Why is it Challenging for Agriculture to Adopt Tech Culture?
The digitization of agriculture, which includes precision farming and process automation, is predicted to have a significant impact on how farmers participate in the production process, regardless of farming techniques.
Fremont, CA: Agriculture technology has advanced dramatically in the previous decade, from smart irrigation systems that rely on sensor data to the use of visual technologies to enable plant-level decisions like precision weed spraying and seed distribution. Despite all of the technical advancements, there is still a lack of confidence among food growers who are not used to purchasing, deploying, and using these technologies on a daily basis.
Overcoming psychological barriers
Farmers are hesitant to adopt computer culture due to psychological hurdles. A lack of onboarding help or technical education is at the root of many psychological hurdles. Although the inventors of these technologies may understand how and when to utilize a piece of equipment or interpret data from a dashboard, end users may not.
Solutions That Add Value and Have a Clear Purpose
While the algorithms and nano-chips at the heart of the tech solutions may be extremely complex and sophisticated, growers are primarily interested in the end result and how these tools will help them run more efficiently, addressing issues such as labor, food safety, and water, among others. Knowing your audience is critical in any industry, and AgTech is no exception. It won't be easy to introduce new tools, procedures, and systems to food growers who have relied on tried-and-true methods for decades.
To Deliver Smart Solutions, Tech Creators Must Work Harder
As crucial as the sophisticated tools themselves will be their simplicity of use, onboarding processes, and training or support for new technology. While some tech firms are eager to tout their data processing power, cutting-edge machine learning algorithms, or billions of data points acquired by sensors, this is not what food producers require. Instead of statistics on how to enhance their work, people will appreciate concrete insights. Even if an engine processes
hundreds of aerial photographs, the insights derived from the raw data will become a critical instrument for growth.
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