Evidence map›Paper›PMID 31787805›Full record

ReviewTrends in food science & technology2019

Rice quality: How is it defined by consumers, industry, food scientists, and geneticists?

Marie Claire Custodio, Rosa Paula Cuevas, Jhoanne Ynion, Alice G Laborte, Maria Lourdes Velasco, Matty Demont

Abstract readReview
In one paragraph

Review in Trends in food science & technology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
84citing papers in PubMed, 2 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

84 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  14. Functional Analysis of the Autophagy-Related GenePlants (Basel, Switzerland) · 2025
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  15. The Endosperm-Specific GenePlants (Basel, Switzerland) · 2025
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  17. TheInternational journal of molecular sciences · 2025
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24 more citing papers are in PubMed but not listed here.

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

6 authors.

Marie Claire CustodioInternational Rice Research Institute (IRRI), Los Baños, Laguna, Philippines.
Rosa Paula CuevasInternational Rice Research Institute (IRRI), Los Baños, Laguna, Philippines.
Jhoanne YnionInternational Rice Research Institute (IRRI), Los Baños, Laguna, Philippines.
Alice G LaborteInternational Rice Research Institute (IRRI), Los Baños, Laguna, Philippines.
Maria Lourdes VelascoInternational Rice Research Institute (IRRI), Los Baños, Laguna, Philippines.
Matty DemontInternational Rice Research Institute (IRRI), Los Baños, Laguna, Philippines.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundQuality is a powerful engine in rice value chain upgrading. However, there is no consensus on how "rice quality" should be defined and measured in the rice sector. SCOPE AND APPROACH: We adopt a Lancasterian definition of rice quality as a bundle of intrinsic and extrinsic attributes. We then review how rice quality is (i) perceived and defined by consumers and industry stakeholders in rice value chains in Southeast and South Asia; (ii) measured and defined by food technologists; and (iii) predicted through genetics. KEY FINDINGS AND

conclusionsConsumers are heterogeneous with respect to their perceived differentiation of rice quality among regions, countries, cities, and urbanization levels. Premium quality is defined by nutritional benefits, softness and aroma in Southeast Asia, and by the physical appearance of the grains (uniformity, whiteness, slenderness), satiety, and aroma in South Asia. These trends are found to be consistent with industry perceptions and have important implications for regional and national breeding programs in terms of tailoring germplasm to regions and rice varieties to specific local market segments. Because rice is traded internationally, there is a need to standardize definitions of rice quality. However, food technologists have not reached unanimity on quality classes and measurement; routine indicators need to be complemented by descriptive profiles elicited through sensory evaluation panels. Finally, because rice quality is controlled by multiple interacting genes expressed through environmental conditions, predicting grain quality requires associating genetic information with grain quality phenotypes in different environments.

Indexed as

Gene × environmentIntrinsic attributesPerceptionSensory evaluationValue chain upgrading

Identifiers

PMID31787805
PMCPMC6876681

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.