El cultivo del cerezo en España: producción, consumo e intercambios comerciales
Bibliographic record
Abstract
espanolSe realiza un analisis de los cambios experimentados por el cerezo en Espana durante las ultimas decadas, examinando las tendencias de superficies y producciones, para pasar despues a un analisis mas detallado de la innovacion varietal y de la tecnologia de produccion en las principales regiones productoras. Se analizan los intercambios comerciales y el consumo a lo largo de los ultimos anos. Espana es, segun el ano, el primer o segundo productor/exportador de cerezas dulces de la Union Europea, alternando con Italia el primer lugar. La diversidad de zonas de produccion proporciona un amplio periodo de aprovisionamiento de los mercados, que oscila entre mediados de abril en zonas extra–precoces hasta principios de agosto en las zonas mas tardias. El consumo muestra una tendencia creciente desde 1989. Se esta produciendo una importante renovacion varietal con la introduccion de nuevas variedades de Summerland (Canada), California (USA), Italia, Francia y Hungria que han alargado considerablemente el calendario de recoleccion. La innovacion tecnologica ha sido muy importante en lo referido a la tecnologia de produccion, adaptando de forma generalizada un sistema de formacion de media densidad como es el vaso de pequeno volumen (vaso espanol o vaso catalan). Destacable ha sido tambien la implementacion de una eficiente estructura de postcosecha y de los diferentes sistemas de certificacion y calidad, requeridos por los mercados de destino, liderados por Reino Unido y Alemania. EnglishThe Spanish changes in sweet cherry in recent decades, with especial importance to production areas, are exposed, describing the situation and trends concerning cultivars, rootstocks, training systems and cost of production. The import–export trade and the cherry consumption are analyzed. Spain is, depending on the season, the first or second largest producer/exporter of cherry in the European Union, alternating with Italy the first place. The different production areas provide an extended period of supply to markets, ranging from mid–April in early producing areas, to early August in the late areas. Consumption shows a constant increase since 1989. Technological innovation has been very important in particular with regard to new cultivars introduced from Summerland (Canada), California (USA), France, Hungary and Italy and training system development. The semi–intensive reduced goblet, also called “Spanish bush” or “Catalan bush”, with local modifications is the most popular in all the producing areas. The implementation of a modern post–harvest infrastructure has enabled to develop and apply the different protocols of certification required by the destination markets.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".