Jan 22, 2018
By Sierra Clark
Running a profitable farm is hard. Among many reasons, running a farm is difficult because variables are constantly changing. Soil moisture levels, nutrient and fertilizer needs, weather patterns, and the threat of pests are among a few of the variables that often fluctuate. This is why farming is really a numbers game. A successful farm is able to collect large amounts of data, determine what data is actually relevant, and then turn this data into insights and predictive modeling. This is what helps farmers know the current condition of crops and the best next steps.
Traditional methods of data collection, including pen, paper, and spreadsheets, can be time consuming and an undesirable part of running a farm. This is where data analytics changes the game. With the use of hardware and software, data analytics is able to intake hundreds of data points and provide farmers actionable advice that can improve their business. By using data analytics, farmers can decrease waste and increase yield, ultimately creating a more smart, efficient, and profitable farm.
Data Analytics Took Root in the 2000s
As technology has advanced, it has become easier to run a profitable farm. Since the 1960s agriculture has seen immense technological change. The Green Revolution, and the introduction of RoundUp and genetically modified crops gave the industry a taste of the power of technology by dramatically increasing yield percentages.
In the 2000s the introduction of software, hardware, and cloud based technology led the way for precision agriculture. For example, in 2001 John Deere added global positioning systems (GPS) to each of its tractors, allowing farmers to track what land was treated. This led to more effective fertilizer dosing and a decrease in accidental repeat treatments.
John Deere and NASA technology allows farmers to digitally track multiple variables over time on their fields.
This technology jump led the way for an entire wealth of tools designed to help farmers plan for better harvests. Satellites and GPS data provide yield mapping and precise seed planting, while sensors detect soil moisture levels, nutrient content, nitrogen needs, and even yield. A modern farm today produces a whole lot of data. However, the data alone is not what will produce a profitable farm.
Data Analytics is Key to Profitability
At its simplest, data analytics is about collecting information and then knowing what to do with it. There are two sides that make this possible: hardware and software. Hardware is the physical pieces that intake data. This includes sensors, drones, satellites, and any other tools that detect and monitor important variables.
Software is the programs that store the data and connects to a computer or the cloud. It is software that crunches the data and gives farmers a read out of what is happening on the farm, and ultimately what to do.
The combination of hardware and software give life to different data analytics tools including farm management software, precision agriculture techniques, predictive data analysis, and smart irrigation. These categories all have the goal of helping farmers make smarter decisions. Because of data analytics tools, farms waste less and produce more. Due to financial, social, and political pressures to conserve resources and improve yields, the need for data analytics is greater than ever.
The question becomes not if a farm should use data analytic products, but which ones.
Illumitex grow lights in a vertical farm. The company is developing high-resolution imaging technology that will integrate with sensors and their lights to give a fuller picture of the growing environment.
There Are More Options Than Ever
Luckily, there are many tools that allow farmers to harness the power of data analytics. Both indoor and traditional agriculture have a huge range of data analytic products to choose from. Here are some companies that are moving the industry forward and providing the edge:
For Indoor Agriculture
Agrilyst: provides farm management software.
Autogrow: provides intelligent dosing, irrigation, and climate control systems.
Lumigrow: provides smart grow light solutions comprised of LED hardware and cloud-based software.
Priva: provides a whole host of both hardware and software products that optimize environment conditions and support process management.
Illumitex: provides digital horticulture solutions with a focus on smart grow lights.
Other notable data driven companies include AEssenseGrows, Agrinamics, Argus Controls, and turnkey farms such as Urban Crop Solutions.
It is important to note that there are indoor farms that design, manufacture and patent their own data driven technology which may or may not be available to the market in the future.
For Outdoor Agriculture
Agrible: provides field-specific yield projections, soil workability, nutrient availability, pest pressures, and record keeping.
aWhere: provides high resolution weather and scientifically vetted agronomic data through mobile devices.
Farmers Edge: provides VTR, field-centric data management and analysis.
Other notable big data and analytic companies include Agerpoint, Adapt-N, Descartes Labs, MavrX, OnFarm, Orbital Insight, Precision Hawk, and Resson.
Although these companies are focused on outdoor agriculture, it is within reason to expect that as the indoor agriculture industry grows, some of these companies may begin to build products that cross into the indoor agriculture space as well.
To sum this all up: Data analytics provides endless ways to help farmers grow their most profitable farms. By using the power of numbers farms can decrease waste, and increase yield and profit margins. This technology is good for the farmer, the consumer, and the environment. Ultimately, the more universally data analytics is adopted and utilized the faster the industry can grow.