id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
easat-7610	Raksuntorn, Nareenart ; Sirichokworrakit, Supatchalee ; Aukkanit, Nuntaporn ; Kularbphettong, Kunyanuth 	Machine learning-driven optimization of Riceberry donut formulations for high sensory acceptance and low calorie	2025	12	.pdf	application/pdf	4860	246	40	Employing the enhanced model, simulated recipes were generated by adjusting Riceberry flour (20- 35%), shortening (15-19g), and protein (2.6-3.0g), and the most effective formulation, consisting of 30% Riceberry flour, 15g of shortening, and 2.7g of protein, obtained a predicted Overall Liking score of 7.37 and 114.5 kcal per 30g serving. The incorporation of Riceberry flour in baked products, particularly in fried foods such as donuts, poses significant formulation difficulties.	cache/easat-7610.pdf	txt/easat-7610.txt