IMPACT OF CONVENTIONAL AND PRECISION CATTLE MANURE APPLICATION METHODS ON HORMONE CONCENTRATIONS AND ACTIVITIES IN SURFACE WATER AND SOIL
Notice bibliographique
Résumé
Worldwide, agricultural activities such as animal production have intensified to supply nutrients for the growing human population. To satisfy nutritional demands, sustainable strategies must be implemented to enhance agricultural outputs and manage resulting by-products, while securing agricultural and environmental system viability. Intensive animal production can generate vast quantities of animal manure that is concentrated within relatively limited areas. Managing manure is challenging, but management often involves applying manure to agricultural lands. Applying manure to land recycles valuable nutrients and organic matter beneficial for producing crops. However, manure-borne pollutants, such as hormones, can threaten water and soil quality. Specifically, hormones can be readily exported in surface runoff water from manured fields to ecosystems. This thesis compared conventional and precision manure application strategies to determine if either method contributed hormone concentrations and activities to water and soil. For this watershed-scale study, a previously unmanured cropland field adjacent to the University of Saskatchewan Beef Cattle Research and Teaching Unit was used for a study established in 2018. Within the field, three treatment zones of approximately 40 acres each were set up. The three treatments were 1) commercial fertilizer (no manure), 2) conventional, also termed traditional, cattle manure application at constant rate with no setbacks from watershed basin centers, and 3) precision cattle manure application at variable rate with no manure applied in basin centers. During 2019, snowmelt, rainfall runoff, and soil was collected from nine watershed basins within the three field treatment zones. Manure source material was also directly sampled from the windrow pile used for field treatments in May of 2019. In 2021, fecal rectal grabs, pen floor manure, and windrow pile manure were also collected from the cattle feedlot facility where manure was obtained for field treatments. Chemical analyses were combined with in vitro reporter gene assays to assess hormone concentrations and activities in environmental samples and manure materials. Targeted hormonal growth promoting chemicals, and corresponding metabolites, were identified and quantified by liquid chromatography ultra-high resolution mass spectrometry, while hormone activities were assessed by in vitro bioassays. Targeted analytes included trenbolone acetate, 17α-trenbolone, 17β-trenbolone, trendione, melengestrol acetate, and melengestrol. No target analyte concentrations were detected in any water, soil, or windrow pile manure. Fresh rectal feces contained 17α-trenbolone and 17β-trenbolone, while pen floor manure contained 17α-trenbolone. Hormone activities assessed included (anti-)androgenic/glucocorticoid activity and (anti-)estrogenicity. Fresh and pen materials both contained androgenic/glucocorticoid activity, and (anti-)estrogenicity. In contrast, windrow manure samples (collected in 2019, and 2021) were mostly estrogenic and lacked androgenic/glucocorticoid activity. All pre- and post-manure application water samples (snowmelt, and rainfall runoff) were estrogenic. Estrogenic potency was increased in rainfall runoff after conventional application. In contrast, estrogenic potency did not increase in rainfall runoff after precision application. No hormone activities were detected in soil samples collected late August of 2019. Increased estrogenicity in rainfall runoff from the conventional application likely originated from windrow manure uniformly applied across the field, which included the watershed basin centers. These results indicate precision manure application, with setbacks, may protect water from hormone entry. Precision application may be particularly effective if runoff occurs after recent manure-amendment, or before hormones dissipate in manured soils. This thesis supports precision manure application as a viable method to help mitigate hormone export from manure-amended soils to sensitive systems.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».