Economical Productivity of Maize Genotypes under Different Herbicides Application in Two Contrasting Climatic Conditions

Dragan Božović, Dragana Popović, Vera Popović, Tomislav Živanović, Nataša Ljubičić, Milivoje Ćosić, Anđela Spahić, Divna Simić and Vladimir Filipović
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Dragan Božović: Faculty of Agriculture, University of Belgrade, 11080 Zemun, Serbia
Dragana Popović: Faculty of Economics in Subotica, University of Novi Sad, 21000 Novi Sad, Serbia
Vera Popović: Institute of Field and Vegetable Crops, 21000 Novi Sad, Serbia
Tomislav Živanović: Faculty of Agriculture, University of Belgrade, 11080 Zemun, Serbia
Nataša Ljubičić: Biosense Institute, University of Novi Sad, 21000 Novi Sad, Serbia
Milivoje Ćosić: Faculty of Agriculture, University of Bijeljina, 76300 Bijeljina, Bosnia and Herzegovina
Anđela Spahić: Faculty of Organization Science, University of Belgrade, 11000 Belgrade, Serbia
Divna Simić: Institute for Applied Science in Agriculture, 11000 Belgrade, Serbia
Vladimir Filipović: Institute for Medicinal Plants Research “Dr. Josif Pančić”, 11000 Belgrade, Serbia

Sustainability, 2022, vol. 14, issue 9, 1-14

Abstract: Maize ranks first among worldwide production and an important source of human and animal feed. Its production can be affected by management practices and climatic conditions. The objective of this study was to estimate stability of yield and hundred grains weight of six maize genotypes during two growing seasons at two locations, subjected to four different treatments: T 1 treatment—without herbicide, Control; T 2 treatment—active substance Nicosulfuron and Motivell commercial preparation; T 3 treatment—active substance Rimsulfuron and Tarot; and, T 4 treatment—active substance Forasulfuron and Equip. Additive main effects and multiplicative interaction—AMMI model and genotype × environment interaction—GGE biplot were used to estimate GEI—genotype by environment interaction. The results showed that the influence of genotype (G), year (Y), locality (L), treatment (T) and all interaction on hundred grains weight were significant. The share of genotypes in the total phenotypic variance was 64.70%, while the share in total interaction was 26.88%. The share of IPCA1 in terms of G × T interaction was 50.6%, while share of IPCA2 was 44.74%, which comprised together 94.80% of interaction. The first IPCA1 axis showed high share in the total interaction, which indicates out significance of genotype in total variation and interaction, while high level of IPCA2 indicates a significant treatment effect. Genotype L-6 had the same mass of 100 grains (37.96 g) during both years of testing, while genotype L-1, with 4.46 g, had the largest difference between years. This clearly indicates the influence of genotype but also stress under the influence of sulfonylureas and environmental factors. The maize genotype with the highest values of hundred grains weight, L-5 and L-6, expressed the highest values of grain yield (4665 kg ha −1 and 4445 kg ha −1 ).

Keywords: Zea mays; genotype; principal components analysis-PCA; grain yield component; stability (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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