Comparison of Sampling Methods for Estimating Seed Bank and Weed Population Densities during the Growing Season
Notice bibliographique
Résumé
In order to compare sampling methods for estimating the populations of the seed bank and the populations of weed seedlings during the growing season in the field, an experiment was conducted in the research field of the Agriculture college of Karaj in the cropping year of 2007. In this experiment, sampling of the seed bank was carried out first at the start of the growing season. Then, during the growing season, the weed populations were sampled in 96 points using the networking method, and their means were considered as the base and the real means of the populations of the weeds. Next, to compare other methods with the networking method, sampling was carried out using the systematic, the diagonal, and the random methods, and then the variance of error of each method was calculated and compared with that of the networking method in the format of factorial using a completely randomized design. The first factor studied, the species of weeds, included the three species of grasses, Amaranthus, and Portulaca. The zigzag, the diagonal, and the random sampling methods constituted the second factor. Results relating to the seed bank and those concerning the populations of the weeds were different from each other. The results obtained showed that the suitable method for each species differed according to the different distribution patterns of the weed species in the field. In the seed bank, there were no significant differences among sampling methods for any of the species, but the random method for grasses and Portulaca showed the least error in predicting weed populations. Altogether, among the sampling methods used for Amaranthus, there were no differences in accuracy. Concerning the populations of weed seedlings, the random method for broadleaf weeds (Amaranthus and Portulaca), and the zigzag method for grasses, were the best. As for the seed bank, the variance of error of all the methods decreased with an increase in the number of samples taken; and when more than 15 samples were taken, this trend of decrease in the variance of error stabilized and no more reduction in error was observed. Regarding the populations of the weeds, no trend was found between the number of samples taken and the variance of error.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».