# Variable Rate Seeding (Planting) Maps ## Overview Variable Rate Seeding (VRS) or VR Planting maps are essential for optimizing seeding strategies based on field-specific conditions. Configuring VRS maps effectively can significantly enhance crop yield and resource efficiency. This guide outlines the main aspects and options for creating effective VRS maps using GeoPard's precision agriculture tools. Read more about [Variable Rate Planting in the GeoPard Blog](https://geopard.tech/blog/variable-rate-seeding-how-does-it-work). ## VRS Map Configuration Options The following are some recommended configurations for VRS maps ### **1. Field Potential Based on Imagery Only** * **Description**: Use historical imagery to create Variable Rate Seeding (VRS) maps based on the [Field Potential Maps](https://geopard.tech/blog/field-potential-maps-yield-data/). GeoPard's automated recommendation system helps identify representative years. Since predicting the next season's weather is challenging, it compensates for outlier years (e.g., balancing too dry with too wet years) to provide more accurate recommendations. [GeoPard's Automated Recommendation of Representative Years](https://geopard.tech/blog/r8yc32d9jc-multi-year-zones/).

GeoPard automatically selects imagery, nevertheless you can select other images on demand

Field Potential Zones utilized for VR Planting, automatically created based on multi-year imagery

* **Best For:** Quick start scenarios, especially when crop rotation information is available. Select years with the same crop (e.g., corn years for corn planting). ### **2. Field Potential Based on Imagery, Topography, and Soil Brightness** * **Description:** This [multi-layer approach](https://docs.geopard.tech/geopard-tutorials/product-tour-web-app/zones-maps-and-analytics/multi-layer-analytics) incorporates imagery, topography, and [soil brightness](https://geopard.tech/blog/how-the-soil-brightness-index-enables-sustainable-agriculture/). * **Configuration:** Assign negative weight to slope (to account for erosion risk) and to higher soil brightness (indicating less organic matter). ### **3. Field Potential Based on Yield, Soil Sampling/Scanning, Imagery, Topography, and Soil Brightness**

An Example of VR Seeding map based on Electrical COnductivity, Topography, Yield and Satellite imagery data

* **Description:** Integrate multiple data sources for a comprehensive field potential map. * **Steps:** 1. [**Clean and calibrate yield data**](https://docs.geopard.tech/geopard-tutorials/agronomy/yield-calibration-and-cleaning): Ensure accuracy of past yield data. 2. **Generate** [**Synthetic Yield Map**](https://docs.geopard.tech/geopard-tutorials/agronomy/synthetic-yield-map)**s**: If yield data is missing for past seasons, use GeoPard to generate these maps. Only total or average yield is needed, with an accuracy of 90%. ### **4. Equation-Based Approach for Planting**

An example of VR Seeding Soybean map based on Yield datasets

* **Description:** [Utilize customized formulas](https://geopard.tech/blog/equation-based-analytics-precision/) and any available data layers (e.g., imagery, topography, yield, soil). * **Flexibility:** Allows for tailored configurations based on specific agronomic needs. * Available also in [Batch Analytics](https://docs.geopard.tech/geopard-tutorials/changelog-and-release-notes/release/release-web-april-2024#batch-execution-of-equation-maps) ## Variable Rate Planting Recommendations Table Below is a comprehensive table of planting recommendations for various crops across multiple countries. The population recommendations are in seeds per acre for the USA and Canada and seeds per hectare for other countries.
CropCountryPopulation (Seeds/Acre)Population (Seeds/Hectare)
CornUSA28,000 - 34,000
Canada28,000 - 34,000
Ukraine65,000 - 75,000
Brazil60,000 - 70,000
Australia70,000 - 85,000
Germany70,000 - 85,000
France70,000 - 85,000
WheatUSA1,000,000 - 1,300,000
Canada1,000,000 - 1,300,000
Ukraine4,000,000 - 5,000,000
Brazil3,500,000 - 4,500,000
Australia4,000,000 - 5,000,000
Germany4,000,000 - 5,000,000
France4,000,000 - 5,000,000
SoybeanUSA140,000 - 180,000
Canada140,000 - 180,000
Ukraine350,000 - 450,000
Brazil300,000 - 400,000
Australia350,000 - 450,000
Germany350,000 - 450,000
France350,000 - 450,000
SunflowerUSA15,000 - 22,000
Canada15,000 - 22,000
Ukraine55,000 - 65,000
Brazil50,000 - 60,000
Australia50,000 - 60,000
Germany50,000 - 60,000
France50,000 - 60,000
Canola (Rapeseed)USA500,000 - 800,000
Canada500,000 - 800,000
Ukraine350,000 - 450,000
Brazil2,200,000 - 3,500,000
Australia1,200,000 - 2,000,000
Germany1,200,000 - 2,000,000
France1,200,000 - 2,000,000
SugarcaneUSA8,000 - 12,000
CanadaN/A
UkraineN/A
Brazil100,000 - 140,000
Australia100,000 - 140,000
GermanyN/A
FranceN/A
BarleyUSA1,000,000 - 1,300,000
Canada1,000,000 - 1,300,000
Ukraine4,000,000 - 5,000,000
Brazil3,500,000 - 4,500,000
Australia2,500,000 - 3,200,000
Germany4,000,000 - 5,000,000
France4,000,000 - 5,000,000
RiceUSA100,000 - 150,000
CanadaN/A
UkraineN/A
Brazil400,000 - 600,000
Australia250,000 - 370,000
GermanyN/A
FranceN/A
CottonUSA45,000 - 55,000
CanadaN/A
UkraineN/A
Brazil100,000 - 120,000
Australia110,000 - 135,000
GermanyN/A
FranceN/A
SorghumUSA40,000 - 60,000
Canada40,000 - 60,000
Ukraine100,000 - 150,000
Brazil90,000 - 120,000
Australia100,000 - 150,000
Germany100,000 - 150,000
France100,000 - 150,000
#### Sources: Purdue University, University of Illinois Extension, [FAO](https://www.fao.org/), [Embrapa](https://www.embrapa.br/), Department of Agriculture and Fisheries, North Dakota State University, [Alberta Wheat Commission](https://www.albertawheat.com/), [Grains Research and Development Corporation](https://grdc.com.au/), [National Sunflower Association](https://www.sunflowernsa.com/), [Australian Oilseeds Federation](https://www.australianoilseeds.com/), [Canola Council of Canada](https://www.canolacouncil.org/), [USDA](https://www.usda.gov/), [European Commission - Agriculture and Rural Development](https://ec.europa.eu/agriculture/index_en) ### Post-Season Analysis After the season, run [statistical and trial analytics](https://docs.geopard.tech/geopard-tutorials/agronomy/field-trial-analytics) to calculate yield output and profit maps based on yield data. This will enable optimization of the VRS map for the next season. ### More PrecisionAg use-cases Refer to the [GeoPard PrecisionAg use cases PDF](https://docs.geopard.tech/geopard-tutorials#product-overview-and-use-cases) for visual examples and further insights. ### How to Start Using GeoPard's advanced tools and methodologies, you can optimize your seeding strategies, improve crop yields, and ensure sustainable agricultural practices. To start, register free at [app.geopard.tech](https://app.geopard.tech) *** By integrating these methods, GeoPard helps you achieve efficient and productive farming practices through precise seeding strategies.