Forecasting yield via reference- and scenario calculations
Forecasting yield via reference- and scenario calculations
复制标题
通过参考和情景计算预测产量
DOI：
10.1016/j.compag.2015.03.020
复制
发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Ratjen
中科院分区：
文献类型：
--
作者：
Ratjen
特定地点的平均产量对大多数生产者来说是一个众所周知的值，因此年际产量变异性是任何产量预测的实际目标值。使用机械模型进行季节产量预测可能有助于优化作物管理决策，如绝对施肥量。然而，有偏差的模拟产量可能会限制潜在的利益，往往是产量限制因素的结果，如前茬作物，模型没有考虑。本文概述了一种方法，它使用特定地点的历史天气记录的相对产量预测（Yrel）通过产量预测和参考计算。为了获得产量预测的绝对值，Yrelis然后乘以平均观测产量。这种设计的主要好处是偏差大部分被抵消，从而提高了模型的准确性。所使用的作物土壤模型HumeWheat开发和参数化的广泛的实验数据库，包括几个现代小麦品种。我们假设，广泛的参数化的关键过程允许检测年际产量的变化，即使没有基因型或特定地点的模型校准。我们的第一个目的是评估这种新的方法的产量预测经验，在不同的物候期阶段的普遍适用性。第二个目的是评估不同土壤和天气条件对预报准确性的影响。几个现代面包小麦品种（Triticum aestivumL.）用于评估该方法。对于开花期开始时的预测，与特定处理（前茬作物的地点）平均产量的假设相比，产量的总体平均绝对误差（MAE，t ha− 1干物质）减少了0.24（或相对减少了27%）。随后的模拟研究与三种不同的气候和不同的持水能力，持水能力表明，一个更大的好处，可以预期的网站不稳定的产量，因为干旱的限制。
The site-specific average yield is a well-known value to most producers, thus the inter-annual yield variability is the actual target value of any yield forecast. Using mechanistic models for in-season yield forecasts may help to optimize crop management decisions such as absolute fertilizer rates. However, a biased simulated yield can limit the potential benefits and is often a consequence of yield limiting factors like preceding crop, not considered by the model. This paper outlines a methodology which uses site-specific, historical weather records for a relative yield prognosis (Yrel) via yield projections and reference calculations. In order to obtain the yield forecast in absolute terms,Yrelis then multiplied with average observed yield. The key benefit of this design is that the bias is mostly cancelled out, thereby improving the model accuracy. The used crop–soil modelHumeWheatwas developed and parameterized on a broad experimental database including several modern wheat cultivars. We assume that the broad parameterization of key-processes allows the detection of inter-annual yield variability, even without genotype- or site-specific model calibrations. Our first aim was to evaluate the general applicability of this new approach of yield forecasting empirically at different phenological stages. The second aim was to evaluate the impact of different soil and weather conditions on forecast accuracy. Yield observations from several modern bread wheat cultivars (Triticum aestivumL.) were used to evaluate the method. For forecasts at the start of anthesis, the overall mean absolute error for yield (MAE, t ha−1dry matter) was reduced by 0.24 (or in relative terms 27%) compared to the assumption of treatment-specific (site ∗ preceding crop) average yield. A subsequent simulation study with three different climate and varying water holding capacities water holding capacities reveals that a greater benefit can be expected for sites less stable in yield because of drought limitations.
DOI：
--
发表时间：
2012
期刊：
影响因子：
--
作者：
A. Ratjen;U. Böttcher;H. Kage
通讯作者：
H. Kage
花椰菜氮素利用效率方面 I. 基于模拟模型的田间氮素有效性分析
影响因子：
0.6
作者：
H. Kage;C. Alt;H. Stützel
通讯作者：
H. Stützel
DOI：
--
发表时间：
1988
期刊：
影响因子：
--
作者：
H. Stȕtzel;D. Charles;D. Beech
通讯作者：
D. Beech