LightGBM is an ensemble model of decision trees for classification and regression prediction. We demonstrate its utility in genomic selection-assisted breeding with a large dataset of inbred and hybrid maize lines. LightGBM exhibits superior performance in terms of prediction precision, model stability, and computing efficiency through a series of benchmark tests. We also assess the factors that are essential to ensure the best performance of genomic selection prediction by taking complex scenarios in crop hybrid breeding into account. LightGBM has been implemented as a toolbox, CropGBM, encompassing multiple novel functions and analytical modules to facilitate genomically designed breeding in crops.

中文翻译：

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LightGBM：通过集成学习加速基因组设计的作物育种


LightGBM 是一种用于分类和回归预测的决策树集成模型。我们通过大量自交和杂交玉米品系数据集展示了其在基因组选择辅助育种中的实用性。 LightGBM通过一系列基准测试，在预测精度、模型稳定性、计算效率等方面展现出优越的性能。我们还通过考虑作物杂交育种中的复杂场景来评估确保基因组选择预测最佳性能所必需的因素。 LightGBM 已作为工具箱 CropGBM 实施，包含多种新颖功能和分析模块，以促进作物基因组设计育种。