Improving the properties and sensory acceptability of vegan chocolate formulated with oat milk and soy protein isolate by incorporating encapsulated strawberry extract

This study aimed to investigate the physicochemical properties, antioxidant activity, and organoleptic characteristics of vegan milk chocolate with various formulas. To achieve this objective, seven treatment formulas were used with different levels of OM and SPI, and ESE was added. The parameters analyzed included color, texture profile, particle size distribution, melting profiles, polymorphism, microstructure, fat content, protein content, total phenolics, total flavonoids, antioxidant activity, and organoleptic characteristics. The results showed that the combination of OM and SPI ratios, alongside the addition of ESE, significantly influenced the physicochemical and organoleptic characteristics of milk chocolate. During the reformulation of vegan milk chocolate, type VI (β1) polymorphic crystals were obtained, and no fat bloom was observed, signifying the success of the process. Through organoleptic testing, VC1, VC2, and VC5 received the highest preference from panelists. In particular, VC5 was observed to have the best physicochemical and organoleptic characteristics in this study; the reformulation of milk chocolate was suitable for vegan consumers as a non-dairy plant-based product option.

Authors

Publication Details

Journal
Applied Food Research
Published
2024-12-23
DOI
https://doi.org/10.1016/j.afres.2024.100674
Citations
6
Primary Topic
Food Chemistry and Fat Analysis
Type
article
Field-Weighted Citation Impact
2.09
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improving the properties and sensory acceptability of vegan chocolate formulated with oat milk and soy protein isolate by incorporating encapsulated strawberry extract

Dimas Rahadian Aji Muhammad, Mohamad Djali, Bangkit Wiguna, Edy Subroto et al.
6 citations
Applied Food Research
Food Chemistry and Fat Analysis
2.09
article

Improving the properties and sensory acceptability of vegan chocolate formulated with oat milk and soy protein isolate by incorporating encapsulated strawberry extract

Dimas Rahadian Aji Muhammad, Mohamad Djali, Bangkit Wiguna, Edy Subroto, Rossi Indiarto, Rizal Wahyudi Al-Amin
article en
6 citations

Abstract

This study aimed to investigate the physicochemical properties, antioxidant activity, and organoleptic characteristics of vegan milk chocolate with various formulas. To achieve this objective, seven treatment formulas were used with different levels of OM and SPI, and ESE was added. The parameters analyzed included color, texture profile, particle size distribution, melting profiles, polymorphism, microstructure, fat content, protein content, total phenolics, total flavonoids, antioxidant activity, and organoleptic characteristics. The results showed that the combination of OM and SPI ratios, alongside the addition of ESE, significantly influenced the physicochemical and organoleptic characteristics of milk chocolate. During the reformulation of vegan milk chocolate, type VI (β1) polymorphic crystals were obtained, and no fat bloom was observed, signifying the success of the process. Through organoleptic testing, VC1, VC2, and VC5 received the highest preference from panelists. In particular, VC5 was observed to have the best physicochemical and organoleptic characteristics in this study; the reformulation of milk chocolate was suitable for vegan consumers as a non-dairy plant-based product option.

Applied Food ResearchVol. 5(1)
Zero hunger
Openalex Percentile: Top 14%
Food Chemistry and Fat Analysis
2.09
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.