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Simulation de la croissance des cultures×Observation phénologique×
DomaineAgronomieAgronomie
FamilleProcess / pipelineProcess / pipeline
Année d'origine20031974
Auteur d'origineJohn W. Jones, Gerrit Hoogenboom et al.Zadoks, Chang, Konzak (cereals); Fehr, Caviness (soybean)
TypeComputational pipelineObservational and classification pipeline
Source fondatriceJones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Basso, B., Hunt, L. A., ... & Winter, S. R. (2003). The DSSAT cropping system model. European journal of agronomy, 18(3-4), 235-265. DOI ↗Zadoks, J. C., Chang, T. T., & Konzak, C. F. (1974). A decimal code for the growth stages of cereals. Weed research, 14(6), 415-421. DOI ↗
AliasCrop phenological model, Growth stage simulationGrowth stage assessment, Phenological monitoring, Crop stage scale
Apparentées55
RésuméCrop Growth Simulation is a computational pipeline for predicting daily or seasonal crop development, biomass accumulation, and yield under varying environmental conditions. Developed by Jones and colleagues in the DSSAT framework, this method integrates agronomic knowledge with process-based modeling to enable decision support in field management.Phenological Observation is an observational and classification pipeline for systematically recording crop development stages from germination to maturity. Standardized through crop-specific scales (Zadoks for cereals, Fehr for soybean), this method enables precise communication of crop status, timing of management decisions (fungicide application, irrigation), and prediction of harvest readiness.
ScholarGateJeu de données
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  2. 2 Sources
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  1. v1
  2. 2 Sources
  3. PUBLISHED

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ScholarGateComparer des méthodes: Crop Growth Simulation · Phenological Observation. Consulté le 2026-06-18 sur https://scholargate.app/fr/compare