics of unripe plantain slices, with the highest coefficient of determination (R2) and the lowest root mean square error (RMSE) values compared to the other models tested. The effective moisture diffusivity was calculated using Fick's second law of diffusion and was found to increase with temperature. Response surface methodology (RSM) was employed to optimize the drying process by determining the optimum drying conditions that would result in the shortest drying time and the highest quality dried product. The effects of temperature and air velocity on the drying time and the quality attributes of the dried plantain slices were evaluated using a central composite design. The RSM analysis identified the optimal drying conditions as a temperature of 70°C and an air velocity of 2 m/s, which resulted in a predicted drying time of 4.5 hours and a moisture content of 10%. In conclusion, this study successfully developed mathematical models to describe the drying kinetics of musa paradisiaca (unripe plantain) slices and optimized the drying process using statistical techniques. The results provide valuable insights for improving the efficiency and quality of the drying process for unripe plantain, with potential applications in the food industry for producing high-quality dried plantain products.

Thesis Overview

<p><br><br>CHAPTER<br>ONE<br><br>INTRODUCTION<br><br>Drying is probably the oldest and the most important method of<br>food preservation practiced by humans. This process improves the food<br>stability, since it reduces considerably the water and microbiological activity<br>of the material and minimizes physical and chemical changes during its storage.<br><br>Musa paradisiacal (unripe<br>plantain) is an important staple food in Central and West Africa, which along<br>with bananas provides 60 million people with 25% of their calories. According<br>to FAO, (2004), over 2.11 million metric tons of plantain is produced in<br>Nigeria annually. Plantain for local consumption, plays a role in food and<br>income security and has the potential to contribute to national food security<br>and reduce rural poverty.<br><br>Unripe<br>plantain has rich iron nutrient content (Aremu, et al., 1990). However, they<br>are highly perishable and subject to fast deteriorations, as their moisture<br>contents and high metabolic activity persist after harvest (Demirel, et al.,<br>2003).<br><br>Moreso, about 35-60%<br>post-harvest losses had been reported and attributed to lack of storage facilities<br>and inappropriate technologies for food processing. Air drying alone or<br>together with sun drying is largely used for preserving unripe plantain.<br>Besides helping preservation, drying adds value to plantain.<br><br>1.2<br>PROBLEM STATEMENT<br><br>Drying consists of a critical step<br>by reducing the water activity of the products being dried. Hot air drying of<br>agricultural products is one of the most popular preservation methods because<br>of its simplicity and low cost. Thin layer drying is a common method and widely<br>used for fruits and vegetables to prolong their shelf life.<br><br>However, drying of any food<br>substance is an energy intensive operation with grave industrial consequences,<br>and must be performed with optimal energy utilization.<br><br>This project work seeks to<br>ascertain the best thin layer model and the temperature and slice thickness<br>that optimizes time.<br><br>1.3.<br>OBJECTIVE OF STUDY<br>The objectives of this work are to;<br><br>Ascertain the type of thin-layer model that best fits the<br>moisture ratio/time data during the drying of unripe plantain.<br><br>To<br>determine the temperature and slice thickness that optimizes time (i.e. gives<br>the shortest drying time).<br><br>1.4<br>JUSTIFICATION<br><br>Production<br>of plantain is seasonal while consumption is all year round and therefore there<br>is the need to cut down on post-harvest losses by processing them into forms<br>with reduced moisture content.<br><br>This<br>agricultural product has high moisture content at harvest and therefore cannot<br>be preserved for more than some few days under ambient conditions of 20oC – 25oC (Chua, et al., 2001). This<br>post-harvest loss results in seasonal unavailability and limitations on the use<br>by urban populations. Plantain has however been having an increasing surplus<br>production since 2001 (Dankye, et al.,<br>2007). It is estimated that in 2015, there will be a surplus of about<br>852,000 Mt. This means that these surpluses have to be exported, processed or<br>go to waste.<br><br>A<br>reduction in moisture content potentially increases shelf life and hence<br>prevents excessive post-harvest loss and that drying is an alternative to<br>developing nations, where there is deterioration due to poor storage, weather<br>conditions and processing facilities<br><br>1.5<br>SCOPE OF STUDY<br>The<br>scope of this project work includes the following:<br><br>Using<br>the ten selected thin layer models to investigate the one that best fits the<br>data generated from drying of unripe plantain at specified temperatures, slice<br>thicknesses, and drying time.<br><br>Using<br>regression analysis to obtain the slice thickness and temperature for the<br>optimum (minimum) drying time.<br><br>Get Complete Project Now »<br>Talk to us right now: (+234)906-451-7926 (Call/WhatsApp)<br><br>Share a Comment<br>Purchase Detail<br>Hello, we’re glad you stopped by, you can download the complete project materials to this project with Abstract, Chapters 1 – 5, References and Appendix (Questionaire, Charts, etc) for N5000 ($15) only,<br>Please call 08111770269 or +2348059541956 to place an order or use the whatsapp button below to chat us up.<br>Bank details are stated below.<br>Bank: UBA<br>Account No: 1021412898<br>Account Name: Starnet Innovations Limited<br></p>

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