Genotype × environment interaction and selection of maize (Zea mays L.) hybrids across moisture regimes

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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Stability on Maize Hybrids Based on GGE Biplot Graphical Technique

Natural occurrence of deoxynivalenol, nivalenol and deoxynivalenol-3-glucoside in cereal-derived products from Egypt

One of the best biometrical methods for estimating genetic diversity among germplasm collections is multivariate analysis; it is used to study their variability and genetic relatedness in order to increase their value in plant breeding programs. The objectives of the present study were to: (i) evaluate the magnitude of genetic diversity, based on phenotypic data, among 19 maize genotypes, under drought and/or low N stressed conditions in the field, using principle component analysis (PCA) and (ii) assess the interrelationships between maize grain yield and its related traits under such stressed conditions using genotype × trait (GT) biplot analysis. An experiment was Original Research Article Al-Naggar et al.; AJBGMB, 4(2): 26-44, 2020; Article no.AJBGMB.57573 27 conducted in two seasons using a split-split plot design with 3 replications, where 2 irrigation regimes (well-watered and water stressed at flowering) occupied the main plots, three N rates (high N, medium N and low N) occupied the sub plots and 19 maize genotypes occupied the sub-sub plots. The genotypes were evaluated for 19 agronomic traits. Analysis of variance was performed under each of the six environments. Significant differences (p≤0.01) were recorded among the maize genotypes for all studied traits under each environment. The best genotypes for each trait were identified. Results of the GT biplot indicated that high means of 100-kernel weight (100-KW), ears/plant (EPP), ear height, days to silking, days to anthesis, plant height, and chlorophyll concentration index (CCI) under water stress (WS), kernels/row (KPR), EPP, 100-KW and CCI under low N and KPR, EPP and 100-KW under WS combined with low N environment and low values of anthesis-silking interval (ASI) under the three stressed environments could be considered selection criteria for high grain yield under respective stressed environments and for drought and/or low N tolerance. It is recommended to select for high values of KPR, EPP and 100-KW and low value of ASI in order to increase grain yield under such stressed conditions.

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Genetic Variability of Maize Hybrids and Populations and Interrelationships among Grain Yield and Its Related Traits under Drought and Low N Using Multivariate Analysis

Exploiting new genetic resources is an effective way to achieve sustainable wheat production. To this end, we exposed wheat seeds of the “Punjab-11” cultivar to gamma rays. A total of 32 stable mutants (M7) were developed, followed by characterization by conducting multilocation trials over two seasons. Principal component analysis (PCA) showed that the first six components accounted for 90.28% of the total variation among the plant height, tillers per plant, 1000-kernel weight, grain yield, and quality traits. All mutants were grouped into three clusters based on high yield index values. The genotype by trait (GT) bi-plot revealed significant associations between yield and its components among the mutants. Positive correlations were estimated for tillers per plant, plant height, 1000-kernel weight, and grain yield; however, yield components showed negative associations with protein, moisture, and gluten contents. The mutant lines Pb-M-59 waxy, Pb-M-1272 waxy, Pb-M-2260, Pb-M-1027 waxy, Pb-M-1323 waxy, and Pb-M-1854 exhibited maximum grain yield, 1000-grain weight, and tillers per plant values. Likewise, Pb-M-2725, Pb-M-2550, and Pb-M-2728 were found to be the best mutant lines in terms of grain quality; thus, the use of gamma radiation is effective in improving the desirable traits, including yield and grain quality. It is suggested that these traits can be improved beyond the performance of corresponding traits in their parent genotypes. The newly produced mutants can also be used to explore the genetic mechanisms of complex traits in the future.

Characterization of Gamma-Rays-Induced Spring Wheat Mutants for Morphological and Quality Traits through Multivariate and GT Bi-Plot Analysis

Among the phenotypic, biochemical, and molecular methods employed in assessment of genetic diversity, the phenotypic method has proven efficient for the assessment, description and classification of germplasm collections to enhance their use in maize breeding. The objectives of the present study were: (i) to assess the extent of genetic diversity in a collection of Egyptian commercial maize hybrids and populations, through field evaluation under water and N stressed and non-stressed conditions, using morphological data based on Principle Component Analysis (PCA), (ii) to measure the genetic distance among these genotypes using UPGMA cluster analysis and (iii) to assess the relationship between grain yield and yield-related traits of maize genotypes using GT-biplot analysis. A two-year field experiment was conducted in a split-split plot design with 3 replications, where 2 irrigation regimes, three N rates and 19 maize genotypes occupied the main plots, sub plots and sub-sub plots, respectively. The germplasm was assessed for 21 agronomic traits. Highly significant differences (P ≤ 0.01) were observed among the maize hybrids and populations for all measured traits.  Results of the GT biplot in the present study indicated that high values of 100-Kernel weight, ears/plant, kernels/plant, kernels/row, plant height, nitrogen use efficiency, nitrogen utilization efficiency, and grain nitrogen content and short ASI could be considered reliable secondary traits for improving grain yield under stressed and non-stressed conditions. The highest genetic distance was found between G9 (SC-2055) and each of G15 (American Early Dent), G18 (Midland) or G19 (Ried Type). The Agglomerative Hierarchical Clustering based on phenotypic data assigned the maize genotypes into five groups. The different groups obtained can be useful for deriving the inbred lines with diverse features and diversifying the heterotic pools.

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Genetic Diversity Based on Morphological Traits of 19 Maize Genotypes Using Principal Component Analysis and GT Biplot

The secondary trait for a given abiotic stress tolerance, should be of strong correlation (r) with grain yield, high heritability (h 2 b) and high genetic advance (GA) under stressed conditions. The main objective of the present investigation was to identify secondary trait(s) for drought and/or lowN tolerance in maize genotypes. A two-year experiment was conducted, using a split-split-plot design. Main plots were allotted to two irrigation regimes, i.e. well watering (WW) and water stress at flowering (WS), sub-plots to three N fertilizer rates, i.e. low (LN), medium (MN) and high (HN) and sub-sub-plots to nineteen maize genotypes. Analysis of variance of randomized complete blocks design (RCBD) was also performed under each of the six environments (WW-HM, WW-MN, WW-LN, WS-HN, WS-MN and WS-LN). Tolerance to drought and/or low-N was strongly correlated with grain yield/plant (GYPP) under stressed environments. GYPP had high (h 2 b) and (GA); thus it is considered the best indicator of drought, low N or both stresses tolerance. The best secondary traits are high 100-kernel weight (100-KW), ears/plant (EPP), kernels/row (KPR), and short Original Research Article Al-Naggar et al.; AJAHR, 6(2): 30-44, 2020; Article no.AJAHR.58605 31 anthesis-silking interval (ASI) for low-N tolerance, high EPP, 100-KW, plant height (PH) and short ASI for drought tolerance, high 100-KW, EPP, KPR, PH and short ASI, for tolerance to drought combined with low N, and high 100-KW, rows/ear (RPE) and KPR under optimum conditions (WWHN), since they show high (r), high (h 2 b) and high (GA) estimates under the respective environments. Under low-N and/or drought, future research should focus on the incorporation of secondary traits such as EPP, KPR, 100-KW, PH, ASI in the selection programs along with the grain yield trait.

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Secondary Traits for Maize (Zea mays L.) Tolerance to Drought Combined with Reduced N Fertilization Rate

Deficit irrigation and low nitrogen (N) fertilization rate cause negative effects on maize grain productivity; such effects differ from genotype to genotype. The main objectives of the present investigation were to: (i) identify the drought and low N tolerant genotypes, (ii) estimate the superiority of tolerant to sensitive genotypes and (iii) assess the differential response of maize genotypes to elevated levels of nitrogen. Maize genotypes were evaluated in 2016 and 2017 seasons under three N rates: high; 285.6, medium; 166.6 and low; 47.6 kg N/ha and two irrigation regimes: well-watered (WW) and water stressed (WS) at flowering. A split-split-plot design with three replications was used. Main plots were allotted to irrigation regimes, sub-plots to N rates and sub-sub-plots to genotypes. The tolerant (T) and sensitive (S) genotypes were identified under each stress. Grain yield/plant (GYPP) of T genotypes was significantly (P≤ 0.01) superior to as compared to S genotypes by 109.5%, 39.6% and 141.9% under Low-N, drought, and drought combined with low-N, respectively. Superiority of T over S genotypes in GYPP was associated with significant (P≤ 0.01) superiority in ears/plant (11.5, 13.15 and 11.99%), 100-kernel weight (38.65, Original Research Article Al-Naggar et al.; ARRB, 35(6): 9-33, 2020; Article no.ARRB.58377 10 30.46 and 30.99%), kernels/row (22.81, 11.28 and 20.07%), Nitrogen use efficiency (109.49, 39.62 and 141.89%) and shortening in anthesis-silking interval (-44.56, -29.58 and -29.08%), under the three environments, respectively. A significant linear response on elevated levels of nitrogen was shown by 13 genotypes, but a quadratic response was shown by six genotypes. The present study suggested that further investigation should be conducted to identify the optimum N fertilization rate for each newly developed variety of maize.

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R. Y. M. Musa

Papers

Genetic Diversity Based on Morphological Traits of 19 Maize Genotypes Using Principal Component Analysis and GT Biplot

Genetic Variability of Maize Hybrids and Populations and Interrelationships among Grain Yield and Its Related Traits under Drought and Low N Using Multivariate Analysis

Secondary Traits for Maize (Zea mays L.) Tolerance to Drought Combined with Reduced N Fertilization Rate

Response of Maize (Zea mays L.) to Deficit Irrigation Combined with Reduced Nitrogen Rate is Genotype Dependent