Evidence map›Paper›PMID 34065368›Full record

ReviewGenes2021

Harnessing Crop Wild Diversity for Climate Change Adaptation.

Andrés J Cortés, Felipe López-Hernández

Abstract readReview
In one paragraph

Review in Genes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing 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

53 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Regional Cultivation Forms ofJournal of fungi (Basel, Switzerland) · 2026
    Review
  5. Evaluation and Selection ofPlants (Basel, Switzerland) · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Genomic Prediction of Adaptation in Common Bean (International journal of molecular sciences · 2025
    Article
  12. Article
  13. Article
  14. Article
  15. Abiotic Stress Tolerance Boosted by Genetic Diversity in Plants.International journal of molecular sciences · 2024
    Article
  16. Article
  17. Biocultural diversity and crop improvement.Emerging topics in life sciences · 2023
    Review
  18. Article
  19. Article
  20. 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

2 authors.

Andrés J CortésCorporación Colombiana de Investigación Agropecuaria AGROSAVIA, C.I. La Selva, Km 7 Vía Rionegro, Las Palmas, Rionegro 054048, Colombia.ORCID 0000-0003-4178-0675
Felipe López-HernándezCorporación Colombiana de Investigación Agropecuaria AGROSAVIA, C.I. La Selva, Km 7 Vía Rionegro, Las Palmas, Rionegro 054048, Colombia.ORCID 0000-0002-4967-6955

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Warming and drought are reducing global crop production with a potential to substantially worsen global malnutrition. As with the green revolution in the last century, plant genetics may offer concrete opportunities to increase yield and crop adaptability. However, the rate at which the threat is happening requires powering new strategies in order to meet the global food demand. In this review, we highlight major recent 'big data' developments from both empirical and theoretical genomics that may speed up the identification, conservation, and breeding of exotic and elite crop varieties with the potential to feed humans. We first emphasize the major bottlenecks to capture and utilize novel sources of variation in abiotic stress (i.e., heat and drought) tolerance. We argue that adaptation of crop wild relatives to dry environments could be informative on how plant phenotypes may react to a drier climate because natural selection has already tested more options than humans ever will. Because isolated pockets of cryptic diversity may still persist in remote semi-arid regions, we encourage new habitat-based population-guided collections for genebanks. We continue discussing how to systematically study abiotic stress tolerance in these crop collections of wild and landraces using geo-referencing and extensive environmental data. By uncovering the genes that underlie the tolerance adaptive trait, natural variation has the potential to be introgressed into elite cultivars. However, unlocking adaptive genetic variation hidden in related wild species and early landraces remains a major challenge for complex traits that, as abiotic stress tolerance, are polygenic (i.e., regulated by many low-effect genes). Therefore, we finish prospecting modern analytical approaches that will serve to overcome this issue. Concretely, genomic prediction, machine learning, and multi-trait gene editing, all offer innovative alternatives to speed up more accurate pre- and breeding efforts toward the increase in crop adaptability and yield, while matching future global food demands in the face of increased heat and drought. In order for these 'big data' approaches to succeed, we advocate for a trans-disciplinary approach with open-source data and long-term funding. The recent developments and perspectives discussed throughout this review ultimately aim to contribute to increased crop adaptability and yield in the face of heat waves and drought events.

Indexed as

Climate ChangePolymorphism, GeneticAdaptation, PhysiologicalCrops, AgriculturalMachine LearningPlant Breedingabiotic stress toleranceex situ conservationgenebanksgenetic adaptationgenome–environment associations (GEA)genome-wide selection scans (GWSS)genomic prediction (GP)germplasm collectionsmachine learning (ML)

Identifiers

PMID34065368
PMCPMC8161384

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.