Enzymatic synthesis of structured lipids rich in α-linolenic acid: impacts of triacylglycerol profile on physicochemical characteristics

Abstract Medium- and long-chain triacylglycerols rich in α-linolenic acid (ALA-MLCT) are a kind of functional structural lipids that provide ω-3 fatty acid and faster energy supply to human body. To improve the functional and nutritional properties of vegetable oils, we proposed an effective strategy for the synthesis of ALA-MLCT by enzymatic interesterification of coconut oil and flaxseed oil. Lipase UM1 exhibited the highest interesterification activity compared with commercial Lipozyme RM IM, Lipozyme TL IM and Novozym 435. MLCT (76.59%) and ALA-MLCT (45.03%) were obtained under the optimum reaction conditions: substrate molar ratio (coconut oil/flaxseed oil) 1:1, temperature 40 °C, Lipase UM1 loading 25 U g‑1. Furthermore, we identified 14 characteristic triacylglycerols molecules between enzymatic interesterification and physical blend by orthogonal partial least squares-discrimination analysis (OPLS-DA) model. The content of triunsaturated type triacylglycerols in enzymatic interesterification product (11.29%) was lower than that of physical blend (36.25%). Enzymatic interesterification product had lower solid fat content and 2.44 times oxidative stability than physical blend. These findings provide an effective strategy for the synthesis of functional ALA-MLCT and advance the understanding of the relationship between triacylglycerols composition and physicochemical characteristics.

Authors

Institutions

Publication Details

Journal
International Journal of Food Science & Technology
Published
2024-08-30
DOI
https://doi.org/10.1111/ijfs.17457
Citations
2
Primary Topic
Food Chemistry and Fat Analysis
Type
article
Field-Weighted Citation Impact
0.70
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enzymatic synthesis of structured lipids rich in α-linolenic acid: impacts of triacylglycerol profile on physicochemical characteristics

Erna Li, Lixia Mu, Weifei Wang, Xuan Liu et al.
2 citations
International Journal of Food Science & Technology
Food Chemistry and Fat Analysis
0.70
article

Enzymatic synthesis of structured lipids rich in α-linolenic acid: impacts of triacylglycerol profile on physicochemical characteristics

Erna Li, Lixia Mu, Weifei Wang, Xuan Liu, Jun Liu, Pengfei Zhou, He Shi
article en
2 citations

Abstract

Abstract Medium- and long-chain triacylglycerols rich in α-linolenic acid (ALA-MLCT) are a kind of functional structural lipids that provide ω-3 fatty acid and faster energy supply to human body. To improve the functional and nutritional properties of vegetable oils, we proposed an effective strategy for the synthesis of ALA-MLCT by enzymatic interesterification of coconut oil and flaxseed oil. Lipase UM1 exhibited the highest interesterification activity compared with commercial Lipozyme RM IM, Lipozyme TL IM and Novozym 435. MLCT (76.59%) and ALA-MLCT (45.03%) were obtained under the optimum reaction conditions: substrate molar ratio (coconut oil/flaxseed oil) 1:1, temperature 40 °C, Lipase UM1 loading 25 U g‑1. Furthermore, we identified 14 characteristic triacylglycerols molecules between enzymatic interesterification and physical blend by orthogonal partial least squares-discrimination analysis (OPLS-DA) model. The content of triunsaturated type triacylglycerols in enzymatic interesterification product (11.29%) was lower than that of physical blend (36.25%). Enzymatic interesterification product had lower solid fat content and 2.44 times oxidative stability than physical blend. These findings provide an effective strategy for the synthesis of functional ALA-MLCT and advance the understanding of the relationship between triacylglycerols composition and physicochemical characteristics.

International Journal of Food Science & TechnologyVol. 59(10)
Guangdong Academy of Agricultural Sciences (CN), Ministry of Agriculture and Rural Affairs (CN), South China University of Technology (CN)
Openalex Percentile: Top 28%
Food Chemistry and Fat Analysis
0.70
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.