Spatial and temporal plant-to-plant variability effects on soybean yield

Masino, Alejandra; Rugeroni, Pablo; Borrás, Lucas; Rotundo, José L.

doi:10.1016/j.eja.2018.02.006

Cited by 37 publications

(34 citation statements)

References 36 publications

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“…The lack of a relationship between plant‐to‐plant variability and grain production in soybean further supports the conclusion that uniformity of biomass accumulation within a crop stand is not a good indicator of yield in soybean. Even in highly productive soybean stands in field conditions, high‐yielding plants and low‐yielding plants coexist, and stability in reproductive partitioning may compensate for differences in overall biomass (Masino et al., 2018).…”

Section: Resultsmentioning

confidence: 99%

“…The CV of grain yield (Figure 1) matched that of biomass at R8, which was expected due to the lack of treatment differences in harvest index values. The CVs of biomass production and yield may not have a relationship because of both phenotypic and reproductive plasticity in soybean compared with corn (Andrade & Abbate, 2005; Masino, Rugeroni, Borras, & Rotundo, 2018), which allows for dominated and dominant plants to coexist in high‐yielding plant stands. Hierarchies established early in the season may become more pronounced as dominant plants continue to outcompete dominated plants for resources, leading to an increase in plant‐to‐plant variability in biomass.…”

Section: Resultsmentioning

confidence: 99%

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Plant‐to‐plant biomass and yield variability in corn–soybean rotations under three tillage regimes

O’Brien

Hatfield

2021

Agronomy Journal

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Agronomic management practices have the potential to affect plant‐to‐plant variability of biomass accumulation and grain production. However, the relationship between the variability of crop production per plant (i.e., grain weight) and crop production per unit area (i.e., grain yield) is inconsistent because high variability in grain weight has been linked with lower yields in some instances but not others. The objective of this experiment was to investigate plant‐to‐plant variability of biomass accumulation and grain production at three developmental stages in corn (Zea mays L.)–soybean (Glycine max [Merr.] L.) rotations under conventional tillage, strip tillage, and no tillage. Plant‐to‐plant biomass variability, as measured by the coefficient of variation (CV) of crop biomass at three phenological stages, decreased throughout the growing season in corn but increased in soybean; these trends did not differ among tillage systems but did change among the 4 yr of the experiment. The CV of grain weight per corn plant was higher in no‐till for two of the study years, suggesting an interaction between tillage and weather patterns that affects variability. Overall, mean grain weight per plant increased as CV of grain weight decreased in corn but not in soybean. This finding suggests that corn yields were maximized when all individual plants were producing relatively similar amounts of grain, whereas this relationship was not present in soybean. The findings of this study indicate that tillage practices do not consistently affect plant‐to‐plant variability of biomass or grain production and must be understood in context of weather conditions and other agronomic management practices.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Plant‐to‐plant biomass and yield variability in corn–soybean rotations under three tillage regimes

O’Brien

Hatfield

2021

Agronomy Journal

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“…Unequal plant growth results in yield losses [8]; this is true even for the soybean, despite its capability to compensate [9]. Specifically, in contrast to the historical expectation that soybeans compensate for their non-uniformity, new research has proven that this is not the case [9]. Non-uniformity in the field could be created by the day of emergence of plants in the field [10].…”

Section: Introductionmentioning

confidence: 99%

Soybean Seed Vigor: Uniformity and Growth as Key Factors to Improve Yield

et al. 2020

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Emergence uniformity and the time required for emergence are essential factors for obtaining highly productive potential in plants. Factors such as sowing depth and soil moisture affect uniformity and emergence, but little is known about the impacts of seed vigor. Thus, we determined the impacts of seed vigor on uniformity and growth as well as development and yield in soybean (Glycine max [L.] Merrill) plants. The treatments consisted of four vigor levels (89%, 57%, 47%, and 43%) obtained by accelerated aging, in a randomized block design, with five replicates at three sites. Seeds with the highest vigor level showed higher uniformity and faster emergence. Dominated plants through their phenotypic plasticity modify stem diameter and internode length. The plants that emerged earlier had a larger leaf area in the three stages (V1, V4, and R2), allowing them to accumulate more photoassimilates in the initial stages. Consequently, these plants exhibited an increase in yield components, especially in the number of fertile nodes and the number of pods per plant, making them more productive.

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“…Management decisions can be crucial for optimizing soybean yield and include the selection of an adequate genotype, sowing date (Di Mauro, Cipriotti, Gallo, & Rotundo, 2018; Rattalino Edreira et al., 2017), fertilization (Sucunza, Gutierrez, Garcia, Boxler, & Rubio, 2018), application of fungicide (Grassini et al., 2015) and insecticide, inoculation (Leggett et al., 2017), stand density (DeBruin & Pedersen, 2008; Masino, Rugeroni, Borrás, & Rotundo, 2018), row spacing (Andrade et al., 2019; Andrade, Calviño, Cirilo, & Barbieri, 2002), and crop rotation schemes (Seifert, Roberts, & Lobell, 2017), among others. Environmental variables known to affect yield include weather variables like temperature, solar radiation, rainfall amount (Andrade & Satorre, 2015) and distribution (Calviño, Sadras, & Andrade, 2003), potential evapotranspiration (Grassini et al., 2015), and soil type (Di Mauro et al., 2018), among others.…”

Section: Introductionmentioning

confidence: 99%

Sowing date, genotype choice, and water environment control soybean yields in central Argentina

Vitantonio‐Mazzini

Gómez²,

Gambín

et al. 2020

Crop Science

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Soybean [Glycine max (L.) Merr.] is one of the most important crops worldwide, and Argentina is the third largest global grain producer and the worlds´ largest meal exporter. Under the continuous challenge of increasing crop yields, especially in the central temperate region of the country, there is a growing need to optimize management in relation to the environment that each specific farm and paddock presents. Understanding the impact of available technologies and management options can help optimize crop design. Here, we identify and quantify the effect of the most relevant variables affecting soybean yield by analyzing a database that includes 53 field trials with four common commercial genotypes, reporting 50 management and environmental variables. Linear mixed‐effect models revealed that two management decisions (genotype and sowing date selection) and three environmental variables (rainfall during the reproductive crop period from R1 to R7, soil type [Hapludoll vs. Argiudoll], and water table presence above or below 2 m of depth from the surface) helped explain ∼40% of total yield variability, which ranged from 1,675 to 7,226 kg ha−1 and averaged 5,133 kg ha−1. Water table presence generated higher and more stable yields particularly in coarse‐textured Hapludolls and under low‐rainfall conditions. Results highlight specific management and environmental conditions that affect soybean crop yields in the region, pointing to effective pathways toward yield gap reductions.

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Spatial and temporal plant-to-plant variability effects on soybean yield

Cited by 37 publications

References 36 publications

Plant‐to‐plant biomass and yield variability in corn–soybean rotations under three tillage regimes

Plant‐to‐plant biomass and yield variability in corn–soybean rotations under three tillage regimes

Soybean Seed Vigor: Uniformity and Growth as Key Factors to Improve Yield

Sowing date, genotype choice, and water environment control soybean yields in central Argentina

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