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.