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Record W2105838254 · doi:10.5539/ep.v3n4p1

Assessment of Adaptive Capacity of Leaves and Roots of Golf Grass Plant Irrigated by Reclaimed Wastewater

2014· article· en· W2105838254 on OpenAlexvenueno aff
Hind Mouhanni, Brahim Boudinar, Abdelaziz Bendou

Bibliographic record

VenueEnvironment and Pollution · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsnot available
Fundersnot available
KeywordsIrrigationWastewaterEnvironmental scienceNutrientAgronomyDry weightReclaimed waterAgricultureAridBiologyEnvironmental engineeringEcology

Abstract

fetched live from OpenAlex

The actual potential of reclaimed wastewater discharged into the bay of Agadir (south Morocco), is 3.65 million m3/year. This important volume is a significant loss for irrigation in this region characterized by semi-arid climate and a long-suffering of over-exploitation of groundwater. This situation is against to the increasing scarcity of water resources and the quality degradation in the entire region. The production capacity of M’zar plant available for irrigation purpose without any restrictions (category A of WHO norms), is of about 10 000 m3/day and will reach 50 000 m3/day in the medium term. This production capacity of treated wastewaters will fulfill the whole water needs for irrigation of the entire open spaces of Agadir. Our study is focused on the assess of adaptive capacity of leaves and roots of golf grass plant irrigated by reclaimed wastewater. It presents the planning, protocol and the results of tests conducted to evaluate the effects of TWW reuse on the growth of leaves and roots of grass plant. The results presented involve monitoring of fresh and dry weight of leaves and roots during the first 41 days of growth of three varieties of golf grass: Penccross (V1), the Ray Gras English (V2) and a mixture of 60% Ray Gras English and 40% Red Fescue. The results shown that irrigation with TWW has favored the evolution of the fresh and dry weight of leaves than the root of the grass plant. It’s due to nutrients elements content in the TWW and especially nitrogen compared with conventional irrigation with groundwater.

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 score0.845
Threshold uncertainty score0.118

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 head0.014
GPT teacher head0.190
Teacher spread0.175 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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