Evidence map›Paper›PMID 41042448›Full record

ArticleRice (New York, N.Y.)2025

A Genome‑wide Association Study of the Grain Ionome in Rice Oryza Sativa Ssp. Japonica under Two Diverse Water Management Systems.

Gabriele Orasen, Erica Mica, Giorgio Lucchini, Noemi Negrini, Fabio Francesco Nocito, Elena Baldoni, Alessandro Tondelli, Giampiero Valè, Gian Attilio Sacchi

Abstract read
In one paragraph

Article in Rice (New York, N.Y.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. Article
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

9 authors.

Gabriele Orasen *DiSAA-Dipartimento di Scienze Agrarie e Ambientali - Produzione, Territorio, Agroenergia, Università degli Studi di Milano, via Celoria 2, Milano, I- 20133, Italy.
Erica Mica *DiSSTE - Dipartimento per lo Sviluppo Sostenibile e la Transizione Ecologica, Università del Piemonte Orientale, Piazza Sant' Eusebio 5, Vercelli, 13100, Italy.
Giorgio LucchiniDiSAA-Dipartimento di Scienze Agrarie e Ambientali - Produzione, Territorio, Agroenergia, Università degli Studi di Milano, via Celoria 2, Milano, I- 20133, Italy.
Noemi NegriniDiSAA-Dipartimento di Scienze Agrarie e Ambientali - Produzione, Territorio, Agroenergia, Università degli Studi di Milano, via Celoria 2, Milano, I- 20133, Italy.
Fabio Francesco NocitoDiSAA-Dipartimento di Scienze Agrarie e Ambientali - Produzione, Territorio, Agroenergia, Università degli Studi di Milano, via Celoria 2, Milano, I- 20133, Italy.
Elena BaldoniCNR-National Research Council (CNR), Institute of Agricultural Biology and Biotechnology (IBBA), via Bassini 15, Milano, I-20133, Italy.
Alessandro TondelliResearch Centre for Genomics and Bioinformatics, Council for Agricultural Research and Economics (CREA), Via San Protaso 69, Fiorenzuola d'Arda, 29017, Italy.
Giampiero ValèDiSSTE - Dipartimento per lo Sviluppo Sostenibile e la Transizione Ecologica, Università del Piemonte Orientale, Piazza Sant' Eusebio 5, Vercelli, 13100, Italy. giampiero.vale@uniupo.it.
Gian Attilio SacchiDiSAA-Dipartimento di Scienze Agrarie e Ambientali - Produzione, Territorio, Agroenergia, Università degli Studi di Milano, via Celoria 2, Milano, I- 20133, Italy. gianattilio.sacchi@unimi.it.

Funding

InnovaRisi project BaC Agritech-Spoke 6, Project Code CN00000022
6 · The paper itself

Abstract

Rice is an important human staple food providing calories and useful elements, even though vulnerable to heavy metal contamination. Breeding tools for improving the concentration of nutrient and reduce levels of toxic compounds can improve the nutritional value and safety of rice grains. This work presents a comprehensive analysis of the genetic bases controlling variation in the rice ionome employing genome-wide association studies (GWAS) with a diversity panel of 294 temperate and tropical japonica accessions, each genotyped with 36,830 SNP loci. GWAS was performed for brown rice content of 13 elements: As, Ca, Cd, Cu, Fe, K, Mg, Mn, Mo, Na, Ni, P, Zn for rice plants grown under two diverse water management regimes, permanent flooding and limited watering. GWAS identified 232 significant marker-traits associations (MTAs); 87 of which had high R

Indexed as

GWASIonomic traitsRiceWater management

Identifiers

PMID41042448
PMCPMC12494520

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.