The potential of big data to support businesses has been demonstrated in financial services, manufacturing, and telecommunications. Here, we report on efforts to enter a new data era in plant breeding by collecting genomic and phenotypic information from 12,858 wheat genotypes representing 6575 single-cross hybrids and 6283 inbred lines that were evaluated in six experimental series for yield in field trials encompassing ~125,000 plots. Integrating data resulted in twofold higher prediction ability compared with cases in which hybrid performance was predicted across individual experimental series. Our results suggest that combining data across breeding programs is a particularly appropriate strategy to exploit the potential of big data for predictive plant breeding. This paradigm shift can contribute to increasing yield and resilience, which is needed to feed the growing world population.

大数据支持企业的潜力已在金融服务、制造和电信领域得到证明。在这里，我们报告了通过从代表 6575 个单交杂种和 6283 个自交系的 12,858 个小麦基因型中收集基因组和表型信息进入植物育种新数据时代的努力，这些小麦基因型在六个实验系列中评估了田间试验的产量，包括约 125,000地块。与跨单个实验系列预测混合性能的情况相比，整合数据导致预测能力提高两倍。我们的结果表明，跨育种计划结合数据是一种特别合适的策略，可以利用大数据进行预测性植物育种的潜力。这种范式转变有助于提高产量和弹性，