Assessing the influence of row spacing on soybean yield using experimental and producer survey data

Andrade, José F.; Edreira, Juan I. Rattalino; Mourtzinis, Spyridon; Conley, Shawn P.; Ciampitti, Ignacio A.; Dunphy, James E.; Gaska, John; Glewen, Keith; Holshouser, David Lee; Kandel, Hans; Kyveryga, Peter; Lee, Chad D.; Licht, Mark A.; Lindsey, Laura E.; McClure, Michael A.; Naeve, Seth L.; Nafziger, Emerson D.; Orlowski, John M.; Ross, Jeremy; Staton, Michael J.; Thompson, Laura J.; Specht, James E.; Grassini, Patricio

doi:10.1016/j.fcr.2018.10.014

Cited by 45 publications

(30 citation statements)

References 21 publications

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“…Our results suggest that because no differences were observed between treatments, strip‐till and/or banded fertilizer may contribute to the improved yield at 30‐inch row spacing. These results are inconsistent with Andrade et al (2019), who used a database of experimental and producer data from across the United States and found that growers in northern and southern regions of the United States gained significantly greater soybean yield with narrow rows (i.e., 15 inches) than with wide rows (i.e., 30 inches). However, soybean's yield response to narrow‐row spacing in high‐yielding environments, particularly the central United States, was less consistent (Andrade et al, 2019).…”

Section: Resultscontrasting

confidence: 63%

“…These results are inconsistent with Andrade et al (2019), who used a database of experimental and producer data from across the United States and found that growers in northern and southern regions of the United States gained significantly greater soybean yield with narrow rows (i.e., 15 inches) than with wide rows (i.e., 30 inches). However, soybean's yield response to narrow‐row spacing in high‐yielding environments, particularly the central United States, was less consistent (Andrade et al, 2019). To further understand the effect of strip‐till on soybean seed yield, more small‐plot and on‐farm research may be needed.…”

Section: Resultscontrasting

confidence: 63%

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Effect of Strip-Till Timing, Fertilizer Placement, and Row Spacing on Soybean Seed Yield

Potratz

Mourtzinis

Gaska

et al. 2019

Crop, Forage & Turfgrass Management

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Core Ideas A reduction in penetration resistance was observed in the rooting zone of fall and spring strip‐till rows compared with no‐till rows. Spring strip‐till reduced penetration resistance at more depths than fall strip‐till. There was no yield response of strip‐till compared with no‐till in the small‐plot study. There was no difference in plant population or yield between strip‐till or no‐till in the on‐farm study. The perceived yield deficit normally associated with 30‐in row spacing was reduced with the use of strip‐till. Alleviation of cold, wet, compacted soil is a major concern for Wisconsin soybean [Glycine max (L.) Merr.] growers because of the narrow harvest and planting windows in spring and fall. Strip‐till, which combines benefits of intensive tillage in crop rows and no‐till between crop rows, has emerged as a viable conservation tillage option to alleviate these issues while maintaining soil structure and health. Though strip‐till's yield response in corn (Zea mays L.) is well documented, soybean's yield response has been studied less. This study aims to: (i) quantify the effect of no‐till and strip‐till timing, crop row spacing, and fertilizer placement on soybean plant population, canopy coverage, and seed yield; (ii) evaluate no‐till and strip‐till timing and/or crop row spacing on soil temperature and penetration resistance; and (iii) determine the best management recommendations for strip‐till use in Wisconsin soybean production systems. A small‐plot experiment was conducted in Arlington, WI, during the 2016, 2017, and 2018 growing seasons and an on‐farm experiment was conducted in Sharon, WI, during the 2016 and 2017 growing seasons. In the small‐plot trial, 15‐inch spring strip‐till (66.5 bu acre‐1) yielded 6.7% more than 15‐inch fall strip‐till (62.0 bu acre‐1). There was no difference in yield between the 15‐inch and 30‐inch row spacings across all tillage treatments. Plant population in the small‐plot trial was 17,000 plants acre‐1 (15.5%) greater at the 30‐inch row spacing than at the 15‐inch row spacing. In the on‐farm trial, no differences were observed among treatment combinations. Overall, results suggested that there were no differences in yield when comparing strip‐till and no‐till for soybean production.

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Section: Resultscontrasting

confidence: 63%

Section: Resultscontrasting

confidence: 63%

Effect of Strip-Till Timing, Fertilizer Placement, and Row Spacing on Soybean Seed Yield

Potratz

Mourtzinis

Gaska

et al. 2019

Crop, Forage & Turfgrass Management

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“…Under wet conditions, the 38‐cm row spacing results in excessive moisture build‐up in the canopy favoring the development of Sclerotinia stem rot. Consistent with this result, Andrade et al (2019) found that, in the central United States, July rainfall was higher in the experiments showing a yield advantage using wide row spacing. Soybean producers should be aware that the conclusion given by published data using small plot studies do not necessarily agree with the conclusions from OFRN.…”

Section: Creating a Data‐analytics Frameworksupporting

confidence: 57%

A Framework for Visualization and Analysis of Agronomic Field Trials from On‐Farm Research Networks

et al. 2019

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An on‐farm research network is an organization of farmers that conducts agronomic experiments under local conditions. It is common that an elementary statistical analysis be conducted for individual studies. However, there is unexplored potential in detecting yield response variability patterns for better decision making. We developed a data‐analytics framework and web‐application program that allows users to analyze multiple studies that use a common protocol and can identify the conditions where an imposed treatment may or may not be effective. The development of this data‐analytics framework is needed to improve predictions at the farm level that can lead to more cost‐effective, sustainable and environmentally sound agricultural production. Data visualization is an important part of data‐analytics. In this paper, we have developed and tested a Bayesian hierarchical model that can be used to assess the general agronomic performance of different management practices. Decision making related to new management practices should be based on the complete evidence, local conditions and economic considerations. The web‐application includes dynamic data visualization features to enhance communication and sharing of information with the goal to reach a broader audience. Core Ideas We develop a data‐analytics framework and web‐application for on‐farm research trials. A Bayesian hierarchical model quantifies the uncertainty in yield response. The model helps assess alternative practices, products, and technologies among trial locations. The framework provides a reactive break‐even economic analysis of alternative management practices.

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“…In contrast, HYLs can maximize yield across a much wider range of plant stands and attrition rates, likely due to a higher plant growth rate and ability to intercept more PAR as previously hypothesized. The use of seed treatments (Gaspar et al., 2014), appropriate tillage and planting practices (Oplinger and Philbrook, 1992), narrow rows (Andrade et al., 2019; De Bruin & Pedersen, 2008b), and adequate fertility are all components which can maximize early season stand and minimize in season plant attrition to ensure adequate late season stands are achieved which is particularly important in medium and low yield levels. Yet, growers will continually encounter greater attrition rates as seeding rate increases, further supporting the limited yield and risk benefits from increasing seeding rates above the AOSR.…”

Section: Resultsmentioning

confidence: 99%

Defining optimal soybean seeding rates and associated risk across North America

et al. 2020

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Soybean [Glycine max (L.) Merr.] seeding rate research across North America is typically conducted in small geo-political regions where environmental effects on the seeding rate × yield relationship are minimized. Data from 211 individual field studies (∼21,000 data points, 2007-2017) were combined from across North America ranging in yield from 1,000-7,500 kg ha −1 . Cluster analysis was used to stratify each individual field study into similar environmental (soil × climate) clusters and into high (HYL), medium (MYL), and low (LYL) yield levels. Agronomically optimal seeding rates (AOSR) were calculated and Monte Carlo risk analysis was implemented. Within the two northern most clusters the AOSR was higher in the LYL followed by the MYL and then HYL. Within the farthest south cluster, a relatively Abbreviations: AOSR, agronomically optimal seeding rate; CIPAR, cumulatively intercepted photosynthetically active radiation; HYL, high yield level; LYL, low yield level; MYL, medium yield level; NCCPI, national commodity crop productivity index; PAR, photosynthetically active radiation; VRS, variable rate seeding.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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Assessing the influence of row spacing on soybean yield using experimental and producer survey data

Cited by 45 publications

References 21 publications

Effect of Strip-Till Timing, Fertilizer Placement, and Row Spacing on Soybean Seed Yield

Effect of Strip-Till Timing, Fertilizer Placement, and Row Spacing on Soybean Seed Yield

A Framework for Visualization and Analysis of Agronomic Field Trials from On‐Farm Research Networks

Defining optimal soybean seeding rates and associated risk across North America

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