Crop model determined mega-environments for cassava yield trials on paddy fields following rice

Nateetip Sawatraksa; Poramate Banterng; Sanun Jogloy; Nimitr Vorasoot; Gerrit Hoogenboom

doi:10.1016/j.heliyon.2023.e14201

Crop model determined mega-environments for cassava yield trials on paddy fields following rice

Heliyon. 2023 Feb 28;9(3):e14201. doi: 10.1016/j.heliyon.2023.e14201. eCollection 2023 Mar.

Authors

Nateetip Sawatraksa^{1

2}, Poramate Banterng^{1

3}, Sanun Jogloy^{1

3}, Nimitr Vorasoot¹, Gerrit Hoogenboom^{4

5}

Affiliations

¹ Department of Agronomy, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand.
² Faculty of Science and Agricultural Technology, Rajamangala University of Technology Lanna Lampang, Lampang, 52000, Thailand.
³ Plant Breeding Research Center for Sustainable Agriculture, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand.
⁴ Institute for Sustainable Food Systems, University of Florida, 32611, USA.
⁵ Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, 32611, USA.

Abstract

The Cropping System Model (CSM)-MANIHOT-Cassava provides the opportunity to determine target environments for cassava (Manihot esculenta Crantz) yield trials by simulating growth and yield data for various environments. The aim of this research was to investigate whether cassava production on paddy fields in Northeast, Thailand could be grouped into mega-environments using the model. Simulations for four different cassava genotypes grown on paddy field following rice harvest was conducted for various soil types and the weather data from 1988 to 2017. The genotype main effect plus genotype by environment interaction (GGE biplot) technique was used to group the mega-environments. The analyses of yearly data showed inconsistent results across years for environment grouping and for the winning genotypes of the individual environment group. An analysis using GGE biplot with the average value of the simulated storage root dry weight (SDW) for 30 years indicated that all 41 environments were grouped into two different mega-environments. This study demonstrated the ability of the CSM-MANIHOT-Cassava to help identify the mega-environments for cassava yield trials on paddy field during off-season of rice that could help reduce both time and resources.

Keywords: Cropping system model; GGE biplot; Mega-environments; Multi-environment trials.