Phenological and quantitative plant development changes in soybean cultivars caused by sowing date and their relation to yield

Pierozan, Clovis; Kawakami, Jackson; Bridi, Marcelo; Müller, Marcelo Marques Lopes; Conte, Murilo Viotto Del; Michalovicz, Leandro

doi:10.5897/ajar2014.9325

Cited by 13 publications

(4 citation statements)

References 29 publications

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“…One of the ways to increase average yield of this crop is to reduce key biotic and abiotic factors that affect soybean yield through sowing date adaptations. For example, late sowings often limit soybean yield potential because the flowering and seed filling phase coincides with periods characterized by elevated summer temperatures and frequent drought events ( Zhang et al, 2010 ; Hu, 2013 ; Clovis et al, 2015 ). This is especially true for southern European regions including South-West of France which is one of the two key French soybean production regions ( Terres Inovia, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean

et al. 2020

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Soybean emergence and yield may be affected by many factors. A better understanding of the cultivar x sowing date x environment interactions could shed light into the competitiveness of soybean with other crops, notably, to help manage major biotic and abiotic factors that limit soybean production. We conducted a 2-year field experiments to measure emergence dynamics and final rates of three soybean cultivars from different maturity groups, with early and conventional sowing dates and across three locations. We also measured germination parameter values of the three soybean cultivars from different maturity groups under controlled experiments to parametrize the SIMPLE crop emergence model. This allowed us to assess the prediction quality of the model for emergence rates and to perform simulations. Final emergence rates under field conditions ranged from 62% to 92% and from 51% to 94% for early and conventional sowing, respectively. The model finely predicted emergence courses and final rates (root mean square error of prediction (RMSEP), efficiency (EF), and mean deviation (MD) ranging between 2% to 18%, 0.46% to 0.99%, and −10% to 15%, respectively) across a wide range of the sowing conditions tested. Differences in the final emergence rates were found, not only among cultivars but also among locations for the same cultivar, although no clear trend or consistent ranking was found in this regard. Modeling suggests that seedling mortality rates were dependent on the soil type with up to 35% and 14% of mortality in the silty loam soil, due to a soil surface crust and soil aggregates, respectively. Non-germination was the least important cause of seedling mortality in all soil types (up to 3% of emergence losses), while no seedling mortality due to drought was observed. The average grain yield ranged from 3.1 to 4.0 t ha −1 , and it was significantly affected by the irrigation regime ( p < 0.001) and year ( p < 0.001) but not by locations, sowing date or cultivars. We conclude that early sowing is unlikely to affect soybean emergence in South-West of France and therefore may represent an important agronomic lever to escape summer drought that markedly limit soybean yield in this region.

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Section: Introductionmentioning

confidence: 99%

Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean

et al. 2020

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“…The interception capacity of crops on both direct and diffuse solar radiation is expected to increase under a horizontal canopy of dense seeding [5]. However, closed canopy profile also results in large within-canopy shading, which subsequently induces shade avoidance response and promotes lodging by excessive vegetative growth [6]. Kokubun (1988) investigated the characteristics of high-yielding soybean cultivars and proposed a high-yield ideotype model with the upper leaves vertically closed.…”

Section: Introductionmentioning

confidence: 99%

Genetic Analysis and Gene Mapping for a Short-Petiole Mutant in Soybean (Glycine max (L.) Merr.)

et al. 2019

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Short petiole is a valuable trait for the improvement of plant canopy of ideotypes with high yield. Here, we identified a soybean mutant line derived short petiole (dsp) with extremely short petiole in the field, which is obviously different from most short-petiole lines identified previously. Genetic analysis on 941 F2 individuals and subsequent segregation analysis of 184 F2:3 and 172 F3:4 families revealed that the dsp mutant was controlled by two recessive genes, named as dsp1 and dsp2. Map-based cloning showed that these two recessive genes were located on two nonhomologous regions of chromosome 07 and chromosome 11, of which the dsp1 locus was mapped at a physical interval of 550.5-Kb on chromosome 07 near to centromere with flanking markers as BARCSOYSSR_07_0787 and BARCSOYSSR_07_0808; whereas, the dsp2 locus was mapped to a 263.3-Kb region on chromosome 11 with BARCSOYSSR_11_0037 and BARCSOYSSR_11_0043 as flanking markers. A total of 36 and 33 gene models were located within the physical genomic interval of dsp1 and dsp2 loci, respectively. In conclusion, the present study identified markers linked with genomic regions responsible for short-petiole phenotype of soybean, which can be effectively used to develop ideal soybean cultivars through marker-assisted breeding.

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“…However, it can also promote selfshading and lodging by excessive vegetative growth [80]. When the photoperiod is prolonged in the moment of grain filling, it permits a higher duration of this phase, enabling an increase in the seeds through a higher number of nodes and more legumes per node [81].…”

Section: Crop Managements and Their Impacts On Architecture Modificationmentioning

confidence: 99%

Soybean Architecture Plants: From Solar Radiation Interception to Crop Protection

Chavarria¹,

Caverzan²,

Müller³

et al. 2017

Soybean - The Basis of Yield, Biomass and Productivity

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The soybean plant architecture in relation to better solar radiation interception and production gain is an aspect that requires a better understanding, since soybean is an important crop worldwide. The genetic traits, management and environmental conditions are points that further extend the range of issues on crop productivity. The light quality is measured by the red/far-red (R/FR) ratio (R ∼ 660 nm, FR ∼ 730 nm). This affects the plant growth and morphological developments in different ways. The plant leaves change their angle during the day to better intercept radiation. This heliotropic movement and some computational models together have been used to enhance some agricultural practices. Soybean plant is dependent on the interaction between genotype and environment. Thus, the enhanced understanding in relation to photosynthetic activity, grain yield by light interception efficiency and culture protection managements in soybean are covered.

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Phenological and quantitative plant development changes in soybean cultivars caused by sowing date and their relation to yield

Cited by 13 publications

References 29 publications

Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean

Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean

Genetic Analysis and Gene Mapping for a Short-Petiole Mutant in Soybean (Glycine max (L.) Merr.)

Soybean Architecture Plants: From Solar Radiation Interception to Crop Protection

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