Maize Genomics and Genetics 2025, Vol.16, No.3, 139-148 http://cropscipublisher.com/index.php/mgg 141 so-called "overfitting", some methods can be used. Commonly used methods include cross-validation, regularization, or optimization through parameter adjustment. Sometimes the amount of data is too small, we can also create some "synthetic data" to supplement it. In addition, using an integrated model or only selecting the features most relevant to yield for modeling can also effectively reduce the problem of overfitting. This can make the model more stable and more reliable (Manjunath and Palayyan, 2023; Razavi et al., 2024). 3.3 Model interpretability and reliability analysis Nowadays, people pay more and more attention to whether the model can explain how it makes judgments. This is called "interpretability". Tools like SHAP and LIME can tell us what data the model uses to make predictions (Figure 1) (Nurcahyo et al., 2023; Paudel et al., 2023; Pant et al., 2025). For example, they can analyze whether weather, soil, or planting methods have the greatest impact on yield. In this way, farmers and researchers will be more willing to trust the model after seeing the results. In addition to these, we can also use some methods to test whether the model is reliable. For example, do sensitivity analysis to see if the model will be chaotic when different variables change. You can also evaluate the "uncertainty" of the prediction, that is, whether the model is confident when making predictions. In addition, using some new data to test the model can also help us determine how it performs in real scenarios (Hu et al., 2023). Figure 1 Framework to assess performance and interpretability of deep learning models (Adopted from Paudel et al., 2023) 4 Integration Strategies of Genomic Selection and Machine Learning 4.1 Fusion of genotype, phenotype, and environmental data Under drought conditions, to more accurately predict corn yield, we cannot just look at one type of data. It will be more effective to analyze genotype, phenotype and environmental data together. Studies have found that if genetic
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