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从农艺学和经济学角度来看北美的玉米产量对种植密度的贝叶斯响应方法。

Bayesian approach for maize yield response to plant density from both agronomic and economic viewpoints in North America.

机构信息

Department of Agronomy, Kansas State University, 2004 Throckmorton Plant Science Center, Manhattan, KS, 66506, USA.

Corteva Agriscience, 7100 NW, 62nd Ave., Johnston, IA, 50131, USA.

出版信息

Sci Rep. 2020 Sep 29;10(1):15948. doi: 10.1038/s41598-020-72693-1.

Abstract

Targeting the right agronomic optimum plant density (AOPD) for maize (Zea mays L.) is a critical management decision, but even more when the seed cost and grain selling price are accounted for, i.e. economic OPD (EOPD). From the perspective of improving those estimates, past studies have focused on utilizing a Frequentist (classical) approach for obtaining single-point estimates for the yield-density models. Alternative analysis models such as Bayesian computational methods can provide more reliable estimation for AOPD, EOPD and yield at those optimal densities and better quantify the scope of uncertainty and variability that may be in the data. Thus, the aims of this research were to (i) quantify AOPD, EOPD and yield at those plant densities, (ii) obtain and compare clusters of yield-density for different attainable yields and latitudes, and (iii) characterize their influence on EOPD variability under different economic scenarios, i.e. seed cost to corn price ratios. Maize hybrid by seeding rate trials were conducted in 24 US states from 2010 to 2019, in at least one county per state. This study identified common yield-density response curves as well as plant density and yield optimums for 460 site-years. Locations below 40.5 N latitude showed a positive relationship between AOPD and maximum yield, in parallel to the high potential level of productivity. At these latitudes, EOPD depended mostly on the maximum attainable yield. For the northern latitudes, EOPD was not only dependent on the attainable yield but on the cost:price ratio, with high ratios favoring reductions in EOPD at similar yields. A significant contribution from the Bayesian method was realizing that the variability of the estimators for AOPD is sometimes greater than the adjustment accounting for seed cost. Our results point at the differential response across latitudes and commercial relative maturity, as well as the significant uncertainty in the prediction of AOPD, relative to the economic value of the crop and the seed cost adjustments.

摘要

针对玉米(Zea mays L.)的适宜农艺最优种植密度(AOPD)是一个关键的管理决策,尤其是在考虑到种子成本和谷物销售价格时,即经济最适种植密度(EOPD)。从提高这些估计值的角度出发,过去的研究侧重于利用频率主义(经典)方法来获得产量-密度模型的单点估计值。替代分析模型,如贝叶斯计算方法,可以为 AOPD、EOPD 和最优密度下的产量提供更可靠的估计,并更好地量化数据中可能存在的不确定性和可变性的范围。因此,本研究的目的是:(i)量化不同可实现产量和纬度下的 AOPD、EOPD 和产量;(ii)获得并比较不同可实现产量和纬度下的产量-密度聚类;(iii)在不同经济情景下,即种子成本与玉米价格比,描述其对 EOPD 变异性的影响。2010 年至 2019 年,在美国 24 个州的至少一个县进行了玉米杂交播种率试验。本研究确定了常见的产量-密度响应曲线以及 460 个地点-年份的最佳种植密度和产量。纬度低于 40.5°N 的地区,AOPD 与最大产量之间呈正相关关系,与高生产力潜力水平平行。在这些纬度下,EOPD 主要取决于最大可实现产量。对于北部纬度地区,EOPD 不仅取决于可实现的产量,还取决于成本与价格比,高比率有利于在相似产量下降低 EOPD。贝叶斯方法的一个重要贡献是认识到 AOPD 估计值的变异性有时大于种子成本调整的变异性。我们的研究结果表明,在不同纬度和商业相对成熟度下,AOPD 的响应存在差异,以及在预测 AOPD 方面存在显著的不确定性,这与作物的经济价值和种子成本调整有关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ebdd/7525453/95073156c302/41598_2020_72693_Fig1_HTML.jpg

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