The Toxic Effect of Drug Residues on the Germination of Cultivated Plants
Notice bibliographique
Résumé
Over the past decades, industrial development has led to the identification of several new chemicals in the aquatic environment, which are pollutants of growing concern for water management.These compounds are referred to as "emerging contaminants (ECs)", micropollutants (MPs) or trace organic compounds (TrOCs) [1].In nature, these pollutants are synthetic or naturally occurring contaminants, most of which are of organic origin and typically occur in trace amounts.As emerging micropollutants, their detection in water is difficult and their long-term ecological and health effects are not yet known.In many cases, they have been shown to have known or suspected adverse effects on the aquatic environment or human health [2].Organic micropollutants cannot be fully removed by conventional wastewater treatment processes and therefore accumulate through biomagnification and are spread through the food chain [3].Because drugs are designed to perform different physiological and biochemical functions, they can penetrate biological barriers and persist stably in the human body.Antibiotics used in food (milk, meat, eggs, fruit, vegetables and fish) as growth promoters, therapeutic and preventive agents can pose ecological and health risks if released into the environment [4,5].Globally, pharmaceuticals and their metabolites have been detected in wastewater, groundwater and even drinking water [6].Contamination levels of antibiotics in wastewater can reach 10-100 mg/L, but the majority of reports have shown levels in the ng-g/L range, and water in this form cannot be used in agriculture [7].The main objective of this study is to investigate the toxic effects of pharmaceuticals (tetracycline and ampicillin) on germination through standard tests such as germination, growth, morphological/anatomical changes of the germ.White mustard (Sinapis alba) and lettuce (Lactuca sativa) were used as model plants.Our experiment was performed on seeds (25 seeds) placed on filter paper in sterilized Petri-dishes.Samples were germinated for 72 hours in the dark at T= 202 o C on solutions of different initial concentrations of analytical grade and commercially used ampicillin and tetracycline (5-5 mL, 0-10 g/L).Our tests were carried out in 6 replicates.Seedling growth inhibition (SGI), relative germination, relative root growth and germination index were calculated.The morphology was studied and compared by microscopy.
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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) | 0,000 | 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 ».