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Record W2800787043 · doi:10.1111/jac.12283

Legume endosymbionts: Drought stress tolerance in second‐generation chickpea (<i>Cicer arietinum</i>) seeds

2018· article· en· W2800787043 on OpenAlexaff
Vinti Kumari, James J. Germida, Vladimir Vujanovic

Bibliographic record

VenueJournal of Agronomy and Crop Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLegume Nitrogen Fixing Symbiosis
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsBiologyAbiotic stressGerminationAbiotic componentSymbiosisCropLegumeDrought toleranceShootAgronomyReactive oxygen speciesBotanySuperoxide dismutaseOxidative stressBacteriaGeneEcology

Abstract

fetched live from OpenAlex

Abstract Chickpea is an important leguminous crop grown worldwide due to its nutritional and economic value. However, abiotic stress, primarily caused by drought, has limited chickpea production. This study highlights endosymbiotic plant growth promotion as well as alleviation of abiotic stress in germinating chickpea seeds and seedlings under drought stress conditions. Seed produced by F 1 endosymbiotic plants under controlled environment was used to conduct this second‐generation (F 2 ) study in the greenhouse. Fungal and bacterial endosymbionts improved seed germination and enhanced root and shoot growth in second‐generation seeds produced by applying drought stress without endophytes. Expression levels of antioxidant genes, proline, SOD ‐superoxide dismutase and dehydrin, were downregulated, which characterizes enhanced oxidative stress tolerance and reduced reactive oxygen species ( ROS ) in host cells. The endosymbiont beneficial effect on plant resilience and improved phenotypes was translated into increased nutrient quality of second‐generation seed. This study indicates the potential of the fungal and bacterial endosymbionts to moderate drought stress in plants by triggering epigenetic changes inherited across chickpea generations which correlated with enhanced resilience and improved agricultural traits in this globally important crop.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.495
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.218
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2018
Admission routes1
Has abstractyes

Explore more

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