Results 241 to 250 of about 340,858 (296)

Ferulic acid‐impregnated sodium alginate–pectin biopolymer film for active packaging and shelf‐life extension of potato chips

open access: yesJournal of the Science of Food and Agriculture, EarlyView.
Abstract BACKGROUND This study explores the development of active films incorporating ferulic acid (FA), a natural antioxidant, at concentrations of 0 (F1), 2.5 (F2), and 5 g L−1 (F3) into sodium alginate (SA; 13 g kg−1) and pectin (P; 10 g kg−1) matrix.
Shaik Sadiya   +4 more
wiley   +1 more source

Black flesh disorder in mango: a chilling injury symptom increased by early harvest and low storage temperature and reduced by 1‐methylcyclopropene

open access: yesJournal of the Science of Food and Agriculture, EarlyView.
Abstract BACKGROUND Black flesh (BF) is an internal disorder in mango, characterized by the development of dark brown to black pigmentation in the inner mesocarp tissue during storage or transport. This study investigated the effects of harvest maturity, low storage or low transport temperatures, and 1‐methylcyclopropene (1‐MCP) on mango fruit ...
Bruna Parente de Carvalho Pires   +8 more
wiley   +1 more source

Probiotic fermented goat milk incorporated with blackberry (Rubus sp.): A novel functional food product

open access: yesJournal of the Science of Food and Agriculture, EarlyView.
Abstract BACKGROUND This study created functional fermented goat milk by adding blackberry pulp and probiotics (Lactobacillus acidophilus LA‐5 and Bifidobacterium animalis subsp. lactis Bb‐12). The preparation involved two variations of fermented goat milk with blackberry (Rubus sp.), distinguished by the absence (fermented goat milk, FGM) or inclusion
Bibiana Bittencourt Bicca   +6 more
wiley   +1 more source

Advancing forward osmosis predictions: A deep learning‐based surrogate modeling approach

open access: yesJournal of the Science of Food and Agriculture, EarlyView.
Abstract BACKGROUND This study presents a deep learning‐based surrogate model for the rapid and accurate prediction of forward osmosis (FO) performance under diverse operating conditions. To assess the applicability of data‐driven approaches, several machine learning models – decision tree, random forest, support vector machine, and deep neural network
Hyeon Woo Park, Woo‐Ju Kim
wiley   +1 more source

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