通过典型相关性研究硒组分与土壤特性之间的关系

Assoc. Prof.dr. Abdullah Özkan, Abdullah Nuri Özsoy, V. Uygur
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引用次数: 0

摘要

一种元素的可用性和分布取决于土壤条件和地球化学组分。本研究采用典型相关法(CCA)研究了阿米克平原土壤参数(X 组)与硒(Se)组分(Y 组)之间的关联。第一个典型变量对(FCVP)之间的相关性为 0.391 ± 0.06,具有统计学意义(P < 0.01)。粘土、砂和淤泥变量的标准化典型系数最大,分别为 74.55、75.83 和 94.77。此外,B3 百分比的标准化典型系数为 1.029。FCVP 分析表明,X 组的原始变量和/或其规范变量(U1)与 Y 组中的有机质(OM)和 B3 百分比(0.603)具有最强的线性关系(0.770)。有机物(OM)(0.3012)与 Y 集的典型变量和 X 集的原始变量之间的线性结构相关性最强。然而,典型冗余分析表明,在 FCVP 中,X 集的方差由其典型变量描述的程度为 20.97%,而 Y 集的解释程度为 21.96%。因此,可以推断出,使用典型相关性可以有效地阐明土壤参数与植物营养各组成部分之间的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigation of the relationships between selenium fractions and soil properties by canonical correlation
The availability and distribution of an element are determined by soil conditions and the geochemical fractions. In this study, canonical correlation (CCA) was used to examine the associations between the soil parameters (X set) of the Amik plain and the fractions of selenium (Se) (Y set). A statistically significant correlation (P < 0.01) of 0.391 ± 0.06 was observed between the first canonical variable pair (FCVP). The clay, sand, and silt variables exhibited the greatest standardized canonical coefficients, with values of 74.55, 75.83, and 94.77, respectively. Additionally, the B3 percent had a standardized canonical coefficient of 1.029. The analysis of the FCVP showed that the original variables of the X set and/or its canonical variable (U1) had the strongest linear connection (0.770) with organic matter (OM) and the B3 percentage in the Y set (0.603). The OM (0.3012) exhibited the most substantial linear structural correlations between the canonical variables of the Y set and the original variables of the X set. However, the canonical redundancy analysis revealed that in the FCVP, the variance of the X set was described by its canonical variables to the extent of 20.97%, whereas the Y set was explained by 21.96%. Hence, it can be inferred that the use of canonical correlation is effective in elucidating the relationship between soil parameters and various components of plant nutrition.
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