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Book Sections Year : 2021

AI-Driven Yield Estimation Using an Autonomous Robot for Data Acquisition

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1
Lucas Mohimont
Mathias Roesler
Nathalie Gaveau
Marine Rondeau
François Alin
Clément Pierlot
  • Function : Author
Rachel Ouvinha de Oliveira
  • Function : Author
Marcello Coppola
  • Function : Author

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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Dates and versions

hal-03355284 , version 1 (27-09-2021)

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Attribution - NonCommercial - NoDerivatives - CC BY 4.0

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  • HAL Id : hal-03355284 , version 1

Cite

Lucas Mohimont, Luiz Angelo Steffenel, Mathias Roesler, Nathalie Gaveau, Marine Rondeau, et al.. AI-Driven Yield Estimation Using an Autonomous Robot for Data Acquisition. Artificial Intelligence for Digitising Industry Applications, River Publishers, pp.279-288, 2021, 9788770226646. ⟨hal-03355284⟩

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