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Adaptive neuro fuzzy inference system modeling of Synsepalum dulcificum L. drying characteristics and sensitivity analysis of the drying factors

Scientific reports, 2022-08, Vol.12 (1), p.13261-13261, Article 13261 [Peer Reviewed Journal]

The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2022 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-022-17705-y ;PMID: 35918406

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  • Title:
    Adaptive neuro fuzzy inference system modeling of Synsepalum dulcificum L. drying characteristics and sensitivity analysis of the drying factors
  • Author: Adeyi, Oladayo ; Adeyi, Abiola John ; Oke, Emmanuel Olusola ; Ajayi, Oluwaseun Kayode ; Oyelami, Seun ; Otolorin, John Adebayo ; Areghan, Sylvester E ; Isola, Bose Folashade
  • Subjects: Developing countries ; Drying ; Energy consumption ; Fruits ; LDCs ; Sensitivity analysis ; Synsepalum dulcificum
  • Is Part Of: Scientific reports, 2022-08, Vol.12 (1), p.13261-13261, Article 13261
  • Description: 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 2 /s, 22.73 kWh and 113.64 kWh/kg, respectively at 50 °C drying time, with lowest activation energy of 28.8589 kJ/mol. The 3 min blanched MBF had the lowest drying time, highest EMD, lowest total and specific energy consumption of 130 min, 2.5607 E−08 m 2 /s, 7.47 kWh and 37 kWh/kg, respectively at 70 °C drying temperature. The 5 min blanched MBF had the highest activation energy of 37.4808 kJ/mol. Amongst others, 3—gbellmf—38 epoch ANFIS structure had the highest modeling and prediction efficiency (R 2  = 0.9931). The moisture ratio variability was most sensitive to drying time at individual factor level, and drying time cum pretreatment at interactive factors level. In conclusion, pretreatment significantly reduced the drying time and energy consumption of MBF. Refined ANFIS structure modeled and predicted the drying process efficiently, and drying time contributed most significantly to the moisture ratio variability of MBF.
  • Publisher: London: Nature Publishing Group
  • Language: English
  • Identifier: ISSN: 2045-2322
    EISSN: 2045-2322
    DOI: 10.1038/s41598-022-17705-y
    PMID: 35918406
  • Source: PubMed Central
    ProQuest Central
    DOAJ Directory of Open Access Journals
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