Evidence map›Paper›PMID 40894902›Full record

ArticleiScience2025

Identification of superior rice donors with enhanced nitrogen use efficiency using a comprehensive multivariate genotype selection strategy.

Nguyen Trung Duc, Amooru Harika, Dhandapani Raju, Sudhir Kumar, Renu Pandey, Lekshmy Sathee, Elangovan Alimuthu, Biswabiblap Singh, Chandrapal Vishwakarma, Ranjith Kumar Ellur and 8 more

Abstract read
In one paragraph

Article in iScience, 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

18 authors.

Nguyen Trung DucDivision of Plant Physiology, Indian Council of Agricultural Research (ICAR)- Indian Agricultural Research Institute (IARI), New Delhi, India.
Amooru HarikaDivision of Plant Physiology, Indian Council of Agricultural Research (ICAR)- Indian Agricultural Research Institute (IARI), New Delhi, India.
Dhandapani RajuDivision of Plant Physiology, Indian Council of Agricultural Research (ICAR)- Indian Agricultural Research Institute (IARI), New Delhi, India.
Sudhir KumarDivision of Plant Physiology, Indian Council of Agricultural Research (ICAR)- Indian Agricultural Research Institute (IARI), New Delhi, India.
Renu PandeyDivision of Plant Physiology, Indian Council of Agricultural Research (ICAR)- Indian Agricultural Research Institute (IARI), New Delhi, India.
Lekshmy SatheeDivision of Plant Physiology, Indian Council of Agricultural Research (ICAR)- Indian Agricultural Research Institute (IARI), New Delhi, India.
Elangovan AlimuthuDivision of Plant Physiology, Indian Council of Agricultural Research (ICAR)- Indian Agricultural Research Institute (IARI), New Delhi, India.
Biswabiblap SinghDivision of Plant Physiology, Indian Council of Agricultural Research (ICAR)- Indian Agricultural Research Institute (IARI), New Delhi, India.
Chandrapal VishwakarmaDivision of Plant Physiology, Indian Council of Agricultural Research (ICAR)- Indian Agricultural Research Institute (IARI), New Delhi, India.
Ranjith Kumar EllurDivision of Genetics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Research Institute (IARI), New Delhi, India.
Mir Asif IquebalDivision of Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute (IASRI), New Delhi, India.
Rakesh PandeyDivision of Plant Physiology, Indian Council of Agricultural Research (ICAR)- Indian Agricultural Research Institute (IARI), New Delhi, India.
Ambika RajendranDivision of Genetics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Research Institute (IARI), New Delhi, India.
Akshay SakhareDivision of Crop Improvement, ICAR-Indian Institute of Rice Research, Hyderabad, India.
Rabi Narayan SahooDivision of Agricultural Physics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Research Institute (IARI), New Delhi, India.
Naga Neeraja ChirravuriDivision of Crop Improvement, ICAR-Indian Institute of Rice Research, Hyderabad, India.
A SenthilDepartment of Crop Physiology, Tamil Nadu Agricultural Research Institute, Coimbatore, Tamil Nadu, India.
Viswanathan ChinnusamyDivision of Plant Physiology, Indian Council of Agricultural Research (ICAR)- Indian Agricultural Research Institute (IARI), New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Improving nitrogen use efficiency (NUE) of rice plants utilizing a few end-of-season traits poses a severe phenotyping bottleneck in exploring the genetic diversity of a large population and genotype selection accuracy. Therefore, a comprehensive multivariate genotype selection strategy was developed to explore maximum genetic variation of 300 diverse rice genotypes and accurately select promising rice donors with enhanced NUE traits on a multi-year (2019, 2021, and 2022) -trait (126 traits) -environment (2) -temporal (5) -location (3) scale. The multi-trait genotype ideotype distance index (MGIDI) ranked Cauvery, Suweon, RPW9-4 (SSI) and BAM3690 (IC463705) as superior NUE genotypes; Moroberekan, PUSA1121 and BAM8315 (Basmati 370) as low NUE genotypes. The multi-location field performance and molecular analysis of key nitrogen assimilatory genes confirmed the outperformance of the Cauvery genotype in terms of possessing efficient N sensing, uptake, transport and assimilation characteristics under N-limited conditions. Phenome-wide multivariate analysis highlights root-shoot plastic response as a key target trait for breeding rice genotypes resilient to N stress conditions.

Indexed as

Agricultural scienceGenomic libraryGenotypingNatural sciencesPlant biology

Identifiers

PMID40894902
PMCPMC12398238

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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.