@article { author = {Klomsa-ard, P. and Patanothai, A. and Jaisil, P.}, title = {Efficient test sites for multi-environment evaluation of sugarcane genotypes in Thailand}, journal = {International Journal of Plant Production}, volume = {7}, number = {4}, pages = {763-790}, year = {2013}, publisher = {Gorgan University of Agricultural Sciences}, issn = {1735-6814}, eissn = {1735-8043}, doi = {10.22069/ijpp.2013.1268}, abstract = {Multi-environment trials (METs) of crop genotypes are costly and require efficient test sites for cost effectiveness. This study aimed to identify efficient test sites for METs of sugarcane (Saccharum spp.) genotypes in Thailand, utilizing data from 10 sugarcane genotypes conducted at nine locations covering different sugarcane growing regions of the country for two crop-classes. Cluster analysis and the genotype plus genotype × environment (GGE) biplot method were used to group these sites into five subsets, based on their similarity in genotypic responses of cane and sugar yields of the planted crop and the first ratoon crop. The results showed a fair agreement between the two methods, but inconsistent results were obtained from groupings that were based on different yield traits and crop-classes. Locations appearing more consistent in certain groups were chosen as the representatives of the respective groups to constitute the set of efficient test sites. Cluster analysis and the GGE biplot, however, identified different sets of test sites that were equally effective in retaining the G×L interaction and the performance ranking of the test genotypes as the original nine test sites. The selected locations by cluster analysis which included Nakhon Ratchasima, Ratchaburi, Kamphaeng Phet, Tha Phra, Khon Kaen and Udon Thani are preferred because of their wider geographical distribution. Four sites could thus be omitted, which would substantially reduce the costs and time and greatly improve the efficiency of the METs of sugarcane genotypes in Thailand. Keywords: Multi-environment trials (METs); Environment grouping; GGE biplot; Cluster analysis; Breeding line evaluation.}, keywords = {}, url = {https://ijpp.gau.ac.ir/article_1268.html}, eprint = {https://ijpp.gau.ac.ir/article_1268_398c15bc473cb1801389930ee753b3c3.pdf} }