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Record W4386295555 · doi:10.1111/ppl.14005

The physiology of drought stress in two grapevine cultivars: Photosynthesis, antioxidant system, and osmotic regulation responses

2023· article· en· W4386295555 on OpenAlexaff
YiLing Lin, Siyu Liu, Xiang Fang, Yanhua Ren, Zhijie You, Jiaxin Xia, Abdul Hakeem, Yuxian Yang, Lingyu Wang, Jinggui Fang, Lingfei Shangguan

Bibliographic record

VenuePhysiologia Plantarum · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsMinistry of Agriculture
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsKey Technology Research and Development Program of ShandongNatural Science Foundation of Jiangsu ProvinceNanjing Agricultural UniversityGovernment of Jiangsu Province
KeywordsBiologyCultivarDrought toleranceDrought stressPhotosynthesisMalondialdehydePlant physiologyOsmotic shockBotanyAntioxidantGeneHorticulturePhysiologyGeneticsBiochemistry

Abstract

fetched live from OpenAlex

Drought stress impedes viticultural plant growth and development by modifying various metabolic pathways. However, the regulatory network response underlying drought stress is not yet clear. In this study, the leaves and roots of "Shine Muscat" ("SM," Vitis labruscana × Vitis vinifera) and "Thompson Seedless" ("TS," V. vinifera L. cv.) were subjected to drought stress to study the regulatory network used by drought stress. Morphophysiological results showed that the malondialdehyde content after 28 days of drought stress increased more significantly in "TS" than "SM." Furthermore, the multiomics analysis studies showed that a total of 3036-6714 differentially expressed genes and 379-385 differentially abundant metabolites were identified in "SM" and "TS" grapevine cultivars under drought stress. Furthermore, the retained intron was the major form of differential alternative splicing event under drought stress. The photosynthesis pathway, antioxidant system, plant hormone signal transduction, and osmotic adjustment were the primary response systems in the two grapevine cultivars under drought stress. We have identified GRIK1, RFS2, and LKR/SDH as the hub genes in the coexpression network of drought stress. In addition, the difference in the accumulation of pheophorbide-a reveals different drought resistance mechanisms in the two grapevine cultivars. Our study explained the difference in drought response between cultivars and tissues and identified drought stress-responsive genes, which provides reference data for further understanding the regulatory network of drought tolerance in grapevine.

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 score0.896
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.027
GPT teacher head0.277
Teacher spread0.251 · 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

Citations20
Published2023
Admission routes1
Has abstractyes

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