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Record W77194040 · doi:10.17221/3433-pse

Hot pepper response to interactive effects of salinity and boron

2006· article· en· W77194040 on OpenAlexaff
Supanjani Supanjani, K.D. Lee

Bibliographic record

VenuePlant Soil and Environment · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Micronutrient Interactions and Effects
Canadian institutionsMcGill University
Fundersnot available
KeywordsSalinityPepperAPXChemistryHorticultureAgronomyAntioxidantBotanyBiologyCatalaseFood scienceEcologyBiochemistry

Abstract

fetched live from OpenAlex

An excess of salinity and boron (B) can limit production of hot pepper (Capsicum annuum L.), but little is known about the physiological responses, including antioxidant activities, in response to these excesses. We investigated the physiological responses and defense mechanisms of hot pepper grown under salinity (NaCl) stress at 3 and 6 dS/mand B stress at 15 and 30 mg/kg. Dry weight and the total chlorophyll content decreased with increasing salinity and B levels. The toxic effect of B was greater under saline conditions. Higher levels of salinity and B resulted in increased B concentrations in leaves. The stomatal resistance values increased as the combined levels of salinity and B increased. Furthermore, increasing salinity, B or both increased activities of H2O2, SOD, POX, APX and GR, which increased oxidative stress, compared to the control plants. Increases in combined salinity and B levels disrupted plant nutrient balance and water use, and induced production of secondary toxic substances leading to an increased plant tissue concentration of H2O2, and suppression of growth in hot pepper.

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 score0.001
Threshold uncertainty score0.004

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 integrity0.0000.001
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 head0.005
GPT teacher head0.172
Teacher spread0.167 · 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

Citations64
Published2006
Admission routes1
Has abstractyes

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