论文标题
农场脱衣试验的最佳设计 - 系统或随机的？
Optimal design for on-farm strip trials -- systematic or randomised?
论文作者
论文摘要
毫无疑问，农艺学家和生物有限公司在农业实验中随机化的重要性。即使农艺师将实验从小型试验扩展到大型农场试验，随机设计占主导地位而不是系统的设计。但是，情况可能会根据（Ofe）的农场实验的目标而变化。如果OFE的目标是获得平滑的地图，显示了覆盖整个领域的行和列的网格上可控输入的最佳水平，则在稳健性和可靠性方面，应该优先使用系统设计，而不是随机设计。通过针对OFE和模拟研究的新型地理加权回归（GWR），我们得出结论，对于大型脱衣试验，如果拟合了线性的处理模型或未考虑空间变化，则随机设计和系统设计之间的差异并不显着。但是对于二次模型，系统设计优于随机设计。
There is no doubt on the importance of randomisation in agricultural experiments by agronomists and biometricians. Even when agronomists extend the experimentation from small trials to large on-farm trials, randomised designs predominate over systematic designs. However, the situation may change depending on the objective of the on-farm experiments (OFE). If the goal of OFE is obtaining a smooth map showing the optimal level of a controllable input across a grid made by rows and columns covering the whole field, a systematic design should be preferred over a randomised design in terms of robustness and reliability. With the novel geographically weighted regression (GWR) for OFE and simulation studies, we conclude that, for large OFE strip trials, the difference between randomised designs and systematic designs are not significant if a linear model of treatments is fitted or if the spatial variation is not taken into account. But for a quadratic model, systematic designs are superior to randomised designs.
