Evidence map›Paper›PMID 33097677›Full record

ReviewJournal of biosciences2020

Plant abiotic stress tolerance: Insights into resilience build-up.

Penna Suprasanna

Abstract readReview
PubMed
In one paragraph

Review in Journal of biosciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Abiotic Stresses in Plants: From Molecules to Environment.International journal of molecular sciences · 2024
    Article
  2. Article
  3. Article
  4. Article
  5. Pyramiding of transcription factor,Frontiers in plant science · 2023
    Article
  6. Review
  7. Review
  8. 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

1 author.

Penna SuprasannaNuclear Agriculture and Biotechnology Division, Bhabha Atomic Research Centre, Trombay, Mumbai 400 085, India, penna888@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Climate change and the consequential unpredictable environmental stress conditions negatively impact crop productivity. It has thus become a challenge to develop solutions for food security and sustainable agriculture in the backdrop of increasing population pressure and dwindling land and water resources. This further necessitates that focus of international research should be on curtailing yield losses through improved crop breeding practices and genetic manipulation for the development of resistant crop varieties. Plants being sessile, have developed a complex regulatory network of genetic machinery which includes transcription factors, small RNAs, signalling pathways, stress sensors and defense pathways. Needless to say, research efforts have exploited this genetic reservoir for manipulating crop plants for tolerance or resistance against different stresses. In the past few decades, significant achievement has been made for developing transgenic plants for a wide variety of single or multiple stress tolerance associated traits. Several regulatory mechanisms have been identified to fine tune and tailor the tolerance response in target sensitive crops. The advent of metabolic engineering has added new dimensions to manipulate stress tolerance pathways. Novel strategies are needed to develop stable, superior performing lines under challenging field environment without yield penalty and significant success has to be achieved to translate the research outcome from lab-to-land to reach farmer's fields.

Indexed as

Climate ChangeCrops, AgriculturalGenetic EngineeringPlants, Genetically ModifiedQuantitative Trait LociStress, Physiological

Identifiers

PMID33097677

What OpenQuestion holds

Textmetadata
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.