AI-Driven Yield Estimation Using an Autonomous Robot for Data Acquisition
Abstract
The quality of the harvest depends significantly on the quality of the grapes. Therefore, winemakers need to make the right decisions to obtain highquality grapes. One of the first problems is estimating the yield of the crops. It allows winemakers to respect the specific norms of their appellation (yield quota, alcohol levels, etc.). It is also necessary to organise the logistics of the harvest (start date, human resources required, transportations, etc.). Traditionally, the yield estimation is performed by collecting grapes and berries over small, randomised samples, a destructive and laborious task. This work explores how automatic data acquisition combined with artificial intelligence can drive an automated and non-destructive yield estimation, adapted to the characteristics of each vine parcel.
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