Effects of Soil Management on Wheat Composition
Notice bibliographique
Résumé
There is growing demand for locally and organically grown food. This demand has spurred efforts to produce flour and breads made from wheat grown locally in Maine. Unfortunately millers and bakers do not have access to enough locally grown organic wheat to meet their needs. New England farmers have a tremendous opportunity to discover ways to supply organic bread wheat for this rapidly growing market. In addition it is important to understand how soil management practices and genetics affect wheat's nutrient composition for human health and bread-making purposes. The fructan content, starch content, and gluten content and strength are important characteristics of bread quality. The oxygen radical absorbance capacity (ORAC) and free phenolic content have a potential impact on human health. The objectives of this research were to assess how wheat cultivar, soil management practices, and location impact bread-making and nutritional quality of wheat grown in Maine. The wheat was planted in a split-split plot design, with soil management as the main plot, wheat variety as the subplot, and the nitrogen fertilizer rate as the sub-subplot. Two cultivars were studied in this experiment - AC Barrie and AC Walton. Four soil treatments were evaluated: "amended" that received manure as a nitrogen (N) source, and non-amended that received synthetic fertilizer. Within the non-amended treatment, 4 rates of fertilizer were evaluated: 60, 75, 90, and 105 kg of N per hectare. Starch content, SDS sedimentation, fructan content, and phenolic content were all within expected ranges compared to previously published values. ORAC values on average were a little lower than other published data. No significant differences were seen in starch content, sedimentation volumes, fructan content, or ORAC values of wheat between cultivars or type of soil management treatment. This suggests that the increased organic matter and the slower release of N from the accumulated amendments of the amended plots, amount of inorganic nitrogen fertilizer added or cultivar tested did not significantly affect these parameters. There were significant differences seen between treatments for some of the phenolic acid measurements and these differences were due to the fact that as increased levels of nitrogen fertilizer were added to the wheat, phenolic acid levels were correspondingly lowered. Wheat crude protein content was negatively correlated with SDS sedimentation volumes, which indicates that as the protein levels of the wheat increased, the protein quality potentially decreased. The free phenolic content positively correlated with the ORAC values, indicating that the higher the phenolic content the more potential antioxidant capacity. Regression analysis of the amount of nitrogen added indicated that each increased amount of applied nitrogen fertilizer caused the protein content of the wheat to increase and the phenolic acid content of the wheat to decrease. However this increased protein content did not necessarily lead to increased breadmaking quality, and the higher levels of nitrogen fertilizer applied to increase crude protein content also simultaneously decreased one of the components beneficial to human health. Overall the data suggest that the cultivar and soil management treatment had little effect on the parameters measured.
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 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 | 0,000 | 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».