U.S.: Mechanization Making Way to a Cherry Orchard Near You

In tree fruits, precision orchard management and mechanization are natural associations, writes Gregory Lang at Growing Produce. Precision orchard management is about quantification to make optimal decisions, such as: How many leaves are needed to grow a sweet cherry of the targeted quality (e.g., 9 Row size, or 30 mm diameter, or 12 grams)? How many flower buds or flowers are needed to achieve a desired yield (e.g., 8 tons/acre) of fruit of the targeted quality?

Of course, these illustrations can be refined to sharpen the targets with the input of more data — not just how many leaves are needed but also how many sun-exposed leaves are needed? How does the typical number of daily hours of sunlight in a Michigan orchard vary from the typical number of daily hours of sunlight in an orchard in eastern Washington? And does this differential alter the target leaf number in an inversely proportional way to produce comparable fruit?

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Next, when the factors for making orchard decisions have been identified and quantified so decisions are based on numbers rather than intuition, this simplification is a key step toward introducing or improving mechanization for specific tasks. What are the machines, or sensors, that can potentially help gather the quantified data, such as measuring sun-exposed leaves or estimating numbers of flower buds or flowers? What are the machines that can be used for carrying out orchard tasks to implement the data-driven decisions for optimizing fruit quality or yield outcomes?

The most valuable, incomparable machine in the orchard today is the human — a biological machine with incredible visual sensory perception, an amazingly fast and complex processor of highspeed sensory inputs in the context of anticipated outcomes, and a marvelously adaptable force/motion activator with motor skills and dexterities that range from brute force to subtle and precise micro-adjustments. And increasingly important, the ability to utilize other mechanized machines to improve the efficiency of the human machine.

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