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Record W4410898381 · doi:10.3390/plants14111666

Effects of Salinity Stress on Grasspea (Lathyrus sativus L.) and Its Wild Relatives: Morpho-Physiological Insights at the Seedling Stage

2025· article· en· W4410898381 on OpenAlexaff
Khawla Aloui, Outmane Bouhlal, Hasnae Choukri, Priyanka Gupta, Keltoum El Bouhmadi, Noureddine El Haddad, Khadija El Bargui, Fouad Maalouf, Shiv Kumar

Bibliographic record

VenuePlants · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Stress Responses and Tolerance
Canadian institutionsUniversité Laval
FundersIndian Council of Agricultural Research
KeywordsLathyrusSeedlingGermplasmBiologySalinityShootAbiotic componentHorticultureAbiotic stressBotanyGeneEcology

Abstract

fetched live from OpenAlex

Salinity is a critical abiotic stress influencing plant growth. However, its effect on grasspea (Lathyrus sativus L.) remains insufficiently explored. The present study screened 24 germplasm accessions representing 11 Lathyrus species at the seedling stage at 0, 100, and 150 mM NaCl concentrations using a hydroponic system. Our findings indicated that salt stress had a significant effect on all assessed traits, including a reduction in relative leaf water content and SPAD index, a decline in the length and biomass of shoots and roots, and an elevation in their corresponding dry contents. The grasspea accessions displayed a wide range of responses to salt stress. This variation allowed the identification of nine tolerant accessions at both stress levels, belonging to cultivated and wild relative species, specifically LAT 495, IG 65117, L.OCH, IG 65273, IG 64931, IG 114526, IG 64892, IG 66065, and IG 65018. Four accessions, namely IG 110632, IG 114531, IG 65133, and IG 66026, demonstrated tolerance only at 100 mM NaCl concentration. Through identifying these promising accessions, our research offers crucial insights for the initial screening of tolerant genotypes in grasspea, setting the stage for further studies to decipher the intricate mechanisms of salinity tolerance in these accessions.

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)0.000
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 score0.878
Threshold uncertainty score0.210

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.019
GPT teacher head0.234
Teacher spread0.215 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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