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Record W4323664223 · doi:10.3390/plants12061233

Indoleamines Impart Abiotic Stress Tolerance and Improve Reproductive Traits in Hazelnuts

2023· article· en· W4323664223 on OpenAlexaffabout
Murali‐Mohan Ayyanath, Mukund R. Shukla, Praveen K. Saxena

Bibliographic record

VenuePlants · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Reproductive Biology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCultivarCuttingAbiotic componentBiologyAbiotic stressAdaptation (eye)HorticultureBotanyEcology

Abstract

fetched live from OpenAlex

Hazelnuts have recently gathered tremendous attention due to the expansion of the confectionary industry. However, the sourced cultivars fail to perform in initial phase of cultivation as they enter bare survival mode due to changes in climatic zones, for example, Southern Ontario, where the climate is continental, as opposed to the milder climate in Europe and Turkey. Indoleamines have been shown to counter abiotic stress and modulate vegetative and reproductive development of plants. Here, we examined the effect of indoleamines on the flowering response of the dormant stem cuttings of sourced hazelnut cultivars in controlled environment chambers. The stem cuttings were exposed to sudden summer-like conditions (abiotic stress) and the female flower development was assessed in relation to endogenous indoleamine titers. The sourced cultivars responded well to serotonin treatment by producing more flowers compared to the controls or other treatments. The probability of buds resulting in female flowers was highest in the middle region of the stem cuttings. It is interesting to note that the tryptamine titers of the locally adapted, and N-acetyl serotonin titers of native hazelnut cultivars, provided the best explanation for adaptation to the stress environment. Titers of both compounds were compromised in the sourced cultivars which resorted mostly to serotonin concentrations to counter the stress. The indoleamines tool kit identified in this study could be deployed in assessing cultivars for stress adaptation attributes.

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 score0.484
Threshold uncertainty score0.614

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 head0.011
GPT teacher head0.247
Teacher spread0.235 · 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

Citations8
Published2023
Admission routes2
Has abstractyes

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