Spatial field variations in soybean (Glycine max [L.] Merr.) performance trials affect agronomic characters and seed composition

被引:20
|
作者
Vollmann, J
Winkler, J
Fritz, CN
Grausgruber, H
Ruckenbauer, P
机构
[1] Univ Agr Sci, Agron & Plant Breeding Dept, A-1180 Vienna, Austria
[2] Saatzucht Gleisdorf GmbH, A-8200 Gleisdorf, Austria
基金
奥地利科学基金会;
关键词
grain yield; neighbour analysis; seed protein content; soybean; spatial heterogeneity;
D O I
10.1016/S1161-0301(99)00042-8
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
The objective of this study was to investigate field trends in agronomic characters of soybean (Glycine max [L.] Merr,) performance trials. Field experiments were arranged as lattice designs, and for each plot within an experiment, an environmental covariate representing the spatial trend was calculated using neighbour analysis. Correlations between environmental covariates of different characters were then used to analyse the degree of similarity in their spatial trends. Grain yield, seed protein content, and seed size were more influenced by spatial variations than time to flowering, time to maturity, and oil content. Significant correlations between environmental covariates were found, which demonstrate the similarity of trend patterns in different characters within particular experiments. In field trials exhibiting a high degree of spatial heterogeneity, correlations between environmental covariates of grain yield and protein content were highly positive. This indicates that field conditions, which promote grain yield, would also enhance protein content. Moreover, the observed trend patterns considerably affected the calculation of phenotypic coefficients of correlation between grain yield and seed protein content. The results suggest that spatial analysis should be applied to all characters of interest, when field conditions are not homogeneous. (C) 2000 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:13 / 22
页数:10
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