Today’s farmers are faced with many challenges including feeding a growing population, providing a livelihood for themselves, and protecting the environment.
Farmers make everyday decisions related to farming such as how much fertilizer to be applied, time of application, the specific area to be applied, which resources are needed for plant protection, and related aspects based on limited information, traditional knowledge, and hearsay.
This can lead to wastage of resources, greater costs, and unsustainable farming in the longer run.
Precision agriculture involves the application of technologies and agronomic principles to manage all aspects of agricultural production to improve crop performance and minimize environmental impact.
What is precision agriculture?
The International Society of Precision Agriculture defines it as “a management strategy that gathers, processes and analyzes temporal, spatial and individual data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production.”
Precision agriculture uses information and knowledge via physical inputs and benefits the environment by the targeted use of inputs that reduce fertilizer losses from excess applications and the reduction of losses due to nutrient imbalances, weed escapes, insect damage while also reducing environmental loading.
The concepts of precision agriculture and sustainability are inextricably linked. From the first time, a global positioning system was used in agriculture, the potential for environmental benefits became apparent.
Intuitively, applying fertilizers and pesticides only where and when they are needed, helps reduce carbon footprint.
Why precision agriculture is not enough?
Precision agriculture was a major innovation when it came about in the 1990s but on its own today, it’s simply not enough!
In the world of modern applications, stand-alone data in silos is of little use to application developers and operators and cannot enable evidence-based decision-making.
These silos and the manual processing required, limit the benefits of technology for the farmer.
The future of agriculture is in precision agriculture big data analytics. These combined with interconnected systems provide for maximum efficiency, profitability, and sustainability.
Silos are for grain, not data!
When we think silos, we usually imagine the large metal or concrete structures that dot the landscapes of farming areas and are usually filled with commodity crops like corn or wheat.
Grain silos make good sense for farmers because grain from hundreds of miles around can be pooled and because it is all the same crop, it can be sold as a uniform commodity.
In computing, the term “silos” has also become a great visual analogy for many of the problems with IT and software development. Data silos occur naturally as each department in an organization collects and stores its own data for its own purposes.
This type of disconnect is evident in agricultural data silos too.
Related types of data are dumped into purpose-built databases with monitoring data in one place, financial in another, and crop information and inventory in a third.
Vast quantities of data are stored in these so-called stand-alone agricultural data silos and because of their lack of interconnectivity, cannot maximize the benefits of 21st-century advances in agricultural technology.
The importance of breaking data silos
One of the greatest challenges that crop growers and researchers face today is the fragmentation of data sources with valuable information being stored in these agricultural data silos.
Legacy systems are often difficult to connect and manage and inherited systems often don’t speak to your current ones.
The ability to connect these agricultural data silos is the way of the future. It can lead to innovation, collaboration, and cross-functional operations.
But just collecting and analyzing your data to solve the immediate need is not going to cut it. Real value begins in moving to a more proactive approach, providing the ability to fully benefit from your data, which is what breaking down silos is all about.
Maximizing transformation of big data into actionable insights
Having access to big data is great, but to benefit from it, this data needs to be transformed into something actionable.
Several parameters influence agricultural growing practices including changes in the weather, temperature, rain, and soil pH which can all be accurately measured.
When these are properly integrated, they enable the farmer to not only carry out sound precise agriculture but also to be able to make extemporaneous adjustments based on changes in weather and wind and make accurate calculations regarding fertilizer type and application rates.
Agriculture 4.0
Smart Agriculture or Agriculture 4.0 is a combination of big data and precision agriculture in conjunction with smart devices, drones, sensors, and GPS which have revolutionized farming.
These inputs combined with the correct software can assist decision-making based on solid evidence.
This evidence-based decision-making leads to improvements in the accuracy of fertilizer application, reduced costs, and better quality of produce.
Thanks to the introduction of the internet of things (IoT), precision agriculture big data analytics, and artificial intelligence, it is now possible to manage a larger amount of information and decision-making more accurately – and to apply the data to everything the farmer does.
Agriculture 4.0 plays a determining role concerning sustainability, by allowing agricultural practices to adapt to climate change, reduce greenhouse gas emissions, and use inputs more efficiently while preserving biodiversity and coping with water stress.
You may be interested in:
How precision agriculture helps feed our growing world
How Precision Farming Tools Can Help Agriculture Become More Resilient
Agmatix innovative solutions
Agmatix has launched a revolutionary crop nutrition management platform that drives the agronomic innovation cycle from research and experimental data into meaningful real-life actions.
The Agmatix Digital Crop Advisor is a data-driven ag solution that uses, standardizes, and transforms available information from existing databases and data silos combined with live inputs from growers into actionable, verified scientific-based insights and recommendations needed to optimize day-to-day crop management.
By using precision agriculture big data analytics, our advanced algorithms generate on-demand automated nutrition plans by considering multiple parameters including, among others, crop type, field location, pH, previous crops, plant uptake, and laboratory analyses.
This technology can provide timely warnings that alert the farmer to make changes to the schedule in the case of sudden winds or rain.
Another important feature of our Digital Crop Advisor is the customer/field agent interface which allows the field agent agronomist to view all the farmer’s properties and operations as part of the customer card.
This generates operational visibility and the ability to review all the recommendations created by field agents, including regional trends, and insights from the field.
Impact on sustainability
Synchronizing these data sources optimizes fertilizer application, and so reduces the risk of groundwater and greenhouse gas (GHG) pollution.
The platform can calculate a nutritional plan for a specific field, and it can estimate the carbon footprint and its immediate impact based on field parameters, environmental conditions, agronomic practices, crop type, fertilizer type, and timing of application.
All these actions can be employed to reduce the many sources of greenhouse gas emissions from agriculture.
Enhancing yields, decreasing waste, and improving food security
Using the Agmatix Crop Advisor, in turn, leads to an improvement of the growers’ productivity, more accurate and scientific management of data inputs by agronomists, and a significant advance in crop management.
Our system provides the vital information that’s required to make better crop management decisions, resulting in better yields, decreasing food waste, less environmental pollution, and ultimately improving food security.
