Evidence map›Paper›PMID 31776807›Full record

ArticleRice (New York, N.Y.)2019

Improving the Glossiness of Cooked Rice, an Important Component of Visual Rice Grain Quality.

Seul-Gi Park, Hyun-Su Park, Man-Kee Baek, Jong-Min Jeong, Young-Chan Cho, Gun-Mi Lee, Chang-Min Lee, Jung-Pil Suh, Choon-Song Kim, Suk-Man Kim

Abstract read
In one paragraph

Article in Rice (New York, N.Y.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. QTL detection for rice grain storage protein content and genetic effect verifications.Molecular breeding : new strategies in plant improvement · 2023
    Article
  5. Knocking OutInternational journal of molecular sciences · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Seul-Gi ParkCrop Breeding Division, National Institute of Crop Science, Rural Development Administration, Wanju, Republic of Korea.
Hyun-Su ParkCrop Breeding Division, National Institute of Crop Science, Rural Development Administration, Wanju, Republic of Korea.
Man-Kee BaekCrop Breeding Division, National Institute of Crop Science, Rural Development Administration, Wanju, Republic of Korea.
Jong-Min JeongCrop Breeding Division, National Institute of Crop Science, Rural Development Administration, Wanju, Republic of Korea.
Young-Chan ChoCrop Breeding Division, National Institute of Crop Science, Rural Development Administration, Wanju, Republic of Korea.
Gun-Mi LeeCrop Breeding Division, National Institute of Crop Science, Rural Development Administration, Wanju, Republic of Korea.
Chang-Min LeeCrop Breeding Division, National Institute of Crop Science, Rural Development Administration, Wanju, Republic of Korea.
Jung-Pil SuhCrop Breeding Division, National Institute of Crop Science, Rural Development Administration, Wanju, Republic of Korea.
Choon-Song KimCrop Breeding Division, National Institute of Crop Science, Rural Development Administration, Wanju, Republic of Korea.
Suk-Man KimCrop Breeding Division, National Institute of Crop Science, Rural Development Administration, Wanju, Republic of Korea. qsmkim@korea.kr.ORCID http://orcid.org/0000-0002-6701-4824

Funding

Rural Development Administration PJ01133102
6 · The paper itself

Abstract

backgroundRice is one of the few cereals consumed as a whole grain, and therefore the appearance of the final milled product, both before and after cooking, strongly influences the consumer's perception of product quality. Matching consumer preference for rice grain quality is a key component of rice variety development programs, as the quality drives demand, which in turn drives variety adoption, market price, and profitability. The quality of cooked rice is normally evaluated indirectly, through measurement of key elements driving quality as well as more directly by sensory evaluation, but remains a complex trait conditioned by the genetic complexity of factors driving quality, changes wrought by environment, and the complexity of consumer preferences.

resultIn this study, we evaluated 17 traits, including the taste value obtained by glossiness of cooked rice (TV), to explain rice eating quality by statistical methods and identified QTLs associated with TV. To explain the correlation among traits, exploratory factor analysis was performed for 2 years. The overall eating quality (OE) was correlated with TV and protein content loading at the same factor (PA1) in 2017, and there was a relationship between the OE (PA1) and the TV (PA2) in 2018 (PA1:PA2, r = 0.3). In QTL analysis using 174 RILs, three QTLs for TV derived from Wandoaengmi6 were detected on chromosomes 4, 6, and 9. The QTL qTV9 delimited within Id9007180 and 9,851,330 on chromosome 9 was detected in both years, explaining approximately 17% of the variation, on average. Through the use of fine mapping, qTV9 was delimited to an approximately 34-Kbp segment flanked by the DNA markers CTV9_9 and CTV9_13, and nine ORFs were listed in the target region as candidate genes associated with TV. In the evaluation of qTV9's effect on OE, the lines with qTV9 showed a significant increase in correlation coefficiency compared to the negative lines. These data will apply to functional analysis on the glossiness and the MAS breeding program to improve the eating quality of japonica as a donor line.

conclusionIn this paper we report a number of QTL associated with changes in glossiness of cooked rice, and these may have utility in the development of MAS in breeding programs with a specific focus on cooked grain quality.

Indexed as

Eating qualityGlossiness of cooked riceMASPalatability testQTLRice

Identifiers

PMID31776807
PMCPMC6881499

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.