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Record W2139026703 · doi:10.5424/sjar/2010082-1198

Storage behaviour of ‘Reinette du Canada’ apple cultivars

2010· article· en· W2139026703 on OpenAlexaboutno aff
Marcos Guerra, J. B. Valenciano, V. Marcelo, Pedro A. Casquero

Bibliographic record

VenueSpanish Journal of Agricultural Research · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsnot available
FundersJunta de Castilla y León
KeywordsPostharvestCultivarTitratable acidHorticultureMalusCold storageControlled atmosphereChemistryBiology

Abstract

fetched live from OpenAlex

Apple (Malus domestica Borkh) cultivars ‘Reinette du Canada’ (RC) and ‘Reinette Grise du Canada’ (RG) have been declared throughout the European Community as protected designation of origin (PDO) ‘Manzana Reineta del Bierzo’. The aim of this research was to find out the influence of storage technique on quality of PDO apple cultivars ‘RC’ and ‘RG’, and to evaluate the absence of traditional post-harvest treatments in these high quality cultivars in order to reduce pesticide residues in fruit. Apples were kept in standard cold storage or in controlled atmosphere (CA). At harvest time and during storage, fruit from each treatment and storage technique was analysed to determine quality parameters as well as disorder incidence. CA storage has been useful to delay the maturity process of PDO apple cultivars ‘RC’ and ‘RG’ and to reduce the incidence of storage disorders. Apple cultivars had different behaviour so ‘RG’ cultivar showed lower weight loss (5.1%), shrivelling (6.4%) and bitter-pit (11%) than ‘RC’ cultivar (8.3%, 60.8% and 34%, respectively) at the end of storage. The response of both cultivars to the treatment was quite different, so ‘RG’ adapted better than ‘RC’ to the absence of postharvest treatments. Untreated ‘RG’ showed more brightness, total soluble solids (TSS) and TSS:titratable acidity values than treated ‘RG’, factors that could improve consumer acceptance. Effectiveness of postharvest treatment in terms of bitter-pit was lower in ‘RG’ than in ‘RC’. These results indicate that ‘RG’ would adapt better to storage without the use of chemical postharvest treatments.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.198

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.273
Teacher spread0.241 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations6
Published2010
Admission routes1
Has abstractyes

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