Application of adaptive neuro-fuzzy inference system to estimate mass transfer during convective drying of microwave-treated quinoa sprouts

Document Type : Research Article

Authors

1 MSc Student, Department of Food Science and Technology, Faculty of Food Industry, Bu-Ali Sina University, Hamedan, Iran

2 Associate Professor, Department of Food Science and Technology, Faculty of Food Industry, Bu-Ali Sina University, Hamedan, Iran.

Abstract

Adaptive neuro-fuzzy inference system (ANFIS) is a new method for modeling and study of mass and heat transfer kinetics during food processing. This study examined the effects of microwave treatment time on the moisture loss rate, effective moisture diffusivity coefficient, and rehydration of quinoa sprouts, and the mass transfer rate was modeled using kinetic models and ANFIS. To apply pretreatment, quinoa sprouts were placed in the microwave device for 0, 30, 60, and 90 s, and after leaving from the device, they were dried in a hot air dryer. The results of this study show that microwave pretreatment for 30 s increases the moisture removal rate, increases the effective moisture diffusivity coefficient, and reduces the drying time of fresh quinoa sprouts. With microwave pretreatment of quinoa sprouts for 30 s, it was observed that the effective moisture diffusivity coefficient increased significantly from 5.73×10-11 m2s-1 to 10.49×10-11 m2s-1 (p<0.05). Based on the results obtained from the section on investigating different kinetic models, the use of a logarithmic kinetic model is recommended to investigate the drying process of quinoa sprouts. With microwave pretreatment of quinoa sprouts for 30 s, it was observed that the rehydration of dried sprouts significantly increased from 196.27% to 253.86% (p<0.05). The overall structure of the ANFIS network in this study includes two inputs (microwave pretreatment time and heating time), 20 input membership functions, 10 rules in the middle layer, 10 output membership functions, and one output response (moisture loss of quinoa sprouts). The results of the ANFIS showed that using the optimal ANFIS structure, the moisture loss percentage of microwave-treated quinoa sprouts during convective drying can be predicted with high accuracy. In general, the appropriate condition for drying fresh quinoa sprouts is a 30 s microwave pretreatment followed by the use of a convection dryer.

Graphical Abstract

Application of adaptive neuro-fuzzy inference system to estimate mass transfer during convective drying of microwave-treated quinoa sprouts

Highlights

  • پیش‌تیمار مایکروویو به مدت 30 ثانیه باعث افزایش سرعت خروج رطوبت، افزایش ضریب نفوذ مؤثر رطوبت و کاهش زمان خشک‌کردن جوانه‌های تازه کینوا شد.
  • مدل لگاریتمی برازش خوبی با داده‌های آزمایشگاهی خشک شدن جوانه‌های کینوا داشت.
  • تابع عضویت گاوسی برای مدل‌سازی داده‌های این پژوهش مناسب بود و نتایج خوبی هم هنگام استفاده از این تابع به دست آمد.
  • روش مدل‌سازی انفیس افت رطوبت جوانه‌های کینوا را با خطای پایین و ضریب تبیین حدود 99/0 پیش‌بینی کرد.

Keywords

Main Subjects

References

 
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Innovative Food Technologies
Volume 11, Issue 4
August 2024
Pages 356-372

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History

  • Receive Date: 08 February 2025
  • Revise Date: 27 February 2025
  • Accept Date: 03 March 2025

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