Optimization of the drying of Cavendish banana (Musa acuminata Colla) for flour production

Date

4-2011

Degree

Bachelor of Science in Agricultural Engineering

Major Course

Major in Agricultural and Bio-Process Engineering

College

College of Engineering and Agro-Industrial Technology (CEAT)

Adviser/Committee Chair

Arnold R. Elepano

Committee Member

Engelbert K. Peralta, Edgardo V. Casas

Request Access

To request access of this material, please email the administrator at uscs-mainlib.uplb@up.edu.ph

Abstract

To maximize the efficiency of Cavendish banana flour production, one critical prerequisite is the optimization of the drying process. The optimum condition at which drying will occur was experimentally determined utilizing the Box and Behnken experimental design with drying air temperature (40°C, 50°C, 60°C), air flowrate (0.0212m³/s, 0.0318m³/s, 0.0424m³/s) and thickness of cut (3mm, 4mm, 5mm) as the independent variables. The responses observed were the final moisture content, drying rate, whiteness, particle size, milling ratio and sensory evaluation parameters that include color, aroma, texture and general acceptability. After performing Analysis of Variance (ANOVA), results revealed that drying temperature and thickness of cut significantly affected drying rate since high temperature means high capacity to remove moisture and thick material has comparatively more water holding capacity than thin material respectively. Temperature and air velocity also had significant effects on milling ratio, particle size, aroma, texture and general acceptability. High drying temperature results in brittleness of the product resulting to high milling ratio and consequently smaller particle size and finer texture. Superimposed contour plots of the responses significantly affected by the independent parameters displayed optimum values of 59.6°C air temperature, 2.1 m/s air velocity and 3.2mm thickness of cut with a 75, 5 and 6 percent error respectively when compared with the values calculated using statistical computations. The obtained values were then verified in another three(3) experimental runs. The predicted responses, with a desirability of 84.17% were compared to the responses obtained by validation runs giving a range of 0.25-16.50 percent error. Lastly, Page model best fits the data with an R² of 0.9996 in the form of :M-Me/Mo-Me=exp (-(0.008156)t¹⁻³⁹⁹⁵⁶⁷)

Language

English

LC Subject

Banana Flour

Location

UPLB College of Engineering and Agro-Industrial Technology (CEAT)

Call Number

LG 993.5 2011 A2 G37

Document Type

Thesis

This document is currently not available here.

Share

COinS