GAN-based image prediction of maize growth across varieties and developmental stages

The results showed that the method can make realistic predictions of multi-variety maize growth based on high-resolution generation. Furthermore, it can achieve prediction of maize growth throughout the entire growth cycle with high accuracy. In conclusion, this article provided a novel solution for visualized growth prediction of large plants with complex physiological structures throughout the entire growth cycle. A primary limitation of this study is its focus on modeling and predicting crop growth under uniform environmental conditions, without considering environmental variability. Future work will aim to incorporate diverse environmental factors into the model to enhance its robustness and predictive accuracy.