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首页> 外文期刊>Agronomy Journal >Estimating factor contributions to soybean yield from farm field data.
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Estimating factor contributions to soybean yield from farm field data.

机译:根据农田数据估算因素对大豆产量的贡献。

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Illinois ranks second in soybean [Glycine max (L.) Merr.] production in the United States with an annual crop value of some $4 billion. To discover what management practices, soil parameters, and environmental conditions enable higher soybean yields, the Illinois Soybean Association (ISA) started in 2010 a state-wide "Yield Challenge" (YC) program. Enrolled producers established a "challenge" plot and adjoining "standard" practices plot, and agreed to share crop management information, soil samples, and yield data. Our work describes data analyses and findings using data generated under this program. Yields differed between standard and challenge plots across the state, with foliar applications of fungicide and or insecticide resulting in significant yield increases. Using principal component analyses and multiple regression tools, we were able to explain about 54% of the variation in soybean yield for the state in 2010. Within the available data range, delays in planting date and increased row spacing both reduced soybean yields, and tilled fields yielded more than no- tilled soybean fields. We uncovered a negative trend between soybean yield and PC1, formed by soil cation exchange capacity (CEC), dominant cations, and soil organic matter (SOM), likely due to the drainage characteristics of the plots. Yields were also decreased with increasing values of PC3, a variable that includes soil pH, Mn levels, and soybean cyst nematode (SCN) egg count. On the other hand, higher soil test values of P, Zn, Fe, and K, included in PC2, were related to higher soybean yields. We see this as a promising start to identifying management factors that may be addressed as we continue the search for higher soybean yields.
机译:伊利诺伊州在美国的大豆[Glycine max (L.)Merr。]产量中排名第二,年作物价值约为40亿美元。为了发现哪些管理实践,土壤参数和环境条件可以提高大豆单产,伊利诺伊州大豆协会(ISA)于2010年启动了一项全州范围的“大挑战”(YC)计划。登记的生产者建立了一个“挑战性”地块和一个相邻的“标准”实践地块,并同意共享作物管理信息,土壤样品和产量数据。我们的工作使用在该程序下生成的数据来描述数据分析和发现。全州标准地和挑战地的产量不同,杀真菌剂和/或杀虫剂的叶面施用导致产量大幅增加。使用主成分分析和多元回归工具,我们能够解释该州2010年大豆产量的大约54%。在可用数据范围内,播种日期延迟和行距增加都降低了大豆单产和耕种耕地的产量要高于未耕种的大豆。我们发现了大豆产量与PC1之间的负趋势,该趋势由土壤阳离子交换能力(CEC),优势阳离子和土壤有机质(SOM)形成,可能是由于该地块的排水特性所致。产量也随着PC3值的增加而降低,PC3值包括土壤pH值,Mn水平和大豆孢囊线虫(SCN)卵数。另一方面,PC2中包含的较高的土壤测试值P,Zn,Fe和K与较高的大豆产量有关。我们认为这是确定管理因素的有希望的开端,因为我们将继续寻求更高的大豆单产。

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