Abstract:A genotype is considered to be most adaptive / stable, when it registers high mean yield but show a minimum interaction with the environment. Knowledge of genotype × environment interaction and yield stability are important parameters in breeding new cultivars with improved adaptation to environmental constraints prevailing in the target environments. Therefore, an effort was made to know the genotype - environment interaction and to identify stable single cross hybrids across the environments. Eight newly syn… Show more
“…For the quality traits, the hybrids L7×T3, L9×T3 and L13×T3 for grain protein content, and L1×T1 for grain starch content were found absolutely stable over varying environments. The outcomes were in accordance with Adebayo and Menkir (2014), Raj et al (2019), Arunkumar et al (2020) and Chouhan et al (2021). The hybrids found stable over the different environments for higher grain yield and other traits have been listed in Table 5.…”
Section: Discussionsupporting
confidence: 85%
“…Among the other hybrids, L6×T2 for 50 per cent tasseling, L14×T2 and L1×T3 for 50 per cent silking, and L6×T1, L8×T1, L10×T1, L14×T1, L15×T1, L9×T2, L12×T2, L4×T3, L7×T3 and L15×T3 for anthesissilking interval were found absolutely stable over varying environments for early flowering, therefore these hybrids should be taken under consideration for multi-location trials aimed at identifying hybrids for early flowering under stressed and non-stressed environments. The similar reports were advocated by Haruna et al (2017), Sowmya et al (2018), Raj et al (2019) and Arunkumar et al (2020).…”
Maize production and productivity are hampered by global climate change. The primary concern of crop breeders always have been about high and stable yields. The genotype × environment interaction alters the relative grain yield of genotypes in different environments and makes it difficult to select superior genotypes. Therefore the Eberhart and Russell model for genotype × environment interaction analysis was taken up in the present study for the prediction of performances and phenotypic stability of the single cross hybrids synthesized by crossing 15 inbreds with 3 testers in Line × Tester mating design. All the 18 parents, 45 F1s and 3 checks were evaluated for fifteen quantitative and qualitative traits over three different environments viz., optimal environment, drought stress environment at tasseling stage, and drought stress environment at grain filling stage, during spring 2021, in a Randomized Complete Block Design with three replications. The ANOVA on the basis of pooled data unraveled significance of mean sum of squares due to genotypes and due to genotype × environment interaction which affirms existence of variability and interplay between genotypes and their environments. Out of 45, 39 hybrids expressed non-significant deviation from regression (S2 di) unveiling their higher predictability over changing environments for grain yield per plant. The hybrid L15×T2 had higher mean value than population mean along with regression coefficient equivalent to unity (bi=1) hence was recognized as highly stable and superior for grain yield per plant, and suitable for cultivation in different kinds of environments. Among other hybrids, L6×T2, L14×T2, L1×T3, L8×T1, L10×T1, L14×T1, L15×T1, L12×T2, L4×T3, L15×T3 were noted stable in performance over the environments for flowering traits. While L10×T2, L2×T2, L15×T2, L11×T1, L3×T2 and L5×T2 were recognized stable in performance for higher yield and its component traits over the environments.
“…For the quality traits, the hybrids L7×T3, L9×T3 and L13×T3 for grain protein content, and L1×T1 for grain starch content were found absolutely stable over varying environments. The outcomes were in accordance with Adebayo and Menkir (2014), Raj et al (2019), Arunkumar et al (2020) and Chouhan et al (2021). The hybrids found stable over the different environments for higher grain yield and other traits have been listed in Table 5.…”
Section: Discussionsupporting
confidence: 85%
“…Among the other hybrids, L6×T2 for 50 per cent tasseling, L14×T2 and L1×T3 for 50 per cent silking, and L6×T1, L8×T1, L10×T1, L14×T1, L15×T1, L9×T2, L12×T2, L4×T3, L7×T3 and L15×T3 for anthesissilking interval were found absolutely stable over varying environments for early flowering, therefore these hybrids should be taken under consideration for multi-location trials aimed at identifying hybrids for early flowering under stressed and non-stressed environments. The similar reports were advocated by Haruna et al (2017), Sowmya et al (2018), Raj et al (2019) and Arunkumar et al (2020).…”
Maize production and productivity are hampered by global climate change. The primary concern of crop breeders always have been about high and stable yields. The genotype × environment interaction alters the relative grain yield of genotypes in different environments and makes it difficult to select superior genotypes. Therefore the Eberhart and Russell model for genotype × environment interaction analysis was taken up in the present study for the prediction of performances and phenotypic stability of the single cross hybrids synthesized by crossing 15 inbreds with 3 testers in Line × Tester mating design. All the 18 parents, 45 F1s and 3 checks were evaluated for fifteen quantitative and qualitative traits over three different environments viz., optimal environment, drought stress environment at tasseling stage, and drought stress environment at grain filling stage, during spring 2021, in a Randomized Complete Block Design with three replications. The ANOVA on the basis of pooled data unraveled significance of mean sum of squares due to genotypes and due to genotype × environment interaction which affirms existence of variability and interplay between genotypes and their environments. Out of 45, 39 hybrids expressed non-significant deviation from regression (S2 di) unveiling their higher predictability over changing environments for grain yield per plant. The hybrid L15×T2 had higher mean value than population mean along with regression coefficient equivalent to unity (bi=1) hence was recognized as highly stable and superior for grain yield per plant, and suitable for cultivation in different kinds of environments. Among other hybrids, L6×T2, L14×T2, L1×T3, L8×T1, L10×T1, L14×T1, L15×T1, L12×T2, L4×T3, L15×T3 were noted stable in performance over the environments for flowering traits. While L10×T2, L2×T2, L15×T2, L11×T1, L3×T2 and L5×T2 were recognized stable in performance for higher yield and its component traits over the environments.
“…Similarly, three top hybrids found suitable for poor environments (b i <1) were EI-2176-3 x EI-03, EI-2505 x EI-670 and EI-2653 x EI-03 with non-significant non-linear estimates for the trait grain yield per plant. Similar findings of selection of genotypes for yield and component traits were also reported byLata et al (2010),Karadavut and Akili (2012),Bharathiveeramani et al (2017),Ahmed et al (2017),Synrem et al (2017),Raj et al (2019) andArunkumar et al (2020) in maize.…”
Crop production is the function of genotype, environment and their interaction (GEI) and evaluation of genotypes in multi environments helps in identifying their adaptation and stability. Forty five maize hybrids along with their 18 parents and two checks were evaluated in three environments viz., E1 (Kharif-2019, Instructional Farm, RCA, Udaipur), E2 (Kharif-2019, Agriculture Research Sub-Station, Vallabhnagar, Udaipur) and E3 (Rabi-2019-2020, Instructional Farm, RCA, Udaipur) in randomized block design with three replications at each environment to assess the phenotypic stability of genotypes. The mean squares due to genotypes and environments were found significant for all the traits under study which indicated inherent genetic differences among the genotypes. The mean squares due to G x E (linear) interaction were found significant for most of the traits under study indicating differences among genotypes for linear response to varying environments. The MSS due to pooled deviation were found non-significant for all the traits which indicated major portion of the genotype x environment interaction was formed by predictable component. The majority of the hybrids depicted non-significant deviations from regression (S 2 d i ) for grain yield per plant. It indicated their predictable response across the environments. A great majority of genotypes revealed non-significant non-linear estimates (S 2 d i ) for different traits which suggested that the prediction of stability was more or less accurate and reliable. The top three hybrids suitable for all environments (b i ≈1) were EI-2653 x EI-102, EI-2639 x EI-670 and EI-2505 x EI-102 with non-significant S 2 d i values. The hybrids EI-2176-3 x EI-03, EI-2525-2 x EI-03 and EI-2159 x EI-670 out yielded the best check cultivar CC-1 for grain yield per plant. Thus, these combinations may be exploited commercially after further multi location yield testing.
“…As a multipurpose crop, maize is used as food, feed and fodder. The genetic potential of maize to produce high yield under wide range of environment is what makes this cereal crop "queen of cereals" (Arunkumar et al, 2020). Maize contributes a major share into the global food bowl and more than 150 Mha of maize is cultivated, accounting for nearly 36% of the total food grain production (Sah et al, 2020).…”
Section: Introductionmentioning
confidence: 99%
“…Maize contributes a major share into the global food bowl and more than 150 Mha of maize is cultivated, accounting for nearly 36% of the total food grain production (Sah et al, 2020). The adoption of high yielding maize hybrids instead of traditionally used open pollinated varieties (OPV) has contributed vastly towards a quantum jump in production (Arunkumar et al, 2020).…”
Background: In the wake of unpredictable climate change, it is imperative for the breeders to identify hybrids with better adaptation to meet the growing food demand. The present study was carried out to identify stable maize hybrids across various environments. Methods: Twenty one maize hybrids along with two commercial checks viz., CP-818 and Bioseed-TX369 were tested over three locations viz., Viluppuram, Trivandrum and Nagercoil. The experiments were laid out in randomized block design with three replications. Result: AMMI and GGE analysis of variance revealed that the first two principal axes explained the majority of G ´ E interaction. According to AMMI analysis, the hybrid AUK 6240 was relatively stable with high mean whereas, GGE biplots-genotype view identified AUMH 1277 as stable with better yield per plant. GGE biplot-environment view identified Nagercoil as the ideal test location. What-won-where biplots identified three hybrids viz., AU-101, AU-110 and CP-818 suited to Viluppuram and Nagercoil. Though, hybrids with specific adaptability and ideal test location were efficiently identified, study must be extended to more number of environments and hybrids.
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