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Phospholipids in rice: Significance in grain quality and health benefits: A review

Overview of attention for article published in Food Chemistry, January 2013
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Article details
Title
Phospholipids in rice: Significance in grain quality and health benefits: A review
Published in
Food Chemistry, January 2013
DOI 10.1016/j.foodchem.2012.12.046
Pubmed ID
Authors
Abstract

Phospholipids (PLs) are a major class of lipid in rice grain. Although PLs are only a minor nutrient compared to starch and protein, they may have both nutritional and functional significance. We have systemically reviewed the literature on the class, distribution and variation of PLs in rice, their relation to rice end-use quality and human health, as well as available methods for analytical profiling. Phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylinositol (PI) and their lyso forms are the major PLs in rice. The deterioration of PC in rice bran during storage was considered as a trigger for the degradation of rice lipids with associated rancid flavour in paddy and brown rice. The lyso forms in rice endosperm represent the major starch lipid, and may form inclusion complexes with amylose, affecting the physicochemical properties and digestibility of starch, and hence its cooking and eating quality. Dietary PLs have a positive impact on several human diseases and reduce the side-effects of some drugs. As rice has long been consumed as a staple food in many Asian countries, rice PLs may have significant health benefits for those populations. Rice PLs may be influenced both by genetic (G) and environmental (E) factors, and resolving G×E interactions may allow future exploitation of PL composition and content, thus boosting rice eating quality and health benefits for consumers. We have identified and summarised the different methods used for rice PL analysis, and discussed the consequences of variation in reported PL values due to inconsistencies between methods. This review enhances the understanding of the nature and importance of PLs in rice and outlines potential approaches for manipulating PLs to improve the quality of rice grain and other cereals.

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 245 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Vietnam 1 <1%
Uganda 1 <1%
Iceland 1 <1%
Germany 1 <1%
China 1 <1%
Australia 1 <1%
Unknown 239 98%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 35 14%
Student > Master 33 13%
Researcher 24 10%
Student > Bachelor 16 7%
Lecturer 12 5%
Other 41 17%
Unknown 84 34%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 72 29%
Chemistry 22 9%
Engineering 15 6%
Biochemistry, Genetics and Molecular Biology 12 5%
Medicine and Dentistry 8 3%
Other 22 9%
Unknown 94 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 March 2023.
All research outputs
#21,539,812
of 27,264,936 outputs
Outputs from Food Chemistry
#2,350
of 2,790 outputs
Outputs of similar age
#234,724
of 301,764 outputs
Outputs of similar age from Food Chemistry
#31
of 46 outputs
Altmetric has tracked 27,264,936 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,790 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 301,764 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.