Agronomic Big Data Analytics for improved crop management

农业系统是复杂的，如果我们要实现粮食安全和保持环境质量，就必须对其进行管理。通过“大数据”集的收集、处理和分析，工业和商业中复杂系统的管理正在得到改善。多年来，农民有可能利用联合收割机或拖拉机上的gps驱动的监视器、卫星上的传感器和土壤的直接采样和分析来收集关于他们的作物和土壤的大数据集。这就提出了一个问题，即农业是否能够进入大数据时代，以便比传统的在有限数量的试验点进行实地试验的方法更快、更有效地解决管理问题。我们认为这是可能的，但只有通过使用有生物学意义的方法来分析数据，而不是盲目地挖掘数据的相关性。这是一项在大数据上测试两种量身定制的大数据分析方法的可行性研究

Agricultural systems are complex, and must be managed if we are to achieve food security andmaintain environmental quality. The management of complex systems in industry and commerce isbeing improved by the collection, processing and analysis of "big data" sets. For some years farmershave had the potential to collect big data sets on their crops and soils using GPS-driven monitors onthe combine or tractor, data from satellite-borne sensors and the direct sampling and analysis of soils.This raises the question of whether agriculture can enter the big data era in order to solvemanagement problems more quickly and robustly than through the conventional approach of fieldtrials at a limited number of experimental sites. We contend that this is possible, but only by usingmethods to analyse the data that are biologically meaningful rather than by blindly mining data forcorrelations. This is a feasibility study to test two tailored big-data analytical methods on a large data