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Greenhouse tomato production is a significant part of the Canadian agricultural landscape, contributing substantially to both domestic sales and the export market. Despite the crop’s importance, accurately forecasting tomato yield remains a significant challenge for growers. This unpredictability, largely due to fluctuating climate conditions and the difficulty in assessing fruit development at early stages, can lead to inefficiencies, market instability and price volatility, impacting the entire supply chain.
Growers have traditionally relied on yield forecasting to optimize resource allocation, improve crop management and maximize sales and profitability. Now, an AI-driven solution, combined with crucial grower data, could revolutionize the way yield predictions take place.
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