Salt Stress in Plants and Mitigation Approaches
Abstract
:1. Introduction
- Saline soils (ECe > 4 mS/cm, pHH2O < 8.5, and ESP < 15)
- Saline-alkaline or saline-sodic (ECe > 4 mS/cm, pHH2O < 8.5, and ESP > 15)
- Alkaline or sodic soils (ECe > 4 mS/cm, pHH2O > 8.5, and ESP > 15).
2. Neutral and Alkaline Salinity and Impacts to Plants
3. Sustainable Approaches and Solutions to Improve Plant Nutrition and Crop Production in Saline Conditions
4. Salinity Amelioration by Organic Amendments
5. Salinity and Plant–Microbe Associations
5.1. Salinity and Symbiotic Bacterial Associations
5.2. Salinity and Symbiotic Fungal Associations
6. Salinity and Nanotechnology-Based Solutions
7. Environmental Interaction(s) and Additive Effects of Salinity-Exposed Plants
8. Exploration of Salinization Processes by Artificial Intelligence and Machine Learning Approaches
9. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Neutral Salt Type | pH | Prevalent Ions (%) | Precipitated Forms |
---|---|---|---|
Sodium chloride NaCl | 7.94 | Na+ 98; Cl− 98 | Magnesite Dolomite Hydroxyapatite Calcite Huntite Vaterite Artinite |
Potassium chloride KCl | 7.94 | K+ 98; Cl− 98 | |
Magnesium chloride Mg Cl2 | 7.93 | Mg2+ 77; Cl− 98; Mg-OC 10; MgSO4 4; MgHCO3+ 4; MgCl+ 1 | |
Calcium chloride CaCl2 | 7.93 | Ca2+ 78; Cl− 98; Ca-organo-complexed forms 6; CaSO4 6; CaHCO3+ 5; CaCl+ 1 | |
Sodium sulphate Na2SO4 | 7.94 | Na+ 98; SO42− 72; CaSO4− 16; MgSO4− 10 | |
Alkaline Salt Type | pH | Prevalent Ions (%) | |
Sodium hydrogencarbonate NaHCO3 | 8.01 | Na+ 98; HCO3− 92; CaHCO3+ 2; CaCO3 1 | |
Sodium carbonate Na2CO3 | 8.08 | Na+ 98.2; HCO3− 92; CaHCO3+ 2.2; CaCO3 1.3 | |
Potassium carbonate K2CO3 | 8.03 | K+ 98; HCO3− 92; CaHCO3+ 2; CaCO3 1 | |
Magnesium carbonate MgCO3 | 8.07 | Mg2+ 75; Mg-organo-complexed forms 10; MgHCO3+ 5; MgSO4 4; HCO3− 91; MgHCO3+ 2 | |
Calcium carbonate CaCO3 | 8.07 | Ca2+ 76; Ca-organo-complexed forms 6; CaHCO3+ 6; CaSO4 6; HCO3− 90; CO32− 1 |
Area of Application | AI/ML Tools Applied | Best Performing Model | Reference |
---|---|---|---|
Soil resistance to penetration prediction Soil hydrological classification Digital soil mapping | ANN, SVM | SVM | [139] |
Soil Survey Data, KNN, SVM, Decision Trees (DT) Classification Bagged Ensembles and Tree Bagger | SVM | [122] | |
Multiple linear regression (MLR), RF, SVR, ANN and k-nearest neighbors (KNN) | RF | [140] | |
Disinfection protocol in seed germination Soil moisture prediction | Generalized regression neural network (GRNN) | GRNN | [132] |
Extreme learning machine (ELM), RF, Ensemble empirical mode decomposition (EEMD)-ELM, EEMD-RF Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)-ELM, CEEMDAN-RF | EEMD-ELM | [141] | |
Soil electrical conductivity prediction Soil salinity mapping Prediction of secondary compression index Soil nutrients prediction | Multilayer Perceptron (MLP) Neural Network, Hybrid MLP -grey wolf optimizer (GWO) model | Hybrid (MLP-GWO) Model | [116] |
SVM, ANN, RF | SVM | [120] | |
Multi-gene genetic programming (MGGP) Particle swarm optimization (PSO), ANN, ANN-PSO | MGGP | [142] | |
RF, Naïve Bayes (NB), SVM, ANN, DT, and Least Square SVM (LS-SVM) | LS-SVM and ANN | [143] | |
Soil organic carbon prediction Salt content prediction | ANN, SV, RF, MLR | RF | [144] |
Chemical detection method, visible-near-infrared spectroscopy, and two-dimensional deep learning (2D-DL) | 2D-DL | [145] | |
Soil salinity prediction | Auto Encoder (AE), ANN, SVM, KNN, DT | AE-SVM | [146] |
Soil salinity prediction and mapping | MLR, RF Regression, SVR | RF Regression | [121] |
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Ondrasek, G.; Rathod, S.; Manohara, K.K.; Gireesh, C.; Anantha, M.S.; Sakhare, A.S.; Parmar, B.; Yadav, B.K.; Bandumula, N.; Raihan, F.; et al. Salt Stress in Plants and Mitigation Approaches. Plants 2022, 11, 717. https://doi.org/10.3390/plants11060717
Ondrasek G, Rathod S, Manohara KK, Gireesh C, Anantha MS, Sakhare AS, Parmar B, Yadav BK, Bandumula N, Raihan F, et al. Salt Stress in Plants and Mitigation Approaches. Plants. 2022; 11(6):717. https://doi.org/10.3390/plants11060717
Chicago/Turabian StyleOndrasek, Gabrijel, Santosha Rathod, Kallakeri Kannappa Manohara, Channappa Gireesh, Madhyavenkatapura Siddaiah Anantha, Akshay Sureshrao Sakhare, Brajendra Parmar, Brahamdeo Kumar Yadav, Nirmala Bandumula, Farzana Raihan, and et al. 2022. "Salt Stress in Plants and Mitigation Approaches" Plants 11, no. 6: 717. https://doi.org/10.3390/plants11060717
APA StyleOndrasek, G., Rathod, S., Manohara, K. K., Gireesh, C., Anantha, M. S., Sakhare, A. S., Parmar, B., Yadav, B. K., Bandumula, N., Raihan, F., Zielińska-Chmielewska, A., Meriño-Gergichevich, C., Reyes-Díaz, M., Khan, A., Panfilova, O., Seguel Fuentealba, A., Romero, S. M., Nabil, B., Wan, C., ... Horvatinec, J. (2022). Salt Stress in Plants and Mitigation Approaches. Plants, 11(6), 717. https://doi.org/10.3390/plants11060717