Editor’s Note: Koji Hasegawa is general manager at Kubota Innovation Center Silicon Valley, where he is responsible for new agricultural business planning and execution with open innovation and investing in US agtech startups.
The views expressed in this guest article are the author’s own and do not necessarily represent those of AFN.
You have probably seen videos of rice and wheat being speedily harvested with a combine harvester. Yet specialty crops such as strawberries are still picked by hand at a time when growers are facing rising labor costs and labor shortages. So why isn’t mechanization being utilized by more growers of specialty crops?
In part, it relates to these crops’ variability and fragility. In fields of rice and wheat, for example, there is no big difference in the speed of growth for each individual plant, while the crops also grow to the same height. Consequently, harvesting is not very complicated, and can be mechanized easily.
In the case of specialty crops, on the other hand, fruits are scattered irregularly, while their ripeness varies widely. Many kinds of fruits are also easily damaged during harvesting. Therefore, people need to visually judge fruits one by one and pick them gently to avoid damaging them.
Similar challenges apply to pruning and weeding. The branches to be cut and the weeds to be removed need to be identified precisely.
Up to now, these tasks have been difficult to mechanize because there was no established technology capable of substituting for the human eye, brain, and hand.
Camera-based imaging technology, AI, robotics
However, there have been recent advances in technology, mechanization and automation. The human eye is being replaced by camera-based imaging technology, the brain by AI, and the hands by robotics.
Recently, several startups have combined these technologies to find solutions to these challenges, such as Advanced Farm Technologies and Tortuga AgTech in the field of strawberry harvesting, and FarmWise and Carbon Robotics for weeding. They are already offering their services on a commercial basis and many growers are adopting their groundbreaking solutions.
Two key factors that will drive adoption
In the coming years, the widespread penetration of such mechanization and automation solutions is likely to depend on two key factors.
The first one, of course, is economics. No matter how many people can be replaced, if the cost of using robots is higher, farm operators will not accept the solution. Unless the cost of the robot solution is equal to or less than the human solution, they will not embrace it.
This explains why, in addition to improving work precision, speed and efficiency, these startups are also focused on improving COGS (Cost of Goods Sold) and OPEX (Operating Expenses), to achieve better total cost competitiveness.
Added value from robotics
The second factor is achieving and delivering added value that is unique to robots, i.e., value that cannot be generated with human labor. Returning to the example of harvesting, a robot can make use of GNSS (Global Navigation Satellite System) and harvest data to record the quantity of the harvest in small parts of a field.
At best, humans are only capable of making rough estimates of large fields; they cannot determine this information with such granularity. The data acquired by a robot can be used to compare yield and crop quality of each area of the field.
Furthermore, if the cause-and-effect relationships between inputs and outputs can be clarified by combining them with input data from the other farming process, it could be possible to improve the yield and quality of crops in the following year.
If this became a reality, robots would not merely replace labor; they would become an indispensable element of solutions for achieving more precise and efficient agricultural production. As such, they would be highly valued by growers.
In addition, as the shift to ‘smart agriculture’ advances, data collection and utilization at every step of the farming process will become more sophisticated, and as a result, we can expect to see the emergence of platforms for managing this data centrally. Such platforms will be key factors in accelerating the spread of robot-mechanization and automation solutions.
On the other hand, major challenges for startup companies who provide robotics and automation solutions are the time required to scale up and to secure working capital during the scale-up period.
As there are so many factors involved in agriculture which is typically done outdoors, a non- controlled environment, growers would like to see multiple results for verifying ROI of newly introduced solutions. However, since agriculture has seasons, the cycle is naturally long, resulting in multiple years of ROI verification.
Also, farmers tend to be risk averse, testing new solutions in limited spaces at first before introducing them to a larger field area.
Many robotics startups have not yet demonstrated sufficient reliability to sell their products, so they adopt a RaaS (Robot as a Service) or leasing model, in which they provide services while having robots as their own assets. Therefore, even if they are ready to scale, it’s not easy for startups with limited capital to own a large number of robots.
Therefore, I believe that continuous robust support by investors and strategic partners like us, with a full understanding of the time required to scale up for agtech startup companies, is also an essential requirement for the spread of robotics and automation in agriculture.