Genetic Relationships Among Physiological Processes, Phenology, and Grain Yield Offer an Insight Into the Development of New Cultivars in Soybean (Glycine max L. Merr)

Abstract

Soybean grain yield has steadily increased during the last century because of enhanced cultivars and better agronomic practices. Increases in the total biomass, shorter cultivars, late maturity, and extended seed-filling period are frequently reported as main contributors for better soybean performance. However, there are still processes associated with crop physiology to be improved. From the theoretical standpoint, yield is the product of efficiency of light interception (Ei), radiation use efficiency (RUE), and harvest index (HI). The relative contribution of these three parameters on the final grain yield (GY), their interrelation with other phenological–physiological traits, and their environmental stability have not been well established for soybean. In this study, we determined the additive–genetic relationship among 14 physiological and phenological traits including photosynthesis (A) and intrinsic water use efficiency (iWUE) in a panel of 383 soybean recombinant inbred lines (RILs) through direct (path analyses) and indirect learning methods [least absolute shrinkage and selection operator (LASSO) algorithm]. We evaluated the stability of Ei, RUE, and HI through the slope from the Finley and Wilkinson joint regression and the genetic correlation between traits evaluated in different environments. Results indicate that both supervised and unsupervised methods effectively establish the main relationships underlying changes in Ei, RUE, HI, and GY. Variations in the average growth rate of canopy coverage for the first 40 days after planting (AGR40) explain most of the changes in Ei. RUE is primarily influenced by phenological traits of reproductive length (RL) and seed-filling (SFL) as well as iWUE, light extinction coefficient (K), and A. HI showed a strong relationship with A, AGR40, SFL, and RL. According to the path analysis, an increase in one standard unit of HI promotes changes in 0.5 standard units of GY, while changes in the same standard unit of RUE and Ei produce increases on GY of 0.20 and 0.19 standard units, respectively. RUE, Ei, and HI exhibited better environmental stability than GY, although changes associated with year and location showed a moderate effect in Ei and RUE, respectively. This study brings insight into a group of traits involving A, iWUE, and RL to be prioritized during the breeding process for high-yielding cultivars.

An assessment of the interaction between sucrose content and seed quality traits in soybeans

“…We computed undirected graphical models from the additive genetic, residual, and phenotypic correlation matrix to infer the connection among traits. We used a Gaussian undirected graphical model based on neighborhood selection with the graphical least absolute shrinkage and selection operator (GLASSO) algorithm as proposed by Meinshausen and Bühlmann (2006) and implemented by Zhao et al (2012) using the "huge" package in R. Undirected graphical models have been shown to be useful for uncovering patterns of interaction among soybean traits (Lopez et al, 2021;Xavier et al, 2017). These models are particularly useful when studying variables that are highly correlated, as is the case with plant traits, to infer causal relationships between them.…”

Comportamiento agronómico de líneas experimentales y variedades comerciales de soja (Glycine max, Fabaceae) en el Chaco central de Paraguay

“…Por otro lado, la línea 25 tuvo ciclo más largo, más ramas y vainas, pero menor peso de grano (Tabla 6). La combinación de estos atributos podría ser de utilidad como marcadores fisiológicos para asistir al mejoramiento vegetal, junto con herramientas moleculares (Hall y Sadras 2009;Tester y Langridge, 2010;Lopez et al, 2021). Tabla 6.…”

Efeito da aplicação boratada em diferentes estádios fenológicos na qualidade fisiológica de sementes de soja

“…Os avanços significativos da produção e o aumento na capacidade produtiva da soja brasileira estão aliados aos avanços científicos e à disponibilização de tecnologias no setor produtivo, como a disponibilização tecnológica de fertilizantes minerais (Pereira et al, 2020;Filassi et al, 2021). De acordo com o intenso crescimento populacional, a utilização de programas de melhoramento da soja tem sido crescente e fundamental, pois contribui de forma significativa no desenvolvimento de sementes e de cultivares cada vez mais resistentes aos estresses bióticos e abióticos, eficientes na absorção de água e nutrientes, competitivas e altamente produtivas (Lopez et al, 2021).…”