Evidence map›Paper›PMID 39333483›Full record

ArticleNature communications2024

Context-dependent agricultural intensification pathways to increase rice production in India.

Hari Sankar Nayak, Andrew J McDonald, Virender Kumar, Peter Craufurd, Shantanu Kumar Dubey, Amaresh Kumar Nayak, Chiter Mal Parihar, Panneerselvam Peramaiyan, Shishpal Poonia, Kindie Tesfaye and 4 more

Abstract read
In one paragraph

Article in Nature communications, 2024. 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

14 authors.

Hari Sankar NayakSchool of Integrative Plant Science, Cornell University, Ithaca, NY, USA. 1996harisankar@gmail.com.ORCID 0000-0003-2585-1576
Andrew J McDonaldSchool of Integrative Plant Science, Cornell University, Ithaca, NY, USA.ORCID 0000-0002-2660-3470
Virender KumarInternational Rice Research Institute (IRRI), Los Banos, Philippines.
Peter CraufurdInternational Maize and Wheat Improvement Center (CIMMYT), South Asia Regional Office, Lalitpur, Nepal.
Shantanu Kumar DubeyIndian Council of Agricultural Research (ICAR), New Delhi, India.
Amaresh Kumar NayakICAR-National Rice Research Institute, Cuttack, Odisha, India.
Chiter Mal PariharICAR-Indian Agricultural Research Institute, New Delhi, India.
Panneerselvam PeramaiyanInternational Rice Research Institute (IRRI) - South Asia Regional Centre (ISARC), Varanasi, Uttar Pradesh, India.ORCID 0000-0002-7886-5536
Shishpal PooniaInternational Maize and Wheat Improvement Center (CIMMYT), National Agricultural Science Complex (NASC), New Delhi, India.
Kindie TesfayeInternational Maize and Wheat Improvement Center (CIMMYT), Addis Ababa, Ethiopia.ORCID 0000-0002-7201-8053
Ram K MalikInternational Maize and Wheat Improvement Center (CIMMYT), National Agricultural Science Complex (NASC), New Delhi, India.
Anton UrfelsSchool of Integrative Plant Science, Cornell University, Ithaca, NY, USA.
Udham Singh GautamIndian Council of Agricultural Research (ICAR), New Delhi, India.
João Vasco SilvaInternational Maize and Wheat Improvement Center (CIMMYT), Harrare, Zimbabwe.ORCID 0000-0002-3019-5895

Funding

Gates Foundation INV-005431
6 · The paper itself

Abstract

Yield gap analysis is used to characterize the untapped production potential of cropping systems. With emerging large-n agronomic datasets and data science methods, pathways for narrowing yield gaps can be identified that provide actionable insights into where and how cropping systems can be sustainably intensified. Here we characterize the contributing factors to rice yield gaps across seven Indian states, with a case study region used to assess the power of intervention targeting. Primary yield constraints in the case study region were nitrogen and irrigation, but scenario analysis suggests modest average yield gains with universal adoption of higher nitrogen rates. When nitrogen limited fields are targeted for practice change (47% of the sample), yield gains are predicted to double. When nitrogen and irrigation co-limitations are targeted (20% of the sample), yield gains more than tripled. Results suggest that analytics-led strategies for crop intensification can generate transformative advances in productivity, profitability, and environmental outcomes.

Indexed as

Agricultural IrrigationAgricultureCrop ProductionCrops, AgriculturalOryzaFertilizersIndiaNitrogenFertilizersNitrogen

Identifiers

PMID39333483
PMCPMC11436799

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.