Enhancing drying performance of a forced-convection solar food dryer through multi-attribute decision-making

Abstract

This study applies Grey Relational Analysis (GRA) to optimize drying parameters for Chhurpi, a traditional Himalayan dairy product, by evaluating physicochemical and sensory attributes under varied temperature, airflow, and humidity conditions. Raw data for moisture content, protein, fat, ash, lactose, colour and appearance, flavour and taste, body and texture, overall acceptability, and hardness were normalized using “larger-the-better” and “smaller-the-better” models. Grey relational coefficients and grades were computed to rank eight treatments with and without pebble incorporation. Results identified Treatment T33 (no pebbles) and T4 (with pebbles) as most closely matching the ideal reference sequence. Regression analyses indicated a moderate inverse relationship between hardness and moisture (R² ? 0.5). These findings corroborate previous work on controlled-environment drying effects in dairy products and underscore the utility of GRA in multi-criteria food quality.