Daniel Jacob (INRAE BFP 2022)
Contents
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R scripts for growth modeling on 9 fruit species as part of the ANR FRIMOUSS project (see below). 2 models based on sigmoids (single and double) were chosen. Optimization of model parameters uses the R package minpack.lm which implements the Levenberg-Marquart nonlinear least-squares algorithm.
- odam.R : retrieves data directly in the FRIMOUSS data collection from an ODAM server using the API (see R package Rodam)
- fitmodels.R : general routines for model fitting
- growth.R : routines to interface growth modeling with FRIMOUSS collection data
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2 Jupyter notebooks implementing growth modeling
- Growth_model_nb1.ipynb : comparison of the growth modeling based on both models for one species
- Growth_model_nb2.ipynb : comparison of the growth modeling based on the second model for all species
Frimouss project: FRuit Integrative MOdelling for a Unified Selection System
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ANR Project ID: ANR-15-CE20-0009
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Publication : Léa Roch, Sylvain Prigent, Holger Klose, Coffi-Belmys Cakpo, Bertrand Beauvoit, et al.. Biomass composition explains fruit relative growth rate and discriminates climacteric from non-climacteric species. Journal of Experimental Botany, Oxford University Press (OUP), 2020, 71 (19), pp.5823-5836. doi:10.1093/jxb/eraa302
Frimouss dataset interfaced by ODAM
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All the data concerning each fruit species have been organized and managed in the same way using the ODAM approach and the associated tools.
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ODAM Dataexplorer : https://pmb-bordeaux.fr/dataexplorer/?dc=Frimouss
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ODAM online documentation: https://inrae.github.io/ODAM/