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

Published online by Cambridge University Press:  31 July 2018

Chitnucha Buddhaboon ,
Attachai Jintrawet  and
Gerrit Hoogenboom
Chitnucha Buddhaboon
Affiliation:
Rice Department, Bureau of Rice Research and Development, Ubonratchathani Rice Research Centre, Mueang district, Ubonratchathani 34000, Thailand
Attachai Jintrawet*
Affiliation:
Plant and Soil Sciences Department, Centre for Agricultural Resource System Research, Faculty of Agriculture, Chiang Mai University50200, Thailand
Gerrit Hoogenboom
Affiliation:
Department of Agricultural and Biological Engineering, Institute for Sustainable Food Systems, Gainesville, FL 32611, USA
*
Author for correspondence: Attachai Jintrawet, E-mail: attachai.j@cmu.ac.th
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Abstract

Prior to applying the cropping system model-CERES-Rice model to deep water rice (DWR), it is important to estimate the rice genetic coefficients (GC). The goal of the current study was to compare two methods for estimating GC using a GC calculator (GENCALC) and generalized likelihood uncertainty estimation (GLUE) for three flooded rice (FDR) varieties. Data from a field experiment on the effect of planting date and variety on FDR production was conducted in 2009 on a DWR area in Bang Taen His Majesty's Private Development Project, Prachin Buri, Thailand. The experimental design was split-plot with four main plots (planting dates) and three sub-plots (FDR varieties) with four replications. The simulated values for anthesis date, maturity date and grain weight using GENCALC produced normalized root mean square errors (RMSEn) of 3.97, 3.69 and 3.68, while using GLUE produced RMSEn of 3.67, 2.50 and 3.68, respectively. The simulated grain number and grain yield under GENCALC GC were not significantly different from the observed values but were higher than simulated values for GLUE GC. Simulated values of above-ground biomass for both GENCALC (11 727 kg/ha) and GLUE GC (11 544 kg/ha) were overestimated compared to observed values (8512 kg/ha). In addition, good agreements of leaf N values were found with D-index values of 0.94 and 0.96 using GENACALC and GLUE GC simulations, respectively. Therefore, the GENCALC and GLUE GC estimators of DSSAT can both be used for estimating GC of FDR in the DWR area in Thailand and similar agro-ecosystems in Southeast Asia.

Keywords

Anthesis datematurity daterice grain yieldrice top weight
Type
Crops and Soils Research Paper
Information
The Journal of Agricultural Science , Volume 156 , Issue 4 , May 2018 , pp. 482 - 492
Copyright
Copyright © Cambridge University Press 2018 

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