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Effects of Deficit Irrigation and Salinity Stress on Common Bean (<i>Phaseolus Vulgaris</i> L.) and Mungbean (<i>Vigna Radiata</i> (L.) Wilczek) Grown in a Controlled Environment

2010· article· en· W2059933624 on OpenAlexafffund
Maryse Bourgault, Chandra A. Madramootoo, Heidi Webber, G. Stulina, M. G. Horst, Donald L. Smith

Bibliographic record

VenueJournal of Agronomy and Crop Science · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsMcGill University
FundersFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsPhaseolusAgronomyIrrigationVignaSalinityBiologyBiomass (ecology)CropRadiataTranspirationDeficit irrigationPhotosynthesisIrrigation managementBotanyEcology

Abstract

fetched live from OpenAlex

Abstract As water for irrigation purposes becomes increasingly scarce because of climate change and population growth, there is growing interest in regulated deficit irrigation (RDI) as a way to improve efficiency of water usage and farm productivity in arid and semi‐arid areas. Salinity is also becoming an important problem in these same regions. Experiments were performed to investigate the effects of RDI and salt stress on two legumes crops, common bean ( Phaseolus vulgaris L.) and mungbean ( Vigna radiata (L.) Wilczek); previous work showed contrasting responses to RDI by these two crops under field conditions. The seed and biomass yields of both crops were reduced as a result of increasing water deficit stress; however, mungbean was able to maintain the same proportion of its biomass in reproductive structures and maintain its harvest index under stress, whereas common bean’s decreased. In addition, photosynthesis in mungbean was higher than in common bean and higher at the same levels of transpiration. Finally, salinity stress did not affect the water potential, harvest index or the specific leaf weight of either crop. There were no interactions between salinity and crops or RDI levels, which suggest that the two crops do not differ in their response to salinity stress, and that RDI levels do not modify this response.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.007
GPT teacher head0.209
Teacher spread0.202 · 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 designObservational
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

Citations26
Published2010
Admission routes2
Has abstractyes

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