Identifying Suitable Genotypes for Different Cassava Production Environments—A Modeling Approach

Agronomy

Phanupong Phoncharoen¹  Poramate Banterng¹  Nimitr Vorasoot¹  Sanun Jogloy¹  Piyada Theerakulpisut²  Gerrit Hoogenboom³ 

[1] Department of Agronomy, Faculty of Agriculture, Khon Kaen University, Khon Kaen 40002, Thailand;Department of Biology, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand;Institute for Sustainable Food Systems, University of Florida, Gainesville, FL 32611, USA;

关键词: evaluation;    DSSAT;    CSM–MANIHOT–Cassava;    planting dates;    yield;   

DOI  :  10.3390/agronomy11071372

来源: DOAJ

【 摘 要 】

Crop simulation models can be used to identify appropriate genotypes and growing environments for improving cassava yield. The aim of this study was to determine the best genotypes for different cassava production environments using the cropping system model (CSM)–MANIHOT–Cassava. Data from cassava experiments that were conducted from 2009–2011 and 2014–2015 at Khon Kaen, Thailand, were used to evaluate the model. Simulations were then conducted for different scenarios using four cassava genotypes (Kasetsart 50, Rayong 9, Rayong 11, and CMR38–125–77), twelve planting dates (at monthly intervals starting in January and ending in December), and ten locations in Thailand under fully irrigated and rainfed conditions using 30 years of historical weather data. Model evaluation with the experimental data for total biomass and storage root yield indicated that the model classified well for relative productivity among different planting dates. The model indicated that growing cassava under irrigated conditions generally produced higher biomass and storage root yield than under rainfed conditions. The cassava genotype CMR38–125–77 was identified for high biomass, while the genotype Rayong 9 was identified as a good genetic resource for high yield. The December planting date resulted in the highest biomass for all locations, while the February planting date produced the highest storage root yield for almost all locations. The results from this study suggest that the CSM–MANIHOT–Cassava model can assist in determining suitable genotypes for different cassava production environments for Thailand, and that this approach could be applicable to other cassava growing areas.

【 授权许可】

Unknown