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Record W2997188441 · doi:10.5424/sjar/2019174-15380

Foliage applications of jasmonic acid modulate the antioxidant defense under water deficit growth in sugar beet

2019· article· en· W2997188441 on OpenAlexaff
Hamideh Ghaffari, M. R. Tadayon, Muhammad Nadeem, Jamshid Razmjoo, Mumtaz Cheema

Bibliographic record

VenueSpanish Journal of Agricultural Research · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Stress Responses and Tolerance
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSugar beetJasmonic acidSugarCatalaseMalondialdehydeHorticultureAntioxidantPeroxidaseBiologyAgronomyChemistryBotanyFood scienceSalicylic acidEnzymeBiochemistry

Abstract

fetched live from OpenAlex

Aims of study: Water deficit (WD) is becoming an alarming problem in many regions of the world. Jasmonic acid (JA) is considered an important intracellular plant growth regulator. The aim of the current research was to investigate the important role of JA in mitigating the negative effects of WD on plant growth.Area of study: Sugar beet production systems of two locations in Chaharmahal-Bakhtiari province, Iran.Material and methods: A field trial was conducted to assess the foliar applications of JA (0, 5 µM and 10 µM) and WD (50%, 75%, 100% plant water requirements) effects on physiological yield components of sugar beet (Beta vulgaris L.) plants.Main results: WD significantly (p<0.05) increased catalase, ascorbate and peroxidase activities, and malondialdehyde, hydrogen peroxide and white sugar content (WSC); however, it caused a reduction in white sugar yield and root yield (RY). JA foliage applications further enhanced the enzymes activity in WD treated plants resulting in higher WSC, potassium concentrations, white sugar and final RY. Interestingly the effects of JA applications were more pronounced under severe WD (50%) compared to mild (75%) or well-watered plants (100%). JA (10 µM) foliage applications increased the RY and white sugar production by 21% and 24% under severe WD.Research highlights: JA can ameliorate the adverse effects of WD and increase the WD tolerance of sugar beet crop by upregulating the antioxidant enzyme activities to withstand adverse environmental conditions.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.913
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.272
Teacher spread0.242 · 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

Citations50
Published2019
Admission routes1
Has abstractyes

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