Exploratory analysis in the evaluation of stress due to aluminum presence in Physalis angulata L. and multielement determination by microwave-induced plasma optical emission spectrometry (MIP OES).
Claudia B de AbreuMarcos de O RibeiroCyndi S PinhoCandice N CarneiroAndré D de Azevedo NetoManuela O de SouzaFabio de S DiasPublished in: Environmental science and pollution research international (2020)
The present work aimed to analyze the mineral nutrition of Physalis angulata L. under stress by aluminum in the nutrient solution. The treatments consisted of five different concentrations of aluminum in the nutrient solution (0, 0.04, 0.08, 0.12, and 0.16 mmol L-1) in the AlCl3 form. The plants were exposed to Al for 30 days. Subsequently, nutritional and aluminum analyses were performed on plant tissue. The data were submitted to analysis of variance (p < 0.05), and, in case of significance, the regression study was performed as well as hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used. The formation of four groups occurred, where we can observe the similarity and differences in the treatments between them. The separation of the treatments into groups reflected the heterogeneity of the treatments about the aluminum levels in the nutrient solution, evidencing its phytotoxicity level in Physalis angulata plants. Among the analyzed variables, P, K, Ca, Mg, Fe, Mo, and Zn were the most influential ones demonstrated by principal component analysis (PCA). The stress of 0.16 mmol L-1 of Al increased the phosphorus contents in the stems and roots and the potassium, copper, and molybdenum contents in all parts of the plants. In contrast, Al reduced the levels of calcium, magnesium, iron, and zinc in P. angulata plants. Iron being the micronutrient that showed the largest reduction, followed by zinc in the leaves. The highest levels of aluminum were found in the roots.
Keyphrases
- oxide nanoparticles
- high resolution
- stress induced
- physical activity
- magnetic resonance
- solid state
- mass spectrometry
- magnetic resonance imaging
- computed tomography
- risk assessment
- heavy metals
- endothelial cells
- big data
- diabetic rats
- high speed
- solid phase extraction
- radiofrequency ablation
- artificial intelligence
- metal organic framework
- sewage sludge