Abstract Precision agriculture, using satellite navigation, has grown in popularity around the world. Because of its practical uses for land preparation, sowing, nutrient applications, pest (weed, pathogen, invertebrate) management, stress sensing and harvest recording, many major equipment manufacturers include precision variable rate capability as standard fittings. GIS (Geographic Information System) maps may include georeferenced soil chemistry information and detailed historical harvest yield data. We integrate such data to examine Precision Variable Rate Nitrogen (PVRN) applications with whole-farm management information and rainfall records in a district where waterlogging frequently reduces crop yields. Given wide variations in growing season rainfalls (GSR) and soils in the district, we test year-to-year stability of rainfed crop-yield rankings over time on 90x90m GIS grid-areas in large paddocks (over 100 ha). Variations in historical yield-quartile rankings of grid-areas across GSR levels over time are observed; some areas yield best at some GSR levels but not others, such that the best-yielding part of a paddock one year may be poorest in the next. We answer the question: “Why would a farmer in this district choose to apply a uniform moderate rate of N to a paddock at sowing even though in possession of precision variable rate-capable (PVR) equipment, georeferenced electromagnetic conductance (EM38) data and crop-yield map data for that paddock in many past seasons?” We show that soil conditions in the study district challenge the economic value of PVRN versus uniform rates in farming systems prone to waterlogging. If full-season GSR were reliably predictable early in the season, applications of N could be based on a rule calling for 40 kg/ha N/t of attainable yield at that GSR and grid-area EM38 level, minus sampled soil-N. Unfortunately, GSR is notoriously unpredictable. We simulate whole-farm financial risk profiles (CDFs of simulated decadal cash margins with varying prices and yields, minus all variable, fixed and capital costs) assuming moderate uniform N rates, as practiced in the study area, on two model farms; one with low and one with high-fixed-costs, given historical variations in GSR and prices. Assuming PVRN requires annual geo-referenced soil nutrient sampling of each hectare, these added costs could be covered by a 1% increase in yields across all wheat and canola crops or a 7% decrease in applied N. We cannot reject the null hypothesis that PVRN is no more profitable than uniform applications in this district. Near-real-time NDVI may lower the cost of PVRN for late applications.

中文翻译：

---

澳大利亚东南部涝渍河流平原旱地农业的精密可变速率氮肥？

摘要 使用卫星导航的精准农业在世界范围内越来越受欢迎。由于其在整地、播种、营养应用、害虫（杂草、病原体、无脊椎动物）管理、压力传感和收获记录方面的实际用途，许多主要设备制造商都将精密可变速率能力作为标准配件。GIS（地理信息系统）地图可能包括地理参考土壤化学信息和详细的历史收获产量数据。我们整合这些数据，以检查精确可变速率氮 (PVRN) 应用与整个农场管理信息和降雨量记录，在一个经常因涝渍而降低作物产量的地区。鉴于该地区的生长季降雨量 (GSR) 和土壤变化很大，我们在大围场（超过 100 公顷）的 90x90 米 GIS 网格区域上测试了雨养作物产量排名的逐年稳定性。观察到 GSR 水平上网格区域的历史产量四分位数排名随时间的变化；某些地区在某些 GSR 水平上产量最高，但在其他地区则不然，因此围场中一年产量最高的部分可能在下一年最差。我们回答了这个问题：“为什么这个地区的农民在播种时选择对围场应用统一的中等速率 N，即使拥有精确的可变速率 (PVR) 设备、地理参考电磁电导 (EM38) 数据和那个围场过去多个季节的作物产量地图数据？” 我们表明，研究区的土壤条件挑战了 PVRN 与易涝的农业系统中统一比率的经济价值。如果整个季节的 GSR 在季节早期可以可靠地预测，那么施氮的规则可以要求在该 GSR 和网格区域 EM38 水平下可达到 40 kg/ha N/t 的可达到产量，减去采样的土壤氮。不幸的是，众所周知，GSR 是不可预测的。我们模拟整个农场的财务风险状况（模拟十年现金利润的 CDF，具有不同的价格和产量，减去所有可变成本、固定成本和资本成本），假设在两个模型农场中采用研究区的中等均匀 N 率；考虑到 GSR 和价格的历史变化，一种固定成本低，另一种固定成本高。假设 PVRN 需要每年对每公顷土地进行地理参考土壤养分采样，这些增加的成本可以通过所有小麦和油菜作物的产量增加 1% 或施用的氮减少 7% 来弥补。我们不能拒绝原假设，即 PVRN 并不比该地区的统一应用程序更有利可图。近实时 NDVI 可能会降低后期应用的 PVRN 成本。