Assessment of sugar beet root yield by AMMI analysis
2017
Ćirić, Mihajlo (Institute of Field and Vegetable Crops, Novi Sad (Serbia)) | Ćurčić, Živko (Institute of Field and Vegetable Crops, Novi Sad (Serbia)) | Mirosavljević, Milan (Institute of Field and Vegetable Crops, Novi Sad (Serbia)) | Marjanović-Jeromela, Ana (Institute of Field and Vegetable Crops, Novi Sad (Serbia)) | Jaćimović, Goran (Faculty of Agriculture, Novi Sad (Serbia)) | Prodanović, Slaven (Faculty of Agriculture, Belgrade-Zemun (Serbia)) | Živanović, Tomislav (Faculty of Agriculture, Belgrade-Zemun (Serbia))
Sugar beet cultivars have different responses in various environments, such as different locations, years, mineral nutrition treatments or the combination of these factors, due to genotype × environment interaction. Additive main effect and multiplicative interaction (AMMI) is one of the most commonly used multivariate methods for analysis and visualization of genotype × environment interaction data. The main goals of the present study were to (i) investigate the application of AMMI method in the analysis of genotype × fertilizer interaction in sugar beet, (ii) to assess genotype × fertilizer interaction, and (iii) to identify sugar beet cultivars with the most stable response and high yield performance across different mineral nutrition treatments. The trial with eight sugar beet cultivars was conducted in two successive growing seasons at Rimski šančevi, Serbia. The different levels of nitrogen, phosphorous and potassium fertilizers (0, 50, 100 and 150 kg ha-1) and their combinations represented specific environments for testing genotype × fertilizer interaction. Results from the analysis of variance indicated that the fertilizer treatment, cultivars, and their interaction significantly affected root yield variation in both seasons. Results from our study suggest that AMMI model with two and three first IPCA axes were recommended in 2014 and 2015, respectively. According to AMMI 1 and AMMI 2 biplot, E14 and E15 were high yielding and among the most stable treatments in both years. Among high yielding genotypes in 2014, G4 and G8 stand out as the most stable, while in the following year G3 had the lowest interaction score. AMMI analysis enabled identification of specific associations between cultivars and different mineral nutrition treatments, which was important for adjustment of fertilizer management for each cultivar in order to achieve high root yield with decreased and more rational fertilizer doses.
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