...
首页> 外文期刊>Plant and Soil >Associations between field characteristics and soybean plant performance using canonical correlation analysis
【24h】

Associations between field characteristics and soybean plant performance using canonical correlation analysis

机译:典范相关分析法研究田间特性与大豆植株性能之间的关联

获取原文
获取原文并翻译 | 示例

摘要

The main objective of this study is to find associations between site characteristics (topographic, and soil physical and chemical properties) and soybean [Glycine max (L.) Merr.] plant performance (e.g. yield, canopy development) occurring at a field scale. The study took place in an Illinois production field in the 2000 and 2001 seasons. These associations were studied with canonical correlation analysis (CCA) followed by a spatial analysis of the resulting canonical variables with semivariography. The CCA discovered several significant associations between site characteristics. The first pair of canonical variables had a correlation coefficient of 0.76. The site characteristics most consistently correlated with the first pair of canonical variables were organic matter (OM) (r = 0.64 and 0.51 for the 2000 and 2001 seasons, respectively),. pH (r = 0.39 and 0.51 for the 2000 and 2001 seasons, respectively), and deep electrical conductivity (ECD) (r = 0.53 and 0.49 for the 2000 and 2001 seasons, respectively). Site variables soil phosphorous (P) and soil potassium (K) were inconsistently correlated with the site characteristics canonical variable. These results indicate that site variables related to soil water retention are more consistently associated with soybean performance than site variables related to soil fertility. The plant performance characteristic most correlated with the soybean performance canonical variable were NDVIN (r = 0.76 and 0.72 for the 2000 and 2001 seasons, respectively), SPAD (r = 0.70 and 0.47 for the 2000 and 2001 seasons, respectively), and yield (r = 0.44 and 0.58 for the 2000 and 2001 seasons, respectively). The variables NDVIN, yield. ECD are obtained with sensors and thus they can be easily used at a production field scale. The common spatial structures in pairs of the canonical variables confirm the relationship between site properties and soybean performance, proving their potential in the demarcation of uniform areas within production fields. This approach can be used to explore soil plant relationships in other field studies.
机译:这项研究的主要目的是发现在田间尺度上发生的场地特征(地形和土壤物理和化学性质)与大豆[Glycine max(L.)Merr。]植物的生长性能(例如产量,冠层发育)之间的关联。这项研究是在2000和2001季节在伊利诺伊州的一个生产基地进行的。使用规范相关分析(CCA)研究了这些关联,然后使用半变异函数对所得的规范变量进行了空间分析。 CCA发现了站点特征之间的几个重要关联。第一对规范变量的相关系数为0.76。与第一对典型变量最一致相关的站点特征是有机质(OM)(2000年和2001年季节分别为r = 0.64和0.51)。 pH(2000和2001季节分别为r = 0.39和0.51)和深电导率(ECD)(2000和2001季节分别为r = 0.53和0.49)。站点变量土壤磷(P)和土壤钾(K)与站点特征典范变量不一致。这些结果表明,与土壤水分保持相关的位点变量比与土壤肥力相关的位点变量更一致地与大豆性能相关。与大豆性能典范变量最相关的植物性能特征是NDVIN(2000年和2001年季节分别为0.76和0.72),SPAD(2000年和2001年季节分别为0.70和0.47)和产量(在2000年和2001年季节,r分别为0.44和0.58)。变量NDVIN,产量。 ECD是通过传感器获得的,因此可以很容易地在生产现场使用。成对的典型变量确定了场所特性与大豆生产性能之间的关系,证明了它们在划分生产区域内均匀区域方面的潜力。此方法可用于其他田间研究中的土壤植物关系。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号