scholarly journals GGE Biplot Analysis for Yield Stability in Multi-environment Trials of Promising Hybrid Rice (Oryza sativa L.)

2015 ◽  
Vol 19 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Anowara Akter ◽  
M Jamil Hasan ◽  
Umma Kulsum ◽  
MH Rahman ◽  
M Khatun ◽  
...  
Keyword(s):  
Grain Yield ◽  
Oryza Sativa L ◽  
High Yield ◽  
Gge Biplot ◽  
Yield Data ◽  
Biplot Analysis ◽  
Stability Performance ◽  
Sources Of Variation ◽  
The Difference ◽  
Ideal Genotype

The genotype and genotype by environment biplot model is an excellent tool for visual multi-environment trials data analysis. In this study we investigated grain yield of six rice genotypes (three tested, one released hybrids and two inbred check varieties) in five environments. The combined analysis of variance for grain yield data indicated that the differences among all sources of variation were highly significant (P<0.001). Environment (E), Genotype (G) and G × E interaction effects accounted for 12.49, 76.51 and 10.21% of the total sum of squares respectively. The first two principal components (PC1 and PC2) were used to display a two-dimensional GGE biplot. Thus, genotypic PC1 scores>0 classified the high yielding genotypes while PC1 scores<0 identified low yielding genotypes. Unlike genotypic PC1, genotypic PC2 scores discriminated the unstable ones. The GGE biplot analysis was useful in identifying stable genotypes with high yield performance. In this study, the polygon view of GGE biplot showed that the vertex genotypes were BRRI1A/BR168R (G1), BRRI10A/BRRI10R (G2) and BRRI dhan28 (G5) having the largest distance from the origin, which was most discriminated genotypes with the unstable ones. These vertex genotypes BRRI1A/BR168R (G1) and BRRI10A/BRRI10R (G2) gave higher yield (PC1 scores>0) while another vertex genotype BRRI dhan28 (G5) produced low yield (PC1 score<0). Hence, the vertex genotype BRRI10A/BRRI10R (G2) was high yielding for all environments and it fell into section 1 following IR58025A/BRRI10R (G3) and BRRI hybrid dhan1 (G4). Mean yield and stability performance over environments of each genotype is explored by using the average environment (tester) coordinate (AEC) methods. These methods show that the genotypes BRRI10A/BRRI10R (G2), IR58025A/BRRI10R (G3) and BRRI hybrid dhan1 (G4) had higher stability as well as higher mean yield while the genotype IR58025A/BRRI10R (G3) had the highest stability out of these three genotypes. The ideal genotype biplot suggests that the closer to ‘ideal’ genotype was IR58025A/BRRI10R (G3) followed by G2 and G4 being more desirable than the other genotypes. Similarly, the environment Barisal (E3) was ‘ideal’ environment followed by E1 (Gazipur), E2 (Comilla) and E5 (Satkhira). Hence, the environment Barisal (E3) is more stable and suitable for all genotypes following Satkhira (E5) because it has large PC1 and small PC2 score but Rangpur (E4) is a discriminating environment because it has large PC2 score. The interrelationship among the environments according to the small angles of test environments was highly positively correlated. Gazipur (E1), Comilla (E2), Barisal (E3) and Satkhira (E5) were closely correlated with small angles but Rangpur (E4) had medium long angles. Comparison between two genotypes showed that BRRI10A/BRRI10R (G2) and IR58025A/BRRI10R (G3) were high yielder in test environments. Thus, the difference between G2 and G3 was relatively small in test environments.Bangladesh Rice j. 2015, 19(1): 1-8

scholarly journals Multienvironment Evaluation of Tannin-Free Photoperiod-Insensitive Sorghum (Sorghum bicolor (L) Moench) for Yield and Resistance to Grain Mold in Senegal

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Cyril Diatta ◽  
Mame P. Sarr ◽  
Thierry Klanvi Tovignan ◽  
Ousmane Aidara ◽  
Daniel Kwadjo Dzidzienyo ◽  
...  
Keyword(s):  
Grain Yield ◽  
Gge Biplot ◽  
Rating Score ◽  
Biplot Analysis ◽  
Stability Performance ◽  
Major Interest ◽  
Grain Mold ◽  
Mold Resistance ◽  
Disease Pressure ◽  
Sorghum Bicolor L

Combining resistance to grain mold with high grain yield in tannin-free white-grained photoperiod-insensitive sorghum is of major interest for farmers in Senegal. In this study, GGE biplot analysis was used to assess the performance, adaptability, and stability of eleven sorghum parental lines and their hybrid combinations for yield and grain mold resistance under Senegalese environments. Eleven inbred lines along with their 22 hybrid combinations and one check were evaluated across three sites during the 2015 and 2016 rainy seasons under natural grain mold infestation. The results of this study showed strong genetic variability among studied genotypes for all measured traits. The highly significant G × E interaction effects for grain yield and panicle grain mold rating score (PGMR) indicated that both traits are influenced by genetics and to some extent by environment. Broad-sense heritability computed was high for all these traits except PGMR, showing a high environmental pressure on this later. The study showed that grain mold pressure in the studied sites decreased following a South-North gradient similar to the rainfall pattern, with the south region wetter, explaining the high disease pressure in Darou and Sinthiou Maleme contrary to Bambey. The GGE biplot analysis performed showed that the first two principal components explained 85.84% of the total variation of GGE sum of squares for grain yield. The which-won-where view of the GGE biplot for grain yield showed that the hybrid HB16 was the most adapted for Bambey area. The ranking of genotypes based on both yield performance and stability showed that HB16, HB5, HB21, HB18, and HB7 were the best hybrids combining high grain yield, high stability performance, and tolerance to grain mold disease across the test environments. These hybrids outperformed the best yielding inbred line P29 (2196.7 kg ha−1) with grain yield advantages ranging 17–60%. Therefore, these hybrids could be recommended to farmers in order to improve sorghum yield in Senegal.

Grain yield stability of barley genotypes in uniform regional yield trails in warm and semi warm dry land area

2017 ◽  
Author(s):  
Hassan Khanzadeh ◽  
Behroz Vaezi ◽  
Rahmatolah Mohammadi ◽  
Asghar Mehraban1 ◽  
Tahmaseb Hosseinpor ◽  
...  
Keyword(s):  
Grain Yield ◽  
Agricultural Research ◽  
Gge Biplot ◽  
Ge Interaction ◽  
Dry Land ◽  
Biplot Analysis ◽  
Ammi Model ◽  
Cropping Seasons ◽  
Ideal Genotype ◽  
Better Than

The aim of this study was to assess the effect of GEI on grain yield of barley advanced lines and exploit the positive GEI effect using AMMI and SREG GGE biplot analysis. Therefore, 18 lines were evaluated at five research stations (Ghachsaran, Mogan, Lorestan, Gonbad and Ilam) of Dryland Agricultural Research Institute (DARI), in the semi-warm regions in Iran, in 2012, 2013 and 2014 cropping seasons under rain-fed conditions. Analysis of variance showed that grain yield variation due to the environments, genotypes and GE interaction were highly significant (p>0.01), which accounted for 68.9%, 9.3% and 22.7% of the treatment combination sum of squares, respectively. To determine the effects of GEI on yields, the data were subjected to AMMI and GGE biplot analysis. The first five AMMI model terms were highly significant (p>0.01) and the first two terms explained 59.56% of the GEI. There were two mega-environments according to the SREG GGE model. The best genotype in one location was not always the best in other test locations. According to AMMI1 biplot, G2, G4, G5 and G6 were better than all other genotypes across environments. G2 was the ideal genotype to plant in Gachsaran. It seems that Ghachsaran is the stable environment between the environments studied and next in rank was Gonbad. In finally, the ATC method indicated that G1, G3, G4 and G6 were more stable as well as high yielding.

scholarly journals Analysis of genotype × environment interaction in rain-fed durum wheat of Iran using GGE-biplot and non-parametric methods

2012 ◽  
Vol 92 (4) ◽  
pp. 757-770 ◽  
Author(s):  
Reza Mohammadi ◽  
Ahmed Amri
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Environment Interaction ◽  
Parametric Methods ◽  
Gge Biplot ◽  
Ge Interaction ◽  
Yield Data ◽  
Stability Performance ◽  
Genotype Environment Interaction ◽  
Non Parametric

Mohammadi, R. and Amri, A. 2012. Analysis of genotype × environment interaction in rain-fed durum wheat of Iran using GGE-biplot and non-parametric methods. Can. J. Plant Sci. 92: 757–770. Multi-environment trials (MET) are conducted annually throughout the world in order to use the information contained in MET data for genotype evaluation and mega-environment identification. In this study, grain yield data of 13 durum and one bread wheat genotypes grown in 16 diversified environments (differing in winter temperatures and water regimes) were used to analyze genotype by environment (GE) interactions in rain-fed durum MET data in Iran. The main objectives were (i) to investigate the possibility of dividing the test locations representative for rain-fed durum production in Iran into mega-environments using the genotype main effect plus GE interaction (GGE) biplot model and (ii) to compare the effectiveness of the GGE-biplot and several non-parametric stability measures (NPSM), which are not well-documented, for evaluating the stability performance of genotypes tested and the possibility of recommending the best genotype(s) for commercial release in the rain-fed areas of Iran. The results indicate that the grain yield of different genotypes was significantly influenced by environmental effect. The greater GE interaction relative to genotype effect suggested significant environmental groups with different top-yielding genotypes. Warm environments differed from cold environments in the ranking of genotypes, while moderate environments were highly divergent and correlated with both cold and warm environments. Cold and warm environments were better than moderate environments in both discriminating and representativeness, suggesting the efficiency and accuracy of genotype selection would be greatly enhanced in such environments. According to the NPSM, genotypes tend to be classified into groups related to the static and dynamic concepts of stability. Both the GGE-biplot and NPSM methods were found to be useful, and generally gave similar results in identifying high-yielding and stable genotypes. In contrast to NPSM, the GGE-biplot analysis would serve as a better platform to analyze MET data, because it always explicitly indicates the average yield and stability of the genotypes and the discriminating ability and representativeness of the test environments.

scholarly journals Stability Assessment of Single-Cross Maize Hybrids Using GGE-Biplot Analysis

2021 ◽  
Vol 13 (2) ◽  
pp. 78
Author(s):  
L. Musundire ◽  
J. Derera ◽  
S. Dari ◽  
A. Lagat ◽  
P. Tongoona
Keyword(s):  
Grain Yield ◽  
South African ◽  
Inbred Line ◽  
Inbred Lines ◽  
Yield Potential ◽  
Research Station ◽  
Gge Biplot ◽  
Single Cross ◽  
Ideal Genotype ◽  
Single Cross Hybrids

Grain yield potential of new maize hybrid varieties across target environments contributes to the uptake of these varieties by farmers. Evaluation of single-cross hybrids developed from test crossing introgressed inbred lines bred for three distinct environments to elite tropical inbred line testers was carried out. The study&rsquo;s objective was to assess grain yield stability and genotype adaptability of the single-cross hybrids across South African environments relative to adapted commercial hybrid checks. One hundred and twenty-two introgressed inbred lines developed using the pedigree breeding program were crossed to four tropical elite inbred line testers using line &times; tester mating design to obtain 488 experimental single cross hybrids. Subject to availability of adequate seed for evaluation, a panel of 444 experimental single-cross hybrids was evaluated using an augmented design in two experiments defined as Population A and B for the study&rsquo;s convenience in South African environments. Data for grain yield (t/ha) performance for experimental single-cross hybrids and commercial check hybrids in Population A and B across environments and individual environments identified experimental single-cross hybrids that had significant comparable grain yield (t/ha) performance relative to best commercial check hybrid (PAN6Q445B) on the market. The selected experimental single-cross hybrids 225, 89, 246 and 43 (Population A) and 112 (Population B) also had a better average rank position for grain yield (t/ha) relative to best commercial check hybrid. These selected experimental single-cross hybrids had a grain yield (t/ha) advantage range of 0.9-6.7% for Population A and 7.3% for Population A and B, respectively, relative to the adapted commercial check hybrid. GGE biplot patterns for which won-where for Population A indicated that at Potchefstroom Research Station and Ukulinga Research Station experimental single-cross hybrids 127 and135 were the vertex (winning) hybrids. Cedera Research Station did not have a vertex hybrid for Population A. For Population B, experimental single-cross hybrids 112, 117 and 18 were the vertex hybrids at Cedera Research Station, Ukulinga Research Station and Potchefstroom Research Station, respectively. Experimental single-cross hybrid 257 was identified as ideal genotype for Population A, while experimental single-cross hybrid 121 in Population B was the ideal genotype. Ideal environments were also identified as Ukulinga Research Station for Population A, and Cedera Research Station for Population B. Average-environment coordination (AEC) view of the GGE biplot in Population A indicated that experimental single-cross hybrids 1 was highly stable across environments. In comparison, Population B experimental single-cross hybrid 161 was highly stable across environments. In conclusion, selected single-cross hybrids in the current study can also be advanced for further evaluation with a possibility for identifying high yielding and stable single-cross hybrids for variety registration and release in target environments in South Africa.

scholarly journals Quality and Grain Yield Attributes of Rwandan Rice (Oryza sativa L.) Cultivars Grown in a Biotron Applying Two NPK Levels

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Alphonsine Mukamuhirwa ◽  
Helena Persson Hovmalm ◽  
Rodomiro Ortiz ◽  
Obedi Nyamangyoku ◽  
Eva Johansson
Keyword(s):  
Grain Yield ◽  
Oryza Sativa L ◽  
Quality Attributes ◽  
Mineral Elements ◽  
Nutritional Composition ◽  
High Yield ◽  
Rice Cultivars ◽  
Yield Attributes ◽  
Yield And Quality ◽  
Grain Yield And Quality

High-yielding rice cultivars with good processing quality and rich in nutrition suitable to a changing climate are of particular importance for future rice-based food production. Here, seven Rwandan rice cultivars were grown in a climate chamber of the biotron facility at the Swedish University of Agricultural Sciences, to be evaluated for their grain yield, nutritional composition, and dough mixing properties. Two different levels of inorganic fertilizer were applied weekly from the seedling stage until flowering. Significant differences for grain yield and quality attributes were found between cultivars. Jyambere showed significantly the highest yield while Ingwizabukungu, Nemeyubutaka, and Jyambere were high in mineral elements content. Ndamirabahinzi and Mpembuke had the highest levels of TPC and TAC. Generally, the lower fertilizer dose resulted in a better performance of the cultivars for both yield and quality attributes. Significantly higher content of Fe, Ca, and Ba was found in grains from the moderate fertilizer dose, whereas K, Na, P, S, Zn, Cd, and Pb increased in grains from the higher fertilizer dose. The cultivar Ndamirabahinzi showed less variability of evaluated characters across fertilizer doses. The results from this study may be used for rice breeding of cultivars with high yield and good grain quality.

scholarly journals Generation of High Yielding and Fragrant Rice (Oryza sativa L.) Lines by CRISPR/Cas9 Targeted Mutagenesis of Three Homoeologs of Cytochrome P450 Gene Family and OsBADH2 and Transcriptome and Proteome Profiling of Revealed Changes Triggered by Mutations

Plants ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 788 ◽  
Author(s):  
Babar Usman ◽  
Gul Nawaz ◽  
Neng Zhao ◽  
Yaoguang Liu ◽  
Rongbai Li
Keyword(s):  
Grain Size ◽  
Cytochrome P450 ◽  
Grain Yield ◽  
Rna Sequencing ◽  
Oryza Sativa L ◽  
Targeted Mutagenesis ◽  
High Yield ◽  
Yield And Quality ◽  
Target Sites ◽  
Cytochrome P450 Family

The significant increase in grain yield and quality are often antagonistic but a constant demand for breeders and consumers. Some genes related to cytochrome P450 family are known for rice organ growth but their role in controlling grain yield is still unknown. Here, we generated new rice mutants with high yield and improved aroma by simultaneously editing three cytochrome P450 homoeologs (Os03g0603100, Os03g0568400, and GL3.2) and OsBADH2 with the CRISPR/Cas9 system, and RNA-sequencing and proteomic analysis were performed to unveil the subsequent changes. High mutation efficiency was achieved in both target sites of each gene and the mutations were predominantly only deletions, while insertions were rare, and no mutations were detected in the five most likely off-target sites against each sgRNA. Mutants exhibited increased grain size, 2-acetyl-1-pyrroline (2AP) content, and grain cell numbers while there was no change in other agronomic traits. Transgene-DNA-free mutant lines appeared with a frequency of 44.44% and homozygous mutations were stably transmitted, and bi-allelic and heterozygous mutations followed Mendelian inheritance, while the inheritance of chimeric mutations was unpredictable. Deep RNA sequencing and proteomic results revealed the regulation of genes and proteins related to cytochrome P450 family, grain size and development, and cell cycle. The KEGG and hub-gene and protein network analysis showed that the gene and proteins related to ribosomal and photosynthesis pathways were mainly enriched, respectively. Our findings provide a broad and detailed basis to understand the role of CRISPR/Cas9 in rice yield and quality improvement.

scholarly journals Descriptive Statistics and Heritability for Agronomic Traits and Grain Micronutrient Content in Rice (Oryza sativa L.)

2019 ◽  
pp. 1-10
Author(s):  
Avinash Kumar ◽  
Ashutosh Kumar ◽  
N. K. Singh ◽  
Rajesh Kumar ◽  
S. K. Singh ◽  
...  
Keyword(s):  
Grain Yield ◽  
Agronomic Traits ◽  
Oryza Sativa L ◽  
Block Design ◽  
Zinc Content ◽  
Yield Potential ◽  
High Yield ◽  
Grain Zinc ◽  
Iron And Zinc ◽  
Breeding Programmes

In the present investigation, 10 parents and their 45 crosses (half diallel) along with 2 standard checks (Rajendra Nilam and Rajendra Mahsuri-1) were evaluated during Kharif, 2018 in Randomized Complete Block Design (RCBD) with 3 replications at Rice Farm Section, Dr. Rajendra Prasad Central Agricultural University (RPCAU), Pusa, Bihar. The objective of this study was to identify promising rice genotypes having desirable combination of morphological traits along with high grain iron and zinc content and high grain yield potential. The results of variability parameters indicated that ample amount of genetic variability was present for all the studied traits. Most of the traits showed high heritability coupled with high genetic advance indicating fruitfulness of selection for improvement of these traits. One genotype (P2×P7) with high grain iron (16.10 ppm) and grain zinc (26.40 ppm) content along with high yield (43.12 g/plant) was identified. Genotypes with high grain iron coupled with high grain yield (P7×P9, P8×P9, P5×P7 and P5×P9) and high  grain zinc content coupled with high grain yield (P4×P7, P9×P10, P8×P9 and P5×P7) were also identified. These promising genotypes identified can be used further in breeding programmes to obtain superior segregants with high grain micronutrient content and high grain yield.

scholarly journals Genotype environment interaction and stability for yield and its components in advanced breeding lines of red rice (Oryza sativa L.)

2020 ◽  
Vol 49 (3) ◽  
pp. 425-435
Author(s):  
BM Dushyantha Kumar ◽  
AP Purushottam ◽  
P Raghavendra ◽  
T Vittal ◽  
KN Shubha ◽  
...  
Keyword(s):  
Grain Yield ◽  
Oryza Sativa L ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Red Rice ◽  
Yield Performance ◽  
Breeding Lines ◽  
Genotype Environment Interaction ◽  
Ammi Analysis ◽  
Total Variability

Effects of genotype, environment and their interaction for grain yield and yield attributing characters in 20 advanced breeding lines of rice across six environments was investigated. Yield stability and adaptability of yield performance were analyzed by Eberhart and Russel model and (GGE) bi-plot. The AMMI analysis of variance indicated that mean squares due to genotypes, location and genotype location contributed per cent 59.08, 5.79 and 21.63, respectively for total variability in grain yield per hectare. Estimates of GGE bi-plot revealed that the lines G1, G3, G11, G13, G15, G12, G16, G7 and G10 were positioned near GGL bi-plot origin indicating wider adaptation for the trait grain yield per hectare. Eberhart and Russel Model and GGE biplot model showed the advanced breeding lines viz., JB 1-11-7 (G1) and JA 6-2 (G15) exhibited wider adaptability across the tested environments for number of productive tillers per plant and yield per hectare.

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