MétaCan
Menu
Back to cohort
Record W1603259326 · doi:10.5539/jas.v7n10p281

Performance of Some Alfalfa Cultivars under Salinity Stress Conditions

2015· article· en· W1603259326 on OpenAlexvenueno aff
A. E. Badran, Esraa A. M. ElSherebeny, Yasser Salama

Bibliographic record

VenueJournal of Agricultural Science · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Stress Responses and Tolerance
Canadian institutionsnot available
Fundersnot available
KeywordsSalinityCultivarProlineBiologyHorticultureDry weightPath analysis (statistics)BotanyAgronomyMathematicsEcology

Abstract

fetched live from OpenAlex

The experiment was aimed at assessing the response of three alfalfa (Medicajo sativa L.) varieties viz., Giza 1, Al-hasawi and Siwa 1 under two salinity levels during 2012 and 2013 growing seasons. The statistical analysis revealed significant differences among varieties for various traits associated with salt tolerance under salinity stress. Regarding to stress tolerance index, the results confirm that Al-hasawi cv. and Siwa 1 cv. were found to be more tolerant of salinity than Giza 1 cv. According to correlation and path analysis, proline and chlorophyll content recorded the highest positive direct effect on dry weight per plant (1.135 and 0.693 respectively,). At biochemical level, analysis of soluble protein by SDS-PAGE revealed that percentage of polymorphic and monomorphic were 75 and 25 respectively. Also, the molecular weights of some salt responsive proteins (16.4, 29.5, 33.9 and 37 kDa) are necessary to select the tolerant varieties under salinity stress in alfalfa plant.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.035
GPT teacher head0.258
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural ScienceSame topicPlant Stress Responses and ToleranceFrench-language works237,207