The second day of the annual Washington Tree Fruit Association meeting opened with a strong focus on innovation and economic awareness. Taking center stage were cherries and their future, explored through production strategies, harvesting choices, and emerging technologies.
Norm Gutzwiler: “Don’t pick fruit that doesn’t cover the costs”
Kicking off the cherry session was grower Norm Gutzwiler, who delivered a blunt message to fellow producers: harvesting fruit that does not cover picking and packing costs is a losing decision.
Too many growers, he stressed, underestimate the true cost of harvest, overlooking key expenses such as support staff wages, fuel, portable toilets, and other ancillary costs.
“Eleven-row cherries don’t cover picking costs,” he said, “and they don’t generate any margin for pruning or taxes.”
The solution? Focus on larger fruit sizes through more targeted orchard management, aggressive pruning, and smart use of gibberellic acid (GA). “If you have to cut back to 6 or 7 tons per acre (about 15–17 tons per hectare) to regenerate young wood, so be it. We have too many trees in the ground,” he added.

Welcome Sauer: better data is needed to make decisions
Next, former industry executive Welcome Sauer delved into the economic analysis of the 2025 season, highlighting how difficult it is for growers to decide whether to harvest without access to up-to-date market data.
“We can’t follow Norm’s advice without more precise information,” Sauer said. The 2025 season is a clear example: initially promising FOB (Free On Board) prices were later revised downward as the market evolved.
Still, he argued that the cherry market is more predictable than many believe: “The correlation between supply and price is strong. We can and must plan better with retailers, especially during periods of limited supply and high prices, to manage the later stages of the season.”
Mechanical harvesting: 20 years of research pave the way for change
Matt Whiting, cherry physiologist at Washington State University, presented results from more than twenty years of research on mechanical harvesting. The “shake-and-catch” system has shown high efficiency without significantly increasing fruit defects.
Moreover, consumers appear to respond positively to stemless cherries, one of the outcomes of mechanical harvesting.
There is, however, a remaining obstacle: “We need commercial champions willing to adopt and carry this technology forward,” Whiting emphasized.
AI in the orchard: from ChatGPT to price forecasting
The technology session also drew significant attention, featuring live demonstrations of artificial intelligence applications in agriculture. Gwen Hoheisel, a WSU Extension specialist, showed how she trained ChatGPT to create an operational checklist for a new Quantum Mist sprayer, starting from a 54-page technical manual.
The key to success? A detailed prompt defining role, objective, context, and supporting sources. The result was a structured list organized by daily, weekly, and seasonal tasks, also aligned with 200- and 500-hour maintenance intervals.
Matt Yeager, founder of the startup Kragworks, instead used the AI model Claude together with his father Joel to estimate FOB prices based on real data collected on their farm in the Yakima Valley.
The model refined its forecasts step by step, searching for updated tables and justifying each calculation.
Both experts, however, issued a clear warning: “Artificial intelligence is a powerful tool, but human oversight is always required. Be the human link in the process,” Yeager concluded.
Looking ahead
The day concluded with insights into irrigation automation, heat stress management, and task maps for crop load control.
Final updates covered the Smart Orchard projects and the technology roadmap of the Washington Tree Fruit Research Commission.
A common thread ran through all presentations: for the cherry sector to thrive, a holistic vision is needed, combining agronomic expertise, economic analysis, and openness to technological innovation.
Source: goodfruit.com
Image source: Stefano Lugli
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