Shoot/Root Interactions Affect Soybean Photosynthetic Traits and Yield Formation: A Case Study of Grafting With Record-Yield Cultivars

Abstract

Improvement of soybean [ Glycine max (L.) Merr.] yield and photosynthesis physiology have been achieved over decades of cultivar breeding. Identification of the mechanisms involved in shoot-root interactions would be beneficial for the development of yield improvement breeding strategies. The objectives of this study were to investigate soybean shoot-root interactions with different-year released soybean cultivars and to evaluate their effects on grain yield and yield components. Soybean grafts used in this study were constructed with two record-yield cultivars Liaodou14 (L14) and Zhonghuang35 (Z35) and eleven cultivars released in 1966–2006 from the United States and Chinese. The grafting experiments were conducted as pot-culture experiments and repeated in 2014 and 2015. Our results showed that net photosynthesis rate ( P N ) was positively correlated to both root activity and root bleeding sap mass (RBSM) during the R6 reproductive stage. Moreover, different year-released soybean shoots had all exhibited capabilities of changing the root activity and architecture of L14 and Z35 rootstocks to “generation”-specific patterns during all reproductive stages. However, these influences were independent of the photosynthetic strength. Yield analysis had demonstrated that high-yielding root systems (L14 and Z35 rootstocks) could cause more than 15% of yield increase in seven out of eleven common scions in a scion-genotype-dependent manner. For Williams-descendant cultivar scions, L14 and Z35 rootstocks promoted yields mainly by increasing the seed number (SN), but those scions of Amsoy-descendent cultivars showed mainly seed weight (SW) increases when grafted onto L14 and Z35 rootstocks. On the other hand, although most tested common rootstocks did not show significant influence over the final yields in record-yield L14 and Z35 scions, they were obviously capable of shifting the formation of yield components when compared to L14 and Z35 self-grafting controls. Taken together, soybean shoots could influence the root physiology and played a crucial role in the determination of yield potentials. Synergistically with shoots, soybean roots played a more supportive role during the realization of yield potentials through root activities and by balancing the formation of yield components. These findings provided interesting insightful information for developing new breeding strategies which aim to pyramid elite physiological and yield traits by selecting specific parental combinations.

Application of machine learning and genetic optimization algorithms for modeling and optimizing soybean yield using its component traits

“…A negative correlation between the total soybean seed yield and NRNP was found in this study. It is in agreement with previous studies claimed that increasing the number of non-reproductive nodes decreases the reproductive potential of soybean seed yield [ 81 , 85 ]. The results of linear correlation analyses in this study illustrated the importance of individual yield component traits in determining the total soybean seed yield.…”

Effect of Drought Stress at Reproductive Stages on Growth and Nitrogen Metabolism in Soybean

“…The differences between the means were compared using Tukey's multiple range test (at a p < 0.05 significance threshold), with significant differences indicated by different letters above the bars in each figure. The correlations between seed weight with physiological parameters in soybean leaves were assessed via Pearson's product-moment correlation [54]. The data presented are means (± SD) of three independent experiments.…”

Contribution of the Additive Genetic Effects in Soybean Breeding Aiming at the Agronomic Ideotype

“…The intensification of technical growing management makes it possible to increase the number of pods formed per plant (Liu et al, 2010). Thus, the selection of families with more than two pods becomes relevant, considering the possibility of having genotypes that have a high capacity for seed formation per plant, given problems arising from management, mainly in terms of chemical fertilization and water availability, are apparently surpassed by a large part of farmers (Du et al, 2019;Lopez et al, 2019). In order to select populations, those that stand out for the largest number of pos on the main stem, come from the crosses MG26 x PG17, MG23 x PG23, MG11 x PG3 and MG7 x PG5.…”