ArticleScientific reports2022
Adaptive neuro fuzzy inference system modeling of Synsepalum dulcificum L. drying characteristics and sensitivity analysis of the drying factors.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 10 citations in OpenAlex.
- Pretreatment-Driven Modulation of Green Mango Drying: Kinetics, Energy Consumption, Techno-Functionality, and Environmental Sustainability.Food science & nutrition · 2026Article
- Data-driven intelligent modeling, optimization, and global sensitivity analysis of a xanthan gum biosynthesis process.Heliyon · 2024Article
- Drying kinetics and thermo-environmental analysis of a PV-operated tracking indirect solar dryer for tomato slices.PloS one · 2024Article
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Authors and funding
8 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The requirement for easily adoptable technology for fruit preservation in developing countries is paramount. This study investigated the effect of pre-treatment (warm water blanching time-3, 5 and 10 min at 60 °C) and drying temperature (50, 60 and 70 °C) on drying mechanisms of convectively dried Synsepalum dulcificum (miracle berry fruit-MBF) fruit. Refined Adaptive Neuro Fuzzy Inference System (ANFIS) was utilized to model the effect and establish the sensitivity of drying factors on the moisture ratio variability of MBF. Unblanched MBF had the longest drying time, lowest effective moisture diffusivity (EMD), highest total and specific energy consumption of 530 min, 5.1052 E-09 m
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