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CRONOSOJA: a daily time-step hierarchical model predicting soybean development across maturity groups in the Southern Cone

https://doi.org/10.1101/2023.09.18.558336

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Outgoing claims: the papers this work cites, builds on, or argues with.

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An overview of APSIM, a model designed for farming systems simulation

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Towards the Reliable Prediction of Time to Flowering in Six Annual Crops. VI. Applications in Crop Improvement

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Simulation of growth and development of diverse legume species in APSIM

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Adaptation of soybean ( Glycine max (L.) Merrill) to the dry season of the tropics. I. Genotypic and environmental effects on phenology

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Rcpp : Seamless R and C++ Integration

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Fitting Linear Mixed-Effects Models Using lme4

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Stan : A Probabilistic Programming Language

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insight: A Unified Interface to Access Information from Model Objects in R

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Soybean Yields in Relation to Days Between Specific Developmental Stages1

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Modeling the Occurrence of Reproductive Stages after Flowering for Four Soybean Cultivars

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Soybean Seed Number and Crop Growth Rate during Flowering

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Potential of Early‐Maturing Soybean Cultivars in Late Plantings

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Parameter Estimation for Crop Models

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Genetic Coefficients in the CROPGRO–Soybean Model

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Evaluation of Eleven Thermal Unit Methods for Predicting Soybean Development1

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Effects of Daylength and Temperature on Soybean Development1

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Parameter Estimation for Predicting Flowering Date of Soybean Cultivars

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Comparison of Two Phenology Models for Predicting Flowering and Maturity Date of Soybean

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Photoperiod and Temperature Responses in Early‐Maturing, Near‐Isogenic Soybean Lines

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loo: Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian Models

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rsample: General Resampling Infrastructure

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R: A Language and Environment for Statistical Computing

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Advanced Bayesian Multilevel Modeling with the R Package brms

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CDO User Guide

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partR2 : partitioning R 2 in generalized linear mixed models

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