The contamination of water and soil by arsenic (As) is a global environmental, health, and agricultural issue. The study of As toxicity in plants and its interaction with nutrients requires special attention. We investigated the impact of low concentrations of As on poplar callus and the effectiveness of silicon (Si) in the alleviation of As stress. We focused on the effects of As and/or Si on the concentration of nutrients and its relationship with other parameters studied: callus growth, the concentration of photosynthetic pigments, and the accumulation of As. Using a correlation matrix heatmap we revealed the associations between the above-mentioned parameters. The principal component analysis (PCA) was used to show the variability between the treatments (control, Si, As, As + Si) and the time stages (short and long cultivation). The concentrations of photosynthetic pigments were impacted extremely by both the As and the As + Si treatments. The nutrient balance was heavily disrupted by As but considerably improved by Si. The PCA revealed a strong correlation among growth, photosynthesis pigments, K, Zn, and Mn. We analysed the data from the literature that specified the changes in the concentrations of nutrients and growth induced by As, and compared them with our results. This heatmap analysis revealed the similarity between poplar callus and sensitive plants.
The principal component analysis showed that the variability between the short and long cultivation in the As and/or Si treatment was high in callus growth, nutrient, and chlorophyll concentrations.
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This work was supported by the Slovak Research and Development Agency, Contract No. APVV-17-0164. The authors thank MSc. Matej Holek, for the graphical edit of Supplementary Fig. S1.
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Kučerová, D., Vivodová, Z. & Kollárová, K. Silicon alleviates the negative effects of arsenic in poplar callus in relation to its nutrient concentrations. Plant Cell Tiss Organ Cult (2021). https://doi.org/10.1007/s11240-020-02007-w
- Correlation matrix heatmap
- Photosynthetic pigments
- Principal component analysis