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Effect of different irrigation strategies on vine physiology, yield, grape composition and sensory profiles of <em>Vitis vinifera</em> L. Cabernet-Sauvignon in a cool climate area

2014· article· en· W2281201802 on OpenAlex
Gabriel Balint, Andrew G. Reynolds

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueOENO One · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsBrock University
Fundersnot available
KeywordsVeraisonIrrigationDeficit irrigationVineTranspirationWineHorticultureComposition (language)EvapotranspirationAgronomyChemistryVitis viniferaBiologyBotanyPhotosynthesisFood scienceIrrigation managementEcology

Abstract

fetched live from OpenAlex

<p style="text-align: justify;"><strong>Aim</strong>: The efficacy of partial root zone drying (PRD) and regulated deficit irrigation (RDI) on vine physiology, yield components, fruit composition and wine sensory profiles of ‘Cabernet-Sauvignon’ was investigated in a cool climate region in Ontario, Canada.</p><p style="text-align: justify;"><strong>Methods and results</strong>: Field experiments were conducted in a Cabernet-Sauvignon block in Niagara-on-the-Lake, ON Canada between 2006 and 2008. There were five treatments : non-irrigated control, PRD, full irrigation [100 % of crop evapotranspiration (ET<sub>c</sub>)] and two levels of RDI (50 and 25 % ET<sub>c</sub>). Treatments started immediately after fruit set and continued until post-veraison. Soil and vine water status were apparently controlled not only by the amount of water but also by the irrigation strategy used. In the PRD treatments, soil moisture, leaf water potential, and transpiration rate were generally lower than in 100 % ET<sub>c</sub> but higher than non-irrigated and RDI treatments. Almost all treatments were different than in non-irrigated vines in fruit composition and wine sensory attributes. Wine sensory attributes differed considerably due to the amount of irrigation water applied in 2007. RDI strategies were more consistent than the PRD treatments in their effect on vine water status, grape composition and wine sensory profiles. Inconsistent patterns across seasons for some variables indicated that besides soil and vine water status, there were other factors that impacted vine physiology, yield components and berry composition.</p><p style="text-align: justify;"><strong>Conclusions</strong>: RDI treatments improved wine quality when compared with full or either non-irrigated treatments. Overall, use of RDI irrigation or PRD during dry and warm years can improve grape composition in cool climates.</p><p style="text-align: justify;"><strong>Significance and impact of the study</strong>: To the best of our knowledge, this is the first evaluation of PRD and RDI on Cabernet-Sauvignon in a cool humid climate. It suggests that although RDI strategies are more effective, PRD also has value, particularly in dry seasons.</p>

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.

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 score0.704
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.022
GPT teacher head0.252
Teacher spread0.230 · 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