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A first step towards a real-time predictive yield support system.

Publication Date
  • Crop Model
  • Real-Time
  • Yield Prediction
  • Engineering
  • Computing & Technology :: Computer Science [C05]
  • Ingénierie
  • Informatique & Technologie :: Sciences Informatiques [C05]
  • Life Sciences :: Agriculture & Agronomy [F01]
  • Sciences Du Vivant :: Agriculture & Agronomie [F01]
  • Agricultural Science
  • Medicine


Real-time non-invasive determination of crop biomass and yield prediction are maybe among the major challenges in agriculture. But unknown future weather remains the key point of accurate yield forecast. This paper presents the results of a preliminary study that aims to supply the unknown future by daily mean climatic data. The results show that, under the Belgian weather, this approach is relevant. Furthermore, the developed methodology appears to be a powerful diagnosis tool of the remaining yield potential under ongoing weather.

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