Technology to Meet Agriculture’s Greatest Challenges

At the first-ever FIRA USA summit in Fresno, California, professionals from across the agricultural industry gathered to share their knowledge, ask questions and learn about technological solutions that help streamline farming’s toughest tasks. The event also included a number of panels that sought to dive deeper into a wide range of educational topics.

In the “Mechanization v Automation ("dumb" tech v "smart" tech)–Why it Matters,” five expert panelists explain the technology progression in agriculture and the strategies necessary to meet the industry’s greatest challenges. Moderator Jeff Morrison (Grimmway Farms) spoke with Praveen Penmetsa (Monarch Tractor), Ben Smith (Kubota), Gary Thompson (GUSS), Dennis Utt (Crown Harvesting) and Martha Zwontizer (Grimmway Farms). The following abstract is written based on Morrison’s notes after the discussion.

The basis of the panel was to delve into the differences between mechanization (aka “dumb” technology) and automation (aka “smart” technology) and why each matters in the race to help farmers grow enough food to feed a continually increasing population. Several themes developed throughout the conversation.

The first was with respect to the progression sequence that exists within agtech innovation. This is a process that has been in progress for tens of thousands of years. The contention is that, once the innovation sequence begins and technology is created, future milestones are as follows: Mechanization, then Automation and finally Intelligence. Presently, state-of-the-art computer technology supports the automation and intelligence milestones. Much capital is available to invest in these efforts and failure is common.

The second theme was that the current agtech efforts are highly biased towards the Automation and Intelligence milestones. These efforts frequently fail and stand-out breakthroughs are not common.A breakthrough is exemplified by the general system characteristics being widely adopted across the industry with minor variations. These efforts were termed Automation and Intelligence for the sake of the panel discussion. In certain instances, a well-orchestrated Mechanization effort may offer improved capital returns and wider industry adoption.Herein lies the mechanization v automation debate.

Understanding the depth of this discussion is understanding the terms. As an example, certain rudimentary agricultural hand labor tasks were mechanized during the 19thand 20th centuries due to impacts of the industrialization. These early mechanization efforts represent the first step along the progression. These same legacy systems, and various new systems are now progressing to the next logical step with the ultimate objective of becoming fully autonomous Intelligent systems. As such, the question must be asked: how fast can fully autonomous intelligent systems be achieved with available technology, and will the marketplace support the resulting capital requirements? Is an intermediate objective warranted?

Another theme focused on adoption of these technologies. ROI drives entry points. All systems must realize an improvement in cost structure for the adopting entity/market. Similarly, market variability is characterized by differing cost structures. The cost of production of commodity “X” in one part of the world may be such that available technological systems are easily adopted. Other regions of production may have differing cost structure that makes the capital requirements prohibitive.

Finally, the panelists discussed the importance of trust and the ability of solutions to adapt to various production ecosystems. Industry uptake of systems can be greatly influenced by setting reasonable expectations for the target industry and user, and by not forcing wide adaptations to be implemented to achieve system viability.