Interactive soybean variable‐rate seeding simulator for farmers

Abstract

Seed expense is a critical component affecting soybean (Glycine max L.) production cost. Achieving potential benefits of adjusting seeding rates by yield environment requires translation from theory to practice through decision support tools. This article introduces the soybean variable-rate seeding (VRS) simulator, an interactive web-tool designed to facilitate VRS decisions. A group of agronomists and farmers provided input and feedback to the tool's original design, usability, interactive features, and tool outputs. The simulator generates variable rate seeding recommendations by (a) aggregating and classifying 3 yr of historical soybean yield maps using either yield level (low, medium, or high) or temporal yield stability (stable or unstable) classes, and (b) estimating the difference between the farmers current uniform seeding rate and the optimal seeding rates calibrated for different yield environments of the U.S. Midwest region. For each yield environment, the tool suggests a seeding rate change accompanied by an expected yield increase. Marginal economic and break-even price analyses of each VRS prescription choice are also provided considering soybean plant survival rate, seed cost, market price, and crop production costs. A step-by-step description is provided using a dataset of real, historical, on-farm soybean yield maps to illustrate the tool's features and limitations. Simulated results indicate that compared to typical fixed seeding rate choices, following the tool's recommendations could improve profits between US$5 and 57 ha -1 . The development of this tool contributes to a growing trend of user-friendly interfaces that assist in translating core agronomic knowledge into practical solutions.

Information conveyed by management zones and optimal soybean seeding rate

“…The estimated per‐hectare profit gain from applying VRS compared to URS (i.e., $${\pi ^*}\; - \;{\pi _U}$$) ranges from $0.20 to $30.60 ha −1 . The estimated profit gain is comparable in magnitude to Correndo et al.’s (2022) estimation—$5–57 ha −1 . The site‐years OH‐C1‐2017 and MI‐W1‐2018 have the highest profit gains, both near $30 ha −1 .…”

Precision Agriculture: Reviewing the Advancements, Technologies, and Applications in Precision Agriculture for Improved Crop Productivity and Resource Management

“…VRS in corn production, compared to uniform rate seeding (URS), resulted in a potential economic benefit ranging from $0.15 to $12.83 per hectare, depending on the availability of information and technology adoption (Bullock et al, 1998). In addition, implementing variable rate seeding using the soybean VRS simulator resulted in potential profit improvements ranging from $5 to $57 per hectare compared to typical fixed seeding rate choices (Correndo et al, 2022). This demonstrates the potential economic benefits of adopting VRS in different crop production systems.…”

Data integration dashboard for assessing and planning sustainable intensification agricultural interventions: a case study in Senegal

“…Focusing on these last points, Neufeldt et al (2013) suggested that a systematic gathering and integration of data, overcoming spatial and temporal dimensions differences, is needed to plan agricultural interventions to support the food security agenda. More recently, and from the agriculture side, a few digital tools were generated in a relevant effort to demonstrate a potential path forward on moving from research outcomes to actionable decisions (e.g., Laurent et al, 2021;Correndo et al, 2022). Therefore, as demonstrated by recent agricultural developments, using digital tools reduces the effort and time needed to overcome the challenges to planning agricultural interventions (McCampbell et al, 2021) and potentially increases adoption.…”