SoilOptix® Data Analysis in Precision Agriculture Platform GeoPard

The importance of healthy soil systems in agriculture have been historically undervalued, but innovative agtech companies like СоилОптикс® are shifting this paradigm with data that supports both farmers and local environments. 

Precision agriculture is creating increasingly economic and sustainable systems with modern technologies that can measure vital aspects of land composition, ensuring crops and livestock are managed as efficiently as possible.

SoilOptix ® facilitates this type of sustainable land management by enabling the accurate collection of soil data without doing a labour-intensive soil sampling. 

Soil Data & Variable Rate Application (VRA) maps

A main reason for global topsoil loss has been the mismanagement of fertilizers, pesticides, irrigation systems, and other agro-inputs on a large scale. It is not economically feasible to apply the same amount of, for example, high Nitrogen fertilizers over an area where only a fraction is lacking in Nitrogen.

Variable rate Lime application based on SoilOptix® pH levels. The cost of product is calculated by GeoPard

This is also commonly done with the comprehensive application of lime to balance out acidic soils, despite the fact that only a few specific soil patches with a low pH may need it. Assuming a monotonous soil composition across large areas simplifies what is one of nature’s most complex systems.

This is where SoilOptix® data contributes immense value to farmers, who can view maps that specify exactly where and in what quantities different types of fertilizers and other inputs need to be applied via VRA.

This not only saves costs for farmers, but also contributes to the longevity of that land parcel, which may have otherwise been over-fertilized and expedited the eutrophication of nearby lakes and water sources.

Precision agriculture is all about providing agricultural systems with tools for economic and sustainable development, and this is demonstrated by using soil data to maintain and create healthy soil systems that are actually cheaper to amend. As GeoPard co-founder Dmitry Dementiev says:

“Modern precision agriculture is the synergy of agronomy, technology, software, hardware, all of which optimize sustainable and economic decision making. We are happy to work with SoilOptix®, and analyze soil data from the soil ground scanners to provide real time value to agronomists.” 

Understanding SoilOptix® data through GeoPard

Importing SoilOptix® data into GeoPard can simplify the process of understanding soil mineral composition by providing clearly mapped value gradients that are designed for VRA.

The variety of soil elements that SoilOptix® technology measures can be viewed with different layers in GeoPard, and can be compared and contrasted to better visualize patterns and correlations in a land parcel.

It is also possible to create Rx maps with a multi-layer approach, where users can combine and cross-analyze SoilOptix® data with GeoPard data sets like historical vegetation, topography, yield, or soil moisture.

“The appetite for soil data as part of this modern precision agriculture system is ever increasing as demand for a more healthy soil landscape evolves. We are happy to have GeoPard as part of the platforms working with SoilOptix® data to enable growers and agronomists with the tools to accurately and visually analyze and manage their fields.” – Закари Хармер, North America Sales & Global Support Manager at SoilOptix®

Moreover, GeoPard is capable of automatically create a complete topography profile with soil scanners data and with the latest updates also to create a 3d map of a scanned field. 

3d map of a field was created in GeoPard Agriculture platform using the data from SoilOptix® scanner. The 3d map is overlaid by pH management zones (later used for variable rate lime application) from SoilOptix®.

This data compatibility between GeoPard and SoilOptix® exemplifies the expression ‘work smarter not harder’, by providing agribusinesses and agronomists with the tools and multi-layer analysis needed to optimize yields and save costs on inputs.