Evidence map›Paper›PMID 31775241›Full record

ReviewBiology2019

Advances in Omics Approaches for Abiotic Stress Tolerance in Tomato.

Juhi Chaudhary, Praveen Khatri, Pankaj Singla, Surbhi Kumawat, Anu Kumari, Vinaykumar R, Amit Vikram, Salesh Kumar Jindal, Hemant Kardile, Rahul Kumar and 2 more

Abstract readReview
In one paragraph

Review in Biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Review
  2. Genomic prediction for yield and malting traits in barley using metabolomic and near-infrared spectra.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Article
  3. Physiology of salt tolerance introgressions fromFrontiers in plant science · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Tomato Biodiversity and Drought Tolerance: A Multilevel Review.International journal of molecular sciences · 2023
    Review
  12. Review
  13. Article
  14. Biotechnological Advances to Improve Abiotic Stress Tolerance in Crops.International journal of molecular sciences · 2022
    Review
  15. Article
  16. Article
  17. Review
  18. Review
  19. Review
  20. Review
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

12 authors.

Juhi ChaudharyDepartment of Biology, Oberlin College, Oberlin, OH 44074, USA.
Praveen KhatriNational Agri-Food Biotechnology Institute (NABI), Mohali, Punjab 140306, India.
Pankaj SinglaNational Agri-Food Biotechnology Institute (NABI), Mohali, Punjab 140306, India.
Surbhi KumawatNational Agri-Food Biotechnology Institute (NABI), Mohali, Punjab 140306, India.
Anu KumariNational Agri-Food Biotechnology Institute (NABI), Mohali, Punjab 140306, India.
Vinaykumar RDepartment of Vegetable Science, Dr. Yashwant Singh Parmar University of Horticulture and Forestry, Solan, Himachal Pradesh 173230, India.
Amit VikramDepartment of Vegetable Science, Dr. Yashwant Singh Parmar University of Horticulture and Forestry, Solan, Himachal Pradesh 173230, India.ORCID 0000-0003-3047-1594
Salesh Kumar JindalDepartment of Vegetable Science, Punjab Agricultural University, Ludhiana, Punjab 141004, India.
Hemant KardileDivision of Crop Improvement, ICAR-Central Potato Research Institute (CPRI), Shimla, Himachal Pradesh 171001, India.
Rahul KumarDepartment of Plant Science, University of Hyderabad, Hyderabad 500046, India.ORCID 0000-0002-4298-5130
Humira SonahNational Agri-Food Biotechnology Institute (NABI), Mohali, Punjab 140306, India.ORCID 0000-0003-4796-6120
Rupesh DeshmukhNational Agri-Food Biotechnology Institute (NABI), Mohali, Punjab 140306, India.ORCID 0000-0003-4167-6552

Funding

Department of Biotechnology, Government of India Ramalingaswami Fellow
6 · The paper itself

Abstract

Tomato, one of the most important crops worldwide, has a high demand in the fresh fruit market and processed food industries. Despite having considerably high productivity, continuous supply as per the market demand is hard to achieve, mostly because of periodic losses occurring due to biotic as well as abiotic stresses. Although tomato is a temperate crop, it is grown in almost all the climatic zones because of widespread demand, which makes it challenge to adapt in diverse conditions. Development of tomato cultivars with enhanced abiotic stress tolerance is one of the most sustainable approaches for its successful production. In this regard, efforts are being made to understand the stress tolerance mechanism, gene discovery, and interaction of genetic and environmental factors. Several omics approaches, tools, and resources have already been developed for tomato growing. Modern sequencing technologies have greatly accelerated genomics and transcriptomics studies in tomato. These advancements facilitate Quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and genomic selection (GS). However, limited efforts have been made in other omics branches like proteomics, metabolomics, and ionomics. Extensive cataloging of omics resources made here has highlighted the need for integration of omics approaches for efficient utilization of resources and a better understanding of the molecular mechanism. The information provided here will be helpful to understand the plant responses and the genetic regulatory networks involved in abiotic stress tolerance and efficient utilization of omics resources for tomato crop improvement.

Indexed as

genome-wide association studygenotyping by sequencingionomicsmetabolomicsproteomicsquantitative trait loci

Identifiers

PMID31775241
PMCPMC6956103

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.