Branch development responses to planting density and yield stability in soybean cultivars

Agudamu,; Yoshihira, Taiki; Shiraiwa, Tatsuhiko

doi:10.1080/1343943x.2016.1157443

Cited by 50 publications

(44 citation statements)

References 26 publications

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“…positive linear relationships between R:FR and photosynthetic photon flux density transmittance in maize, soybean, and wheat canopies (Sattin et al, 1994). The numbers of branches and sub-branches were greater at the low planting density (D12) than at the high planting density (D18) (Figure 3; Table 2), as previously reported (Carpenter & Board, 1997;Norsworthy & Shipe, 2005;Agudamu et al, 2016). The numbers were significantly higher in Hatsusayaka than in Sachiyutaka throughout growth (Figure 3) and at maturity (Table 2), also as previously reported (Saruta et al, 2012).…”

Section: Leaf Greenness and Slasupporting

confidence: 72%

“…This system measures PAR above and below the canopy simultaneously, using a sunshine sensor placed at the center of the field higher than the canopy height and a 1-m probe that contains 64 PAR sensors is inserted into the canopy at the ground level, perpendicular to the row direction. The 1-m probe was connected with the sunshine sensor using a 25-m cable and was attached to a unlike in Japanese cultivars, in which yield declined with decreasing planting density (Agudamu et al, 2016). Despite the significant contribution of branch number to yield in soybean, however, information about the relationship between branching performance and the light environment within a canopy is still limited.…”

Section: Measurementsmentioning

confidence: 99%

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Changes in radiation interception and R:FR over time and with canopy depth of two soybean cultivars with different branching characteristics

Toyota

Maitree

Chomsang

2017

Plant Production Science

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Section: Leaf Greenness and Slasupporting

confidence: 72%

Section: Measurementsmentioning

confidence: 99%

Changes in radiation interception and R:FR over time and with canopy depth of two soybean cultivars with different branching characteristics

Toyota

Maitree

Chomsang

2017

Plant Production Science

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“…The yield components most sensitive to the increase in atmospheric [CO 2 ] are the number of lateral branches, number of racemes in the main stem [34,77,79]. The number of pods formed will depend on the number on productive nodes formed on branches and in the main stem.…”

Section: Discussionmentioning

confidence: 99%

“…Avoid intra-specific competition in future scenario by CO 2 -increases, implies the need to avoid negative effects of intra-specific competition, such as self-shading [77,79,83], or the development of modern cultivars with narrow canopy and short branches. Thus, the current trend of the breeding soybean programs to decreasing © 2019 The Author(s).…”

Section: Discussionmentioning

confidence: 99%

“…High yields were found with increased spacing under elevated CO 2 concentration [76]. In the evaluations of branch ontogeny or length of branches, the greatest branching plasticity of the US cultivars compared with Japanese cultivars should also be considered, together the inverse relation between the total length of branches and the density of plants [77].…”

Section: Changes In Plant Height Branches and Racemesmentioning

confidence: 99%

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Yield Components and Biomass Partition in Soybean: Climate Change Vision

Pereira-Flores¹,

Justino²

2019

Soybean - Biomass, Yield and Productivity

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Long-term climate change and inter-annual climate variability are events of concern to farmers and humanity. Global warming could affect agriculture in various ways and it is anticipated that agricultural systems will face great pressure from the variability of climate factors and their extreme events, which in most cases are difficult to predict, particularly extreme events of rainfall, higher dry season, hot and cold waves and their interactions. Global warming could also have some positive effects for plants such as increasing the temperature of current cold regions and increasing carbon dioxide with its positive effect on photosynthesis, growth rates, the use of water and production. Meanwhile, there are still many questions that remain about this possible future. This chapter, brings the response of plants to future conditions through specifics alterations in its components of yield on environmental conditions with enrichment of CO 2 and elevated temperature, two climatic factors, which is understood to be the factors of climatic change of greater global extent. The study of the components of yield and their alterations, can guide diverse sectors of the sciences and decision makers, in order to structure strategies of resilience in the cultivation of soybean. 2 level. This anticipated knowledge may be important for the direction of policies and research lines in various areas of agricultural sciences to develop diverse resilience strategies to climate change.The understanding of how climate influences the growth, development and production of soybean plants depends on the understanding of how the yield components respond to the variations of climate factors, which can also be elucidated if studies the plant alterations in the future atmosphere conditions. The plant production is determined by changes in yield components, in last instance. The artificial enrichment of the growth environment of soybean plants with CO 2 , O 3 and temperatures according to the forecasts on the atmospheric composition for the year 2100, can allow to know the morphophysiological responses in several levels of the plant organization, long before environmental changes occur.The study of the morphophysiological mechanisms of response of soybean plants to the ecological environment where they develop and produce grains, constitutes the basis of soybean ecophysiology.The factors of the climate (temperature, radiation, rainfall, wind and atmospheric pressure, among others), plus the physicochemical properties of the soil and the cultural practices applied in the field continuously influence the performance of the community of soya plants from germination to the senescence of the plants. Throughout the different phenological stages, the expression of stage-tissue genes defines the course of the development of the plant, the formation of the biomass and its components (roots, stems, leaves, flowers, fruits and seeds) respond simultaneously and hierarchically with the objective of completing its biological cycle and producing seeds for the...

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Minimum optimal seeding rate for indeterminate soybean cultivars grown in the tropics

et al. 2020

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The minimum optimal seeding rate in soybean [Glycine max (L.) Merr.] is the least seeds required to achieve optimal yield. This is a function of the crop phenotypic plasticity in response to plant density. However, the effect of seeding rate reduction on the seed composition and yield of cultivars with contrasting branching potentials needs to be better elucidated. The objectives were to evaluate the impacts of reducing the seeding rate on production and to quantify the minimum optimal seeding rate for seed, oil, and protein yield in soybean cultivars with contrasting plant architectures. The field experiment was conducted for two growing seasons in a 5 × 2 factorial scheme in a randomized complete block design with five replications. The treatments consisted of five seeding rates (100, 80, 60, 40, and 20% of the recommended seeding rate) and two indeterminate cultivars (BRS 1010IPRO and NS 5959IPRO). Both cultivars showed a minimum optimal seeding rate below the recommended rate. Pods per m 2 and the number of seeds per pod were the yield components responsible for the compensatory effect in response to lowering the seeding rate. Thousand seed weight was the main yield component responsible for yield loss below the minimum optimal seeding rate. Both cultivars showed high branch yield in response to seeding rate reduction. BRS 1010IPRO has a higher potential for seeding rate reduction than NS 5959IPRO. The minimum optimal seeding rate for seed yield in NS 5959IPRO led to lower protein yield and higher oil yield.Abbreviations: GS, growing season; MOSR, minimum optimal seeding rate; SR, seeding rate.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Branch development responses to planting density and yield stability in soybean cultivars

Cited by 50 publications

References 26 publications

Changes in radiation interception and R:FR over time and with canopy depth of two soybean cultivars with different branching characteristics

Changes in radiation interception and R:FR over time and with canopy depth of two soybean cultivars with different branching characteristics

Yield Components and Biomass Partition in Soybean: Climate Change Vision

Minimum optimal seeding rate for indeterminate soybean cultivars grown in the tropics

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