English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Optimization of fluidized bed drying of sesame seeds was done by response surface methodology (RSM) and genetic algorithms (GA). Effect of drying parameters (drying temperature (40, 50, 60°C), drying time (60, 120, 180 min), air velocity (1, 1.5, 2 m/s) and bed depth of dryer (1–3 cm) was investigated based on the quality attributes of dried seeds. These factors were optimized with respect to the moisture ratio, color indices, and texture parameters (hardness and fracturability). The obtained models showed very well fitness with experimental data. The coefficients of resulting models with RSM were further optimized using GA. It was revealed that GA-optimized models have better fitness with the experimental results than RSM models. Our results suggest that sesame seed dried in 40–45°C for 115–120 min with 1 m/s air velocity had the lowest moisture content and color changes and the best texture.

Optimization of Closed-Cycle Fluidized Bed Drying of Sesame Seeds Using Response Surface Methodology and Genetic Algorithms