Options for calibrating CERES-maize genotype specific parameters under data-scarce environments

Towards improved calibration of crop models – Where are we now and where should we go?

(2018) S.J. Seidel et al.   EUROPEAN JOURNAL OF AGRONOMY

Estimating parametric phenotypes that determine anthesis date in Zea mays: Challenges in combining ecophysiological models with genetics

(2018) Abhishes Lamsal et al.   PLoS One

Methodology to estimate rice genetic coefficients for the CSM-CERES-Rice model using GENCALC and GLUE genetic coefficient estimators

(2018) Chitnucha Buddhaboon et al.   JOURNAL OF AGRICULTURAL SCIENCE

On the number of experiments required to calibrate a cultivar in a crop model: The case of CROPGRO-soybean

(2017) Cesar A. Fensterseifer et al.   FIELD CROPS RESEARCH

CERES–Maize Model for Determining the Optimum Planting Dates of Early Maturing Maize Varieties in Northern Nigeria

(2017) Adnan A. Adnan et al.   Frontiers in Plant Science

Using CERES-Maize and ENSO as Decision Support Tools to Evaluate Climate-Sensitive Farm Management Practices for Maize Production in the Northern Regions of Ghana

(2017) Dilys S. MacCarthy et al.   Frontiers in Plant Science

Using CERES-Maize model to determine the nitrogen fertilization requirements of early maturing maize in the Sudan Savanna of Nigeria

(2016) Adnan A. Adnan et al.   JOURNAL OF PLANT NUTRITION

Predicting Maize Phenology: Intercomparison of Functions for Developmental Response to Temperature

(2014) S. Kumudini et al.   AGRONOMY JOURNAL

A calibration procedure to improve global rice yield simulations with EPIC

(2013) Wei Xiong et al.   ECOLOGICAL MODELLING

Implication of crop model calibration strategies for assessing regional impacts of climate change in Europe

(2012) Carlos Angulo et al.   AGRICULTURAL AND FOREST METEOROLOGY

Influence of likelihood function choice for estimating crop model parameters using the generalized likelihood uncertainty estimation method

(2010) Jianqiang He et al.   AGRICULTURAL SYSTEMS

Using pattern recognition for estimating cultivar coefficients of a crop simulation model

(2009) Mohammad Bannayan et al.   FIELD CROPS RESEARCH

Methodology for the use of DSSAT models for precision agriculture decision support

(2008) Kelly R. Thorp et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

A sequential approach for determining the cultivar coefficients of peanut lines using end-of-season data of crop performance trials

(2008) J. Anothai et al.   FIELD CROPS RESEARCH

Reduction in data collection for determination of cultivar coefficients for breeding applications

(2007) J. Anothai et al.   AGRICULTURAL SYSTEMS