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The influence of bird netting on yield and fruit, juice, and wine composition of <em>Vitis vinifera</em> L.

2013· article· en· W2287889717 on OpenAlex
Vinay Pagay, Andrew G. Reynolds, K. Helen Fisher

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 · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsUniversity of GuelphBrock University
Fundersnot available
KeywordsNettingWineVeraisonYield (engineering)Composition (language)VineTitratable acidBerryHorticultureChemistryFood scienceVitis viniferaWinemakingPolyphenolBotanyBiologyArtMaterials scienceEconomicsBiochemistry

Abstract

fetched live from OpenAlex

<p style="text-align: justify;"><strong>Aims</strong>: To investigate the impact of semi-permanent bird netting and timing of its application on Cabernet franc grapevine yield components and fruit, juice, and wine composition.</p><p style="text-align: justify;"><strong>Methods and results</strong>: Semi-permanent bird netting was installed over Cabernet franc grapevines at various times – post-bloom, bunch closure, and veraison – of the 2004 growing season in the Niagara Peninsula of Canada. At harvest, vine yield components were measured followed by berry and must compositional analysis of soluble solids, pH, titratable acidity (TA), color, and polyphenols. Wines made from these grapes were also analyzed (pH, TA, color, and polyphenols). It was found that installation of bird netting over grapevines had minimal effect on yield components and berry composition regardless of when the nets were installed. Must composition revealed significant decreases in soluble solids, pH, and color as a result of the netting, the least impact being when the nets were applied at post-bloom. Wine composition was similar to the must data with the netted treatments resulting in lower pH, higher TA, and decreased color. Total anthocyanins and polyphenols were slightly reduced as a result of the netting.</p><p style="text-align: justify;"><strong>Conclusions</strong>: Minimal impact of bird netting on yield, fruit, must and wine quality is a positive finding since netting is becoming more prevalent in vineyards worldwide due to changing migratory patterns of birds. It is recommended that netting be applied around post-bloom for the ease of application, to minimize shading effects, which could lead to decreased fruit quality, and to maintain yield.</p><p style="text-align: justify;"><strong>Significance and impact of the study</strong>: Use of bird netting is becoming more prevalent by grape growers worldwide due to changing migratory patterns of birds that feed on grapes. This study shows that bird netting is not detrimental to yield and fruit and wine quality especially when applied early in the growing season.</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 score0.961
Threshold uncertainty score0.241

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 head0.023
GPT teacher head0.240
Teacher spread0.217 · 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