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Record W2111164695 · doi:10.5539/ijb.v1n2p87

Effects of Waterlogging on Growth and Physiology of Hopea odorata Roxb

2009· article· en· W2111164695 on OpenAlexvenueno aff
Hazandy Abdul Hamid, Nor Aini Ab Shukor, Sapari Mat, Abdul Latib Senin, Kamaruzaman Jusoff

Bibliographic record

VenueInternational Journal of Biology · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to water stress
Canadian institutionsnot available
Fundersnot available
KeywordsWaterlogging (archaeology)Stomatal conductancePhotosynthesisHorticultureBiologyBiomass (ecology)BotanyAgronomyEcology

Abstract

fetched live from OpenAlex

This study examines the growth and physiological characteristics of Hopea odorata growing under waterloggingcondition. H. odorata was selected as it is widely planted as urban landscape tree species which experienced some growthstresses. Two waterlogging treatments and a control were designed. Forty 5-year old saplings each were subjected towaterlogged condition for 30 days which were then allowed to recover for a further 30 days as Treatment 1 (T1) andwaterlogged condition for 60 days as Treatment 2 (T2). Aboveground and belowground biomass including leaf area wasdetermined before and at 30 and 60 days of study. The net photosynthesis (Anet), stomatal conductance (Gs), transpirationrate per unit leaf area (EL) and leaf to air vapour pressure deficit (????W) were assessed weekly for 60 days. The resultsshowed that there were no significant differences between treatments for all growth attributes. There were also nosignificant reductions of these attributes found within treatments throughout the experimental period. Furthermore, nosignificant effects were observed in gas exchange variables. The results demonstrate that severe waterlogged conditiondid not affect the physiology of H. odorata. These findings add to the increasing evidences that H. odorata is a flood aswell as a pollution tolerance species that ensuring it to survive and grow well in urban areas by regulating the partitioningstrategies.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.106

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 head0.008
GPT teacher head0.230
Teacher spread0.222 · 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

Citations7
Published2009
Admission routes1
Has abstractyes

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