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Record W2496135721 · doi:10.5539/mas.v10n11p8

Evapotranspiration and Yield of Eggplant under Salinity and Water Deficit: A Comparison between Greenhouse and Outdoor Cultivation

2016· article· en· W2496135721 on OpenAlexvenueno aff
Ali Asghar Ghaemi, Mohammad Rafie Rafiee

Bibliographic record

VenueModern Applied Science · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsGreenhouseEvapotranspirationEnvironmental scienceSalinityIrrigationGrowing seasonCrop coefficientYield (engineering)AgronomyBiology

Abstract

fetched live from OpenAlex

Cultivation environment can be effective on the degree of limitations in crop evapotranspiration and yield, as a result of water shortage and salinity. The purpose of this study was to determine and compare the impact of different irrigation regimes (daily, weekly and every two weeks) combined with different water salinities (0.8, 2.5, 5.0 and, 7.0 dS m-1) on eggplant yield (Y) and evapotranspiration (ETc) in outdoor and greenhouse cultivation. Daily ETc values were measured by diurnal weighting of microlysimeters throughout the growing season (from May 19th to September 5th, 2012 and June 1st to September 22nd, 2013) placed in a plastic greenhouse and outdoor basins. Measurements showed apparent variations between different irrigation regimes×water salinity treatments, during the early growing season in both years. Both water deficit and salinity factors had significant effects on ETc, ECe, Y, fruit diameter and shoot dry weight in both environments. The applicability of Doorenbos-Kassam linear crop-water production function along with Maas-Hoffman salt tolerance model was investigated in the greenhouse and outdoor conditions. The Ky coefficient obtained for outdoor and greenhouse eggplants treatments were 0.97 and 1.03 in the first year and 0.91 and 0.93 in the second year, respectively. Higher sensitivity of greenhouse eggplants to salinity was later demonstrated for both years, obtaining higher values of b and lower values of ECethreshold in the greenhouse eggplants.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.704
Threshold uncertainty score0.213

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 studies0.0000.001
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 head0.026
GPT teacher head0.232
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 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

Citations11
Published2016
Admission routes1
Has abstractyes

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