Predicting optimal planting dates and haplotypes in multiple environments
Finding the optimal planting dates can significantly increase growth, development and crop production (Baum et al., 2019). Nevertheless, this undertaking poses difficulties due to various modulating factors (Sacks et al., 2010). While local agricultural facilities often provide recommendations based on historical records, these suggestions are not always reliable. To tackle this issue, our study used the reaction norm to quantify the phenotypic plasticity of each genotype and predicted trait performance based on weather conditions specific to each planting date and location, from which we proposed the optimal planting date. In the future, our approach can be further improved by incorporating crop models that incorporate a physiological description of crop growth using advanced mathematical algorithms (Hammer et al., 2005). This integration will enhance our ability to explain and predict crop growth and development, while also simplifying the extensive parameter calibration work required by crop models, especially for large-scale and long-term simulations.
Based on an analysis of phenotypic plasticity into the interactions between genes and environmental indices, we generated a prediction model for the relationship between trait performance and these interactions. Using this model, we evaluated the genetic potential of different genotypes to adapt to future climates. We used a precipitation-related environmental index to estimate projected future climate conditions. Other environmental factors, like irradiation, soil moisture and nitrogen application, may emerge as critical in other scenarios, and we may be able to model nonlinear relationships among them (Scheres and van der Putten, 2017, Hammer et al., 2010). While our study used projected future climates for trait performance prediction, it is essential to acknowledge that the accuracy of these predictions may require improvement as more precise estimates of climate change become available. With the aid of powerful tools in artificial intelligence and biotechnologies, advanced models are currently being developed to enhance the precision of breeding and agronomy practices in response to a changing climate. By building upon the establishment of mechanistic links and advanced models, we can effectively address fundamental questions related to phenotypic plasticity and develop potential breeding and agronomic strategies.