A reliable harvest forecast starts with reliable farm records.
AI harvest forecasting only works when it has accurate, structured data to learn from. Farmable is built to capture exactly that data, pest observations, spray records, growth stage notes, and harvest history, so that when the forecast arrives, it's grounded in your farm's real story.
Most harvest forecasts are guesses. AI can change that, but only with the right data.
Harvest forecasting has always been difficult for fruit and vegetable growers. Traditional methods, manual counts, experienced estimates, area sampling, carry 30-50% error rates. AI-powered models can improve this dramatically, but they require structured historical data: pest pressure records, spray timing, weather correlation, growth stage observations, and multi-season harvest history. Without that foundation, even the best AI model is guessing.
Every record you keep today is training data for tomorrow's forecast.
Farmable captures four categories of data that AI harvest forecast models depend on. You're not doing extra work, you're doing the same farm management work you'd do anyway, digitally.
Pest & disease observations
Scouting notes tied to GPS locations and BBCH growth stages. The earlier you catch a pressure event, the better the forecast can account for its impact on yield.
See IPM →Spray & treatment records
Every product application, timing, and rate, connected to the field and growth stage. Spray timing relative to flowering and fruit set is one of the strongest predictors of yield outcome.
See spray records →Harvest records
Yield by field, variety, and quality grade, multi-season. Historical harvest data is the model's ground truth. The longer your record, the more accurate your forecast.
See harvest tracking →Soil sample data
Lab results for each field, linked to the block they came from. Soil chemistry and nutrition history give the model the agronomic baseline it needs to forecast yield accurately.
See fertilization plan →A fifth input is on its way: yield estimates from soil sampling and your fertilizer plan will feed directly into the model in 2027. See soil sampling & fertilization →
Your soil samples easily converted to nutrition insights
Upload lab results once and Farmable links every sample to the field it came from. Sample chemistry, planned yield and applied nutrition sit together per block, ready to feed the 2027 AI harvest forecast.
We're not asking you to predict your harvest. We're building a model that does it for you.
Most harvest forecast tools ask growers to input their own estimates and then refine them. We think that's backwards. Farmable's approach is to derive the forecast from your operational data, not to ask you to provide one. That means the accuracy improves as your records improve, and the grower gets a forecast that reflects reality rather than optimism.
Data-driven, not estimate-driven
The forecast is calculated from pest records, spray timing, growth stage notes, and historical harvest data. You don't manually enter a number.
Gets smarter every season
Each harvest season adds to the model's understanding of how your specific farm performs. Year three is more accurate than year one.
Launches 2027
We're building this feature for release in 2027. Growers who start capturing data now will have the richest model when it launches.
Want to be notified when harvest forecasting launches?
Harvest forecast tools that require hardware or manual input have a fundamental problem.
Some harvest forecast solutions require expensive additional hardware, cameras, sensors, or drone imaging, to generate their predictions. Others ask growers to manually count or estimate, which defeats the purpose. Farmable's forecast will be derived entirely from data you're already capturing in your daily farm management workflow, no extra hardware, no double entry, no guesswork inputs.
The forecast will be as strong as the records behind it.
These growers are already capturing the harvest, spray and scouting data that the 2027 forecast model will learn from.
The farmers who will benefit most from AI harvest forecasting are the ones building records today.
"Keeping good records every season is what's let us actually see what works on each block. It's the boring part that pays off."
Darryl Simpson
Simpson's Wines, Australia
"An essential tool for understanding the profitability of our farm down to the field level."
Pål Audun Høyen
Apple and Berry Grower, Norway
"I save 2 ½ hours every time we do a spray job, and the records are in one place when we need them."
Rory Nunes
Manbulloo, Australia
Harvest forecast questions
Farmable's AI harvest forecast feature is scheduled for release in 2027. We're currently building and testing the models using anonymised farm data from our network. Sign up above to be notified at launch.