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

The suitability of genetic algorithm as an optimization tool for freeze drying of mushroom has been explored. The optimized solution set obtained from genetic algorithm was compared to a derivative based goal attainment algorithm ( fgoalattain ) to identify the better optimizer. Regression models for quality parameters of freeze dried button mushrooms were developed and models with ≥ 85% correlation were selected and compiled into an objective function for optimization. Verified optimal solutions revealed that genetic algorithm was more proficient in optimizing physical quality parameters (rehydration and shrinkage ratio) as contrary to fgoalattain which optimized nutritional characteristics (ascorbic acid and protein) better. The ability of genetic algorithm for optimization from the perspective of a consumer was found to be better.

Application and comparison of genetic and mathematical optimizers for freeze-drying of mushrooms