Optimization and Validation of Extrusion Process Parameters for the Sensory Characteristics of Extruded Aerial Yam and Soybean Flour Blends

The aim of this study was to optimize and validate the extrusion process parameters (barrel temperature, screw speed, and feed moisture) for the sensory properties (texture, taste, appearance, and aroma) of extrudates made from blends of soybean and aerial yam flours. Five levels of barrel temperature (95, 100, 105, 110, and 115 °C), screw speed (85, 100, 115, 130, and 145 rpm), and feed moisture (31, 33, 35, 37, and 39%) were employed in 20 runs of the response surface methodology (RSM), which was based on the Box-Behnken design with three variables. A single-screw extruder at the laboratory scale was used to carry out the extrusion procedure. A high regression coefficient (R2 ≥ 0.9) indicates that the models are useful for navigating the design space. Numerical optimization results indicated that the optimal extrusion process parameters - barrel temperature of 114.12 °C, screw speed of 100.56 rpm, and feed moisture of 38.02% - produced extrudates with optimal sensory property scores of 5.34 for texture, 4.91 for taste, 6.97 for appearance, and 5.80 for aroma, with a desirability of 0.943. The correlation between the predicted and experimental values yielded a high coefficient of determination, indicating a good correlation. The “Fit and Diagnostic Case” statistics showed a low range of deviations between the predicted and observed values for the sensory characteristics. Therefore, the generated quadratic model accurately predicts the sensory characteristics of aerial yam-soybean flour blends and is thus validated.

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Publication Details

Journal
Asian Journal of Science and Applied Technology
Published
2024-10-14
DOI
https://doi.org/10.70112/ajsat-2024.13.2.4246
Citations
4
Primary Topic
Food composition and properties
Type
article
Field-Weighted Citation Impact
1.24
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article

Optimization and Validation of Extrusion Process Parameters for the Sensory Characteristics of Extruded Aerial Yam and Soybean Flour Blends

P. C. Ojimelukwe, Enobong Okon Umoh, Madu Ofo Iwe
4 citations
Asian Journal of Science and Applied Technology
Food composition and properties
1.24
article

Optimization and Validation of Extrusion Process Parameters for the Sensory Characteristics of Extruded Aerial Yam and Soybean Flour Blends

P. C. Ojimelukwe, Enobong Okon Umoh, Madu Ofo Iwe
article en
4 citations

Abstract

The aim of this study was to optimize and validate the extrusion process parameters (barrel temperature, screw speed, and feed moisture) for the sensory properties (texture, taste, appearance, and aroma) of extrudates made from blends of soybean and aerial yam flours. Five levels of barrel temperature (95, 100, 105, 110, and 115 °C), screw speed (85, 100, 115, 130, and 145 rpm), and feed moisture (31, 33, 35, 37, and 39%) were employed in 20 runs of the response surface methodology (RSM), which was based on the Box-Behnken design with three variables. A single-screw extruder at the laboratory scale was used to carry out the extrusion procedure. A high regression coefficient (R2 ≥ 0.9) indicates that the models are useful for navigating the design space. Numerical optimization results indicated that the optimal extrusion process parameters - barrel temperature of 114.12 °C, screw speed of 100.56 rpm, and feed moisture of 38.02% - produced extrudates with optimal sensory property scores of 5.34 for texture, 4.91 for taste, 6.97 for appearance, and 5.80 for aroma, with a desirability of 0.943. The correlation between the predicted and experimental values yielded a high coefficient of determination, indicating a good correlation. The “Fit and Diagnostic Case” statistics showed a low range of deviations between the predicted and observed values for the sensory characteristics. Therefore, the generated quadratic model accurately predicts the sensory characteristics of aerial yam-soybean flour blends and is thus validated.

Asian Journal of Science and Applied TechnologyVol. 13(2)
Akwa Ibom State University (NG), Michael Okpara University of Agriculture (NG)
Openalex Percentile: Top 22%
Food composition and properties
1.24
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