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Enregistrement W7056751619

Greenhouse Cooling.

2017· article· en· W7056751619 sur OpenAlexaboutno aff

Notice bibliographique

RevueOakTrust (Texas A&M University Libraries) · 2017
Typearticle
Langueen
DomainePhysics and Astronomy
ThématiqueMagnetic confinement fusion research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGreenhouseProduction (economics)Yield (engineering)Water coolingQuality (philosophy)
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Experiments started at College Station in 1949 show that the wet-pad exhaust fan system gives the most effective cooling of greenhouses for Texas conditions.This type of greenhouse cooling is practical.economical and efficient.Year-round production is possible, with more accurate timing, greater yields and higher quality.Installations made by commercial growers of florist and nursery crops in Texas show that the wet-pad exhaust fan system reduces labor costs and increases the quantity and quality of crops produced each year.Overall results are better market returns, improved working conditions, reduced water requirements and more consistent yields throughout the year.The use of this cooling system extended the production periods and improved the quality and yield of the following crops: chrysanthemums, geraniums, snapdragons, kalanchoes, begonias, hydrangeas, lilies, poinsettias, azaleas, gloxinias and foliage plants.The following crops also were produced successfully, were timed accurately and brought a high market return: calceolarias, cinerarias, stocks, primroses, carnations and tuberous-rooted begonias.Extensive use of the wet-pad exhaust fan system of greenhouse cooling throughout the United States and in many other areas of the world during the past 3 years has shown that it is practical in nearly every climate.Since the origination of this system, more than 25 million square feet of greenhouse area have bee.n cooled in various sections of the United States and Canada alone.Automatically controlled systems are the nearest approach to ideal growing conditions for greenhouse production with lower production costs.Cooling equipment properly used will make production easier and will give the grower more control over his crops.The system is economical to install and operate, and is considered a sound investment by all commercial growers who have installed it.Flower size has increased and flower color retention has been improved with the use of greenhouse cooling.Feeding programs have been increased with the use of cooling.More rapid and vigorous growth ofte.nhas required increased rates and frequency of fertilizer applications.Disease problems have been reduced by the conditions provided by this system.This type of cooling is efficient and practical in areas having high relative humidity.Proper management of the equipment in these areas has shown even greater gains than in some areas of low relative humidity.The effect on working morale of greenhouse employees has bee.n an important factor in improving quality as well as better climatic effects on crops.Greenhouse cooling is an advantage during the night as well as during the day.On many crops and in many areas, cool night temperatures are of greater importance than cool day temperatures.Examples of some eUects on florist crop production in Texas are: CHRYSANTHEMUMS-Production of year-round crops of high quality now possible with no delay in blooming or no distortion of flowers.CARNATIONS-Production in areas where this crop has' been tried unsuccessfully without cooling can now be practiced profitably with high quality production throughout the year.SNAPDRAGONS-Can now be produced on year-round basis in all areas with recently developed summer varieties.ASTERS-Can now be produced as a high quality crop on a year-round basis in the same manner as chrysanthemums.OTHERS-Better response and higher quality on all pot plant crops, including those considered as winter crops, such as poinsettias, lilies and hydrangeas.On the cover are potted chrysanthemums which flowered in August in a cooled greenhouse.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,796
Score d'incertitude au seuil0,840

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,2080,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,015
Tête enseignante GPT0,220
Écart entre enseignants0,206 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2017
Routes d'admission1
Résumé présentoui

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