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2019
Journal article
A framework for predicting soft-fruit yields and phenology using embedded, networked microsensors, coupled weather models and machine-learning techniques
Improving the accuracy of harvest timing predictions offers an opportunity to sustainably improve soft fruit farming. Fruits are perishable, high-value and seasonal, and prices are typically time-sensitive. Harvesting is labour-intensive and increasingly expensive making accurate phenological predictions valuable for growers. We have developed and tested a novel framework for linking...Lee, Mark A. ; Monteiro, Angelo ; Barclay, Andrew ; Marcar, Jon ; Miteva-Neagu, Mirena …
fruiting, sensors, climate, picking, strawberries, and machine learning