The impact of different nutritional treatments on maize hybrids morphological traits based on stability statistical methods

Mousavi, Seyed Mohammad Nasir; Illés, Árpád; Bojtor, Csaba; Nagy, János

doi:10.9755/ejfa.2020.v32.i9.2147

Cited by 22 publications

(16 citation statements)

References 16 publications

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“…It makes it possible to examine the relationships between the environments and identify the target environments in breeding plans [11]. This model was applied when studying the genotype interacting with the environment in wheat [12], barley [13,14], and maize [15][16][17][18][19][20][21][22]. In a study during two years for 10 regions on the stability of Chinese maize hybrids grain performance, Fan et al [18] used the GGE biplot and other stability statistics.…”

Section: Introductionmentioning

confidence: 99%

Stability on Maize Hybrids Based on GGE Biplot Graphical Technique

et al. 2022

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In this study, 12 maize hybrids were planted and evaluated to determine the effect of genotype and genotype-environment interaction (GEI) base GGE (genotype plus genotype-by-environment) using a Graphical biplot technique in four research stations (Arak, Birjand, Shiraz and Karaj) within two years using a Randomized Complete Blocks Design (RCBD). The combined analysis of variance showed that the effects of the environment, genotype and genotype-environment interaction (GEI) were significant in the one percent probability level. GGE biplot results indicated that the first and second principal components (PC1 and PC2) explained more than 83% of the grain performance variation. Simultaneous study of grain performance and hybrid stability using the biplot of average environment coordinates showed that the KSC705 genotype had the highest yield and stability. Polygon view divided the studied areas into two mega-environments (MEs) and identified the best genotypes in each mega-environment (ME). In the first mega-environment (ME1), the Karaj and Shiraz with KSC706 and KSC400 genotypes were detected, and were the best; and in the second mega-environment (ME2), Arak and Birjand with KSC704 and KSC707 genotypes performed better. The biplot graph for the correlation between the genotypes categorized the studied hybrids into four groups positively related to each other based on the angles between vectors. The KSC704 and KSC707 genotypes were desirable in the yield in Shiraz and Karaj and KSC706 were in Arak and Birjand. Additionally, Arak-Birjand, Karaj-Shiraz showed a positive and significant correlation. Birjand and Karaj had most genotype interaction with each other.

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Section: Introductionmentioning

confidence: 99%

Stability on Maize Hybrids Based on GGE Biplot Graphical Technique

et al. 2022

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“…Comparing the mean of Duncan method genotypes under normal and stress conditions showed that KSC707, SC301 and KSC704 genotypes had better performance than other hybrids in all evaluated traits, respectively. Additionally, the DC307 genotype under normal conditions and the KSC400 genotype under stress conditions were identified as hybrids with low yield and rank ( Table 2 ), Mousavi et al [ 22 ]. In their experiments under normal humidity conditions, the KSC704 genotype had the highest yield compared to other hybrids.…”

Section: Resultsmentioning

confidence: 99%

Comparison of Maize Genotypes Using Drought-Tolerance Indices and Graphical Analysis under Normal and Humidity Stress Conditions

Shojaei

Mostafavi

Omrani

et al. 2022

Plants

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This study aimed to identify drought-tolerant genotypes and to evaluate and compare the response of genotypes under normal conditions and humidity stress. The experiment was conducted in a Randomized Complete Block Design (RCBD) on 12 commercial single cross hybrids of maize (Zea mays L.) with three replications in two separate experiments under normal and stress conditions. GT biplot was used to compare genotypes under normal conditions and humidity stress. Based on the polygon diagrams’ graphical analysis, KSC206, KSC704, KSC705 and KSC706 genotypes were identified as desirable hybrids. The ranking diagram of genotypes based on ideal genotype also showed that the KSC704 genotype had high desirability in all evaluated traits in normal and stress conditions. TOL, MP, HARM, GMP, SSI and STI indices were used to identify drought-tolerant genotypes, and the genotypes were ranked based on this index. Based on this, KSC260, SC302 and KSC400 hybrids were selected as resistant hybrids. Based on the correlation analysis between drought-tolerance indices, a positive correlation was observed between MP, GMP, HARM and STI indices. Based on the analysis of the PCA on the indices, the first and second principal components were given the titles of grain yield tolerance component under humidity stress conditions and grain yield stability component under normal humidity conditions, respectively. KSC704 was superior to other hybrids in terms of grain yield under normal conditions and stress, and the KSC260 hybrid was identified as a tolerant hybrid in terms of all studied traits under drought stress.

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“…In many studies, fertilizer's positive effect emphasized raising grain yield, the number of kernels in an ear, and kernel value in different corn genotypes. Fertilizer causes proliferation of the leaf number, leaf size and width, and the plant's dry matter [35][36][37][38][39][40][41]. The number of seeds per row had a minimum effect for treatments and low stability in terms of GGE analysis.…”

Section: Discussionmentioning

confidence: 99%

Genotype by Trait Interaction (GT) in Maize Hybrids on Complete Fertilizer

Mousavi

Bojtor

Illés

et al. 2021

Plants

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We investigated the interaction between genotype by trait, and an experiment was conducted at the University of Debrecen. Two maize cultivars, FAO340 and FAO410, were studied in a randomized complete block design with four replications. This experiment was applied to the six fertilization treatments. Fertilizer levels were NPK0 (control) (N:0, P2O5:0, K2O:0), NPK1 (N:30, P2O5:23, K2O:27), NPK2 (N:60, P2O5:46, K2O:54), NPK3 (N:90, P2O5:69, K2O:81), NPK4 (N:120, P2O5:92, K2O:108), and NPK5 (N:150, P2O5:115, K2O:135). The first principal component showed 54.24%, and the second principal component showed 20.75%, which explained the total squares interaction using the AMMI model in the case of the FAO410 hybrid. As regards the FAO340 hybrid, the first principal component showed 58.18%, and the second principal component showed 18.04%, explaining the total squares interaction using the AMMI model in the FAO410 hybrid. In the GGE biplot on FAO410, the first and the second principal components covered 91.20% of the total data in this analysis. Accordingly, the desirable treatment was NPK5, followed by NPK4, NPK2, NPK3, NPK1, and NPK0. NPK4 and NPK5 had the most desirable treatments for the number of seeds per row, chlorophyll, weight of 1000 seeds, and stem diameter in the case of the FAO410 hybrid.

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The impact of different nutritional treatments on maize hybrids morphological traits based on stability statistical methods

Cited by 22 publications

References 16 publications

Stability on Maize Hybrids Based on GGE Biplot Graphical Technique

Stability on Maize Hybrids Based on GGE Biplot Graphical Technique

Comparison of Maize Genotypes Using Drought-Tolerance Indices and Graphical Analysis under Normal and Humidity Stress Conditions

Genotype by Trait Interaction (GT) in Maize Hybrids on Complete Fertilizer

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