Variable Rate Seeding (Planting) Maps

GeoPard provides several options how to create VRA 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.

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. 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.

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 incorporates imagery, topography, and soil brightness.

• 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: Ensure accuracy of past yield data.

  2. Generate Synthetic Yield Maps: 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 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

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.

Crop	Country	Population (Seeds/Acre)	Population (Seeds/Hectare)
Corn	USA	28,000 - 34,000
	Canada	28,000 - 34,000
	Ukraine		65,000 - 75,000
	Brazil		60,000 - 70,000
	Australia		70,000 - 85,000
	Germany		70,000 - 85,000
	France		70,000 - 85,000
Wheat	USA	1,000,000 - 1,300,000
	Canada	1,000,000 - 1,300,000
	Ukraine		4,000,000 - 5,000,000
	Brazil		3,500,000 - 4,500,000
	Australia		4,000,000 - 5,000,000
	Germany		4,000,000 - 5,000,000
	France		4,000,000 - 5,000,000
Soybean	USA	140,000 - 180,000
	Canada	140,000 - 180,000
	Ukraine		350,000 - 450,000
	Brazil		300,000 - 400,000
	Australia		350,000 - 450,000
	Germany		350,000 - 450,000
	France		350,000 - 450,000
Sunflower	USA	15,000 - 22,000
	Canada	15,000 - 22,000
	Ukraine		55,000 - 65,000
	Brazil		50,000 - 60,000
	Australia		50,000 - 60,000
	Germany		50,000 - 60,000
	France		50,000 - 60,000
Canola (Rapeseed)	USA	500,000 - 800,000
	Canada	500,000 - 800,000
	Ukraine		350,000 - 450,000
	Brazil		2,200,000 - 3,500,000
	Australia		1,200,000 - 2,000,000
	Germany		1,200,000 - 2,000,000
	France		1,200,000 - 2,000,000
Sugarcane	USA	8,000 - 12,000
	Canada	N/A
	Ukraine	N/A
	Brazil		100,000 - 140,000
	Australia		100,000 - 140,000
	Germany	N/A
	France	N/A
Barley	USA	1,000,000 - 1,300,000
	Canada	1,000,000 - 1,300,000
	Ukraine		4,000,000 - 5,000,000
	Brazil		3,500,000 - 4,500,000
	Australia		2,500,000 - 3,200,000
	Germany		4,000,000 - 5,000,000
	France		4,000,000 - 5,000,000
Rice	USA	100,000 - 150,000
	Canada	N/A
	Ukraine	N/A
	Brazil		400,000 - 600,000
	Australia		250,000 - 370,000
	Germany	N/A
	France	N/A
Cotton	USA	45,000 - 55,000
	Canada	N/A
	Ukraine	N/A
	Brazil		100,000 - 120,000
	Australia		110,000 - 135,000
	Germany	N/A
	France	N/A
Sorghum	USA	40,000 - 60,000
	Canada	40,000 - 60,000
	Ukraine		100,000 - 150,000
	Brazil		90,000 - 120,000
	Australia		100,000 - 150,000
	Germany		100,000 - 150,000
	France		100,000 - 150,000

Sources:

Purdue University, University of Illinois Extension, FAO, Embrapa, Department of Agriculture and Fisheries, North Dakota State University, Alberta Wheat Commission, Grains Research and Development Corporation, National Sunflower Association, Australian Oilseeds Federation, Canola Council of Canada, USDA, European Commission - Agriculture and Rural Development

Post-Season Analysis

After the season, run statistical and 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 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

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By integrating these methods, GeoPard helps you achieve efficient and productive farming practices through precise seeding strategies.