MétaCan
Menu
Retour à la cohorte
Enregistrement W2355490321

Effects of the planting environment of lawn brick with fly-ash medium on the growth of turfgrass

2003· article· en· W2355490321 sur OpenAlexaff
Zheng Hai

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueTurfgrass Adaptation and Management
Établissements canadiensCAE (Canada)
Organismes subventionnairesnon disponible
Mots-clésLawnFly ashSowingBrickEnvironmental scienceLolium multiflorumEnvironmental engineeringAgronomyEngineeringWaste managementEcologyCivil engineeringBiology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

As our environmental awareness strengthened and living standard improved, demand for green parking lots and lawn roadside is enhancing. But the increasing acrea ge of buildings, dams and roads conflicts with the development of lawn in modern cities. In order to settle this contradiction, making full use of lawn bricks b ecomes necessary. Based on the fact that the optimal ratio of fly ash and soil a s lawn medium has been found, this experiment probes into the fertilizing and bi ological effects of lawn bricks with mixed medium of soil and fly ash in their h oles. In order to analyze the brick hole environment, the experiment also desig ns two kinds of contrastive planting environment, one is soil hole environment, the other is mixed environment of soil and fly ash. The soil hole environment has the same holes as lawn bricks, and is infilled by mixed medium of soil and f ly ash. On the surface of the mixed environment of soil and fly ash, four circle s having the same size as the holes in lawn bricks have been lined out. The pot experiment was conducted in March 11 of 2002, which was composed of 3 tr eatments including brick hole environment, soil hole environment and the mixed environment of soil and fly ash. Perennial ryegrass(Lolium multiflorum L. cv, Barmultra) were planted in the holes and circles of different planting env ironment. Each treatment was replicated twenty forth times. The experiment was carried out in the green house, and its purpose was to study and appraise water holding capacity and nutrient supplying capability of the three kinds of plan ting environment, also to investigate their influences on the growth and quality of turfgrass. The results show that, turfgrass tissue under brick hole environment has higher contents of nutrient elements. Its contents of N, K, Na, Cu, Zn are respectivel y 0 073, 0 5517, 0 5263, 4 1287, 1 4044 times higher than those under soil hole environment, and 0 103, 0 3513, 0 5037, 1 695, 0 911 times higher th an those under the mixed environment. Their differences are obvious (P0 05 ). According to the above results, the brick hole environment can benefit plant s greatly. Furthermore, the contents of Fe, Cu and Zn in turfgrass tissue under brick hole environment are far higher than the fitting needs, so it unnecessary to supply iron, copper and zinc fertilizer as usual. It also proves that the br ick hole environment has lowest evaporation rate and highest medium water conte nt. So it has long time water holding capacity to effectively lift the menace of high temperature on turfgrass. In a word, the brick hole environment helps t urf especially the cold season turf go over summertime easily. During the whole growing seasons, the clipping yield of turfgrass under soil hole environment i s higher than that under brick hole environment, but the difference isn't notab le (P 0 05). The clipping yield of turfgrass under mixed environment is lo west. After summertime, the qualities of turfgrass under different planting envi ronment are evaluated. The turf quality under brick hole environment is the bes t and its synthesized score is 3 708, the turf quality under soil hole environ ment, 2 637 scores, the turf quality under the mixed environment, only 2 318 s cores. The diversity of turf grass between the forth and the two later is notabl e (P0 01). Lawn bricks with fly ash medium in their holes used as an environment for lawn growth, can not only increase the acreage of lawn, but also solve the fly ash ou tlet problem.

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 candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,231
Score d'incertitude au seuil0,446

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 technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,004
Tête enseignante GPT0,149
Écart entre enseignants0,145 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

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

En bref

Citations0
Publié2003
Routes d'admission1
Résumé présentoui

Explorer davantage

Même sujetTurfgrass Adaptation and ManagementTravaux en français237 207