Path analysis of agronomic traits in soybean cultivars with determinate and indeterminate growing habits

Abstract

The aim of this study was to determine associations of cause and effect agronomic traits with grain yield in contrasting growth habits of soybean genotypes, as well as to verify the magnitude of similar behaviors in different growing environments. The trials were conducted for one crop season using randomized blocks design arranged in factorial scheme, including two growing environments (Independência -RS and Tenente Portela -RS) x four genotypes (FPS Solimões RR e FPS Júpiter RR; BRS Tordilha RR and Fepagro 36 RR, 2 indeterminate and 2 determinate growing habits, respectively) in three replications. Ten important soybean yield components were evaluated. The data were subjected to individual analysis of variance for each environment and growing habits. For each environment within habits, the phenotypic path analysis was performed among the traits. The components number of pods on the main stem, number of ramifications, number of pods in the ramifications, and number of one and two-grain pods presented contrasting results in growing environments. The number of three-grain pods is among the components mostly related to grain yield for both determinate and indeterminate growing habit genotypes, regardless of the environment. The adoption of genotypes with higher weight of thousand grains may provide satisfactory results for grain yield, regardless of the growth habit and environment of cultivation.

Estimation of Genetic Parameters and Wood Yield Selection Index in a Clonal Trial of Korean Pine (Pinus koraiensis) in Northeastern China

“…This relationship is an important parameter in tree improvement when selecting for multiple characteristics [58]. High genotypic correlation is a high degree of pleiotropy, signifying that many common gene loci affect several traits [24]. In the present study, moderate to high phenotypic and genotypic correlation was found between Ht, BD, DBH, DIAM3, CH, and Vol., indicating that these traits would be improved simultaneously when selecting elite clones using tree volume as an index [59], whereas SSD, CB, or AB would be slightly improved or would need to be selected independently, as they showed weak and negative correlations with stem volume [59].…”

“…Pathway analysis, consisting of measurement of the weight of variance of dependent variables and independent ones [22], involves the conversion of correlation coefficients into direct or indirect effects through a multiple regression equation that calculates the impact of correlated variables with precision. Pathway analysis has revealed associations between cause and effect among yield and yield-related traits of genotypes in agronomic plants [23], as well as different growing environments or habitats [24,25]. By reducing a large set of variables into underlying correlated factors [26], principal component analysis (PCA) appears to be a useful tool to highlight trait combinations that greatly contribute to the variation among tree populations under characterization [27,28].…”

Chemical Control of Asian Soybean Rust and Its Effect in the Yield and Quality of Soybean Seeds

“…The increase in yield (Table 1), relative to the control, ranged from 595.8 kg ha -1 to 1758.5 kg ha -1 for two applications and four applications.The lack of fungicide application in the untreated plot reduced yield by 35.6% the production when compared to the higher production four applications, with four applications. Soybean plants severely infected with this disease present early defoliation, which compromises the formation and filling of pods and the final weight of the grains (Yorinori & Lazzarotto, 2004;Szareski et al, 2018).…”

Artificial Intelligence and Multiple Models Applied to Phytosanitary and Nutritional Aspects That Interfer in the Physiological Potential of Soybean Seeds

“…Soybean (Glycine max) is a legume of great importance worldwide due to its high productive potential and nutritional value, in addition to its use in agro-industries (GABARD et al, 2020;SZARESKI et al, 2018a). To achieve high productivity and meet this demand from the consumer market, some management practices are essential.…”