Dehydration modeling of Cordyceps militaris in mid-infrared-assisted convection drying system: Using low-field nuclear magnetic resonance with the aid of ELM and PLSR

Abstract

The changes in moisture content and shrinkage ratio of Cordyceps militaris during mid-infrared-assisted convection drying (MIRCD) with different drying temperatures (40, 50, and 60 °C) and velocities of airflow (1 and 2 ms⁻¹) were studied. The relationship between low-field nuclear magnetic resonance (LF-NMR) information and moisture content/shrinkage ratio was modeled using partial least-squares regression (PLSR) and extreme learning machine (ELM). Results indicated that the influence of drying temperature was more pronounced than that of air flow velocity. Both types of models showed good predictive ability with R²>0.90. The ELM models exhibited superior predictive performance than that of the PLSR models.

Keywords:

• Cordyceps militaris
• dehydration modeling
• NMR
• extreme learning machine
• partial least-squares regression

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

We acknowledge the financial support from National Key R&D Program of China (Contract No. 2017YFD0400901), Jiangsu Province (China) Agricultural Innovation Project (Contract No. CX(17)2017), Jiangsu Province Key Laboratory Project of Advanced Food Manufacturing Equipment and Technology (No. FMZ201803), Jiangsu Province(China) “Collaborative Innovation Center for Food Safety and Quality Control” Industry Development Program, National First-class Discipline Program of Food Science and Technology (No. JUFSTR20180205), all of which enabled us to carry out this study.