Abstract
ABSTRACT Genotype-by-environment interaction (GEI) is encountered in multi-environment trials. In sugarcane (Saccharum spp.), GEI affects crop growth and cane yield and complicates the selection of superior genotypes. The objective of this study was to assess and analyze GEI for cane yield and stalk weight to identify high-yielding, stable genotypes. Thirteen Canal Point (CP) sugarcane clones and three check varieties were evaluated at five different locations (environments) across three crop cycles (plant cane, first ratoon, and second ratoon) on the Florida organic (muck) soils. At each location, the experiment was conducted as a randomized complete block design with six replications. Mean stalk weight and cane yield data were collected and analyzed via the additive main effects and multiplicative interaction (AMMI) and genotype main effect (G) plus genotype × environment interaction (GEI), i.e. GGE biplot. The AMMI analysis for mean stalk weight and cane yield revealed that variation attributable to genotypes, environments, and GEI for these traits was significant. The GGE biplot analysis indicated that the five locations formed two mega-environments, with different winning genotypes. Two locations, Okeelanta and Duda, were non-representative of the Florida muck-soils. Among all the genotypes, CP 12–1417 had the highest mean cane yield and had the most stable performance across crop cycles. We concluded that the application of GGE biplot in our final-stage sugarcane testing program could help us identify clones best adapted to specific locations and enhance selection efficiency by helping us identify locations that provide similar information.
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