Evidence map›Paper›PMID 40734986›Full record

ReviewFrontiers in plant science2025

Unveiling the underlying complexities in breeding for disease resistance in crop plants: review.

Rutuparna Pati, Surinder Sandhu, Ankita K Kawadiwale, Gagandeep Kaur

Abstract readReview
In one paragraph

Review in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Diversity, Taxonomy, and Pathogenicity of Members ofJournal of fungi (Basel, Switzerland) · 2026
    Article
  3. 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

4 authors.

Rutuparna PatiDepartment of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India.
Surinder SandhuDepartment of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India.
Ankita K KawadiwaleDepartment of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India.
Gagandeep KaurDepartment of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biotic stress significantly contributes to global crop losses, posing a major threat to food security and agricultural sustainability. While conventional plant breeding techniques have successfully enhanced crop resistance to pathogens, the perpetual emergence of new pathogens and the need to develop varieties with effective, stable, and broad-spectrum resistance in the shortest feasible time remain formidable challenges. The rapid delivery of these technologies to stakeholders further underscores the urgency for innovative approaches. This review delves into the complexities of breeding for disease resistance in crop plants, tracing its historical evolution and highlighting recent advancements in genetic and genomic technologies. These advancements have significantly deepened our understanding of host-pathogen interactions, enabling the identification of key genes and mechanisms governing resistance. We aim to offer insights into how historical perspectives and cutting-edge innovations can guide breeders in designing robust resistance strategies. Ultimately, this work seeks to empower breeders with actionable knowledge and tools to address the dynamic challenges posed by pathogens, paving the way for a more resilient and adaptable agricultural landscape.

Indexed as

Flor’s hypothesispathogenpathogenesisplant breedingplant diseaseplant immunityresistanceRLP/RLK

Identifiers

PMID40734986
PMCPMC12305370

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.