Nutrients have an important influence on plant growth, and in particular nitrogen, phosphorus and potassium have a significant impact on plants. Predictive fertilizer demand diagnostic models and critical dilution curves need to be investigated using modern techniques to achieve intensive precision agriculture to avoid nutrient deficiencies or surpluses in plants, plant cultivation, and management. Plant growth models such as predictive fertilizer demand diagnostic models and critical dilution curves play a vital role in plant cultivation and production. Critical dilution curves are subject to dynamic interactions between crop type, soil properties, space, and time, which can lead to slight differences between the overall and local critical dilution curves. In recent years, some new technical methods have been used to construct models to improve the accuracy and versatility of the critical dilution curve, so as to obtain the best model.
This Research Topic will welcome papers involved in research on critical dilution curves and precision agriculture. The selection of papers for publication will depend on the quality and rigor of the research. Specific topics include, but are not limited to, the use and refinement of methods based on critical dilution models in plant types and precision agriculture.
- Critical N Dilution Curves for Crops
- Critical P Dilution Curves for Crops
- Critical K Dilution Curves for Crops
- Critical dilution curves for vegetables
- Critical dilution curves for different parts of the plant
- The use of critical dilution curves in precision agriculture
- Construction of critical dilution curves with different growth indices
- The effect of different cultivation and management practices on critical dilution curves
- Methodological improvement and optimization of critical dilution curves
- Methods for predicting critical dilution curves and yields
- Nutrient interactions on critical curve relationships
- Remote sensing for predicting nitrogen nutrient indices
- Prediction of yield and quality by nitrogen nutrient indices
Nutrients have an important influence on plant growth, and in particular nitrogen, phosphorus and potassium have a significant impact on plants. Predictive fertilizer demand diagnostic models and critical dilution curves need to be investigated using modern techniques to achieve intensive precision agriculture to avoid nutrient deficiencies or surpluses in plants, plant cultivation, and management. Plant growth models such as predictive fertilizer demand diagnostic models and critical dilution curves play a vital role in plant cultivation and production. Critical dilution curves are subject to dynamic interactions between crop type, soil properties, space, and time, which can lead to slight differences between the overall and local critical dilution curves. In recent years, some new technical methods have been used to construct models to improve the accuracy and versatility of the critical dilution curve, so as to obtain the best model.
This Research Topic will welcome papers involved in research on critical dilution curves and precision agriculture. The selection of papers for publication will depend on the quality and rigor of the research. Specific topics include, but are not limited to, the use and refinement of methods based on critical dilution models in plant types and precision agriculture.
- Critical N Dilution Curves for Crops
- Critical P Dilution Curves for Crops
- Critical K Dilution Curves for Crops
- Critical dilution curves for vegetables
- Critical dilution curves for different parts of the plant
- The use of critical dilution curves in precision agriculture
- Construction of critical dilution curves with different growth indices
- The effect of different cultivation and management practices on critical dilution curves
- Methodological improvement and optimization of critical dilution curves
- Methods for predicting critical dilution curves and yields
- Nutrient interactions on critical curve relationships
- Remote sensing for predicting nitrogen nutrient indices
- Prediction of yield and quality by nitrogen nutrient indices