Phenotypic Stability Analysis of Oil Yield in Sesame (Sesamum indicum L.) Verities across the Awash Valleys in Ethiopia

2015 ◽  
Vol 5 (2) ◽  
pp. 650-657
Author(s):  
Mohammed Abate Dawud ◽  
Firew Mekbib Alemu
Keyword(s):  
Stability Analysis ◽  
High Performance ◽  
Block Design ◽  
Principal Component ◽  
Oil Yield ◽  
Yield Potential ◽  
Ammi Model ◽  
Testing Environments ◽  
High Yielding Varieties ◽  
Sesame Genotypes

A study was conducted to estimate the nature and magnitude of G x E Interaction (GEI) for oil yield in sesame varieties and to identify stable and promising varieties for general and specific adaptations. The experiment was carried out at three locations across the areas of the Awash Valley in Ethiopia; namely Assaita, Melkassa and Werer over two seasons during the 2011 cropping and 2012 off seasons. Ten improved sesame varieties were planted in a randomized complete block design (RCBD) replicated trice in each location and year. Analysis of variance using AMMI model revealed significant differences (P<0.01) for genotype, environment, GEI and interaction principal component (IPCA1), suggesting differential response of varieties across testing environments and the need for stability analysis. Stability analysis using Biplot graph and AMMI stability value were done to further shed light on the GEI of oil yield. The study revealed that the environment Wr1 (Werer season-I) had relatively little interaction effects with above average mean oil yield per environment. Hence, it can be recommended as ideal environment for growing the present set of sesame genotypes for breeding programme. Ranking of genotypes based on the different stability indices identified the varieties Adi and Serkamo to be the most stable genotypes across all environments. Therefore, these varieties can be recommended as promising cultivars for oil yield of sesame across diverse agro-ecologies of the Awash Valley to exploit their yield potential. On the other hand, the two high yielding varieties Abasena and Tate were found to be highly interactive and they are recommended for cultivation under favorable environmental conditions for oil yield. Moreover, the study indicated that high performance of genotypes for oil yield recorded in season two (2012). Hence, the off season generally is suggested as the best environment for oil yield of sesame across the areas of the Awash Valley. In this study, AMMI analysis with two IPCA was the best predictive model to reveal the maximum GEI for oil yield in sesame.

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

Plants ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 2388
Author(s):  
Seyed Mohammad Nasir Mousavi ◽  
Csaba Bojtor ◽  
Árpád Illés ◽  
János Nagy
Keyword(s):  
Block Design ◽  
Principal Component ◽  
Gge Biplot ◽  
Maize Hybrids ◽  
Maize Cultivars ◽  
Randomized Complete Block Design ◽  
Total Data ◽  
Ammi Model ◽  
Complete Fertilizer ◽  
The University

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.

scholarly journals COMPARISON OF YIELD AMONG DIFFERENT HIGH YIELDING VARIETIES OF WETLAND RICE

Agric ◽  
2021 ◽  
Vol 33 (1) ◽  
pp. 57-66
Author(s):  
Kiki Kusyaeri Hamdani ◽  
Yati Haryati
Keyword(s):  
Yield Components ◽  
Block Design ◽  
Yield Component ◽  
Yield Potential ◽  
Duncan Multiple Range Test ◽  
Rice Varieties ◽  
Randomized Complete Block Design ◽  
High Yielding Varieties ◽  
Range Test ◽  
Better Than

New superior varieties (VUB) are a reliable technological innovation to increase rice productivity. This study aims to determine the yield potential of some lowland rice VUB. The assessment was carried out on land owned by a member of the Sumber Rejeki Farmer Group, Cintaratu Village, Lakbok District, Ciamis Regency at Dry Season II in June-September 2020. The study used a randomized complete block design (RCBD) with six varieties of treatment and was repeated ten times. The varieties tested were Inpari 32, Inpari 42, Padjadjaran, Cakrabuana, Inpari IR Nutrizinc, and Siliwangi varieties. The variables observed included the growth component, yield component, and yield component. Data were analyzed using the F test followedby the Duncan Multiple Range Test at the Q=5% level. In addition, a correlation test was conducted between the growth components, yield components, and yields. The results of the study indicated that the new superior rice varieties studied had different performance in growth, number of tillers, yield, and yield components. Inpari 42 variety produced the highest productivity, namely 6.88 ton ha-1 which was supported by the number of grains per panicle, percentage of filled grains per panicle, and percentage of empty grain per panicle which were better than other varieties. Plant height and number of grains per panicle were positively correlated with yield.

The use of an AMMI model and its parameters to analyse yield stability in multi-environment trials

2008 ◽  
Vol 146 (5) ◽  
pp. 571-581 ◽  
Author(s):  
N. SABAGHNIA ◽  
S. H. SABAGHPOUR ◽  
H. DEHGHANI
Keyword(s):  
Stability Analysis ◽  
Crop Improvement ◽  
Principal Component ◽  
Environmental Variance ◽  
Combined Analysis ◽  
Genotype By Environment ◽  
Breeding Programmes ◽  
Ammi Model ◽  
Index Measure ◽  
Stability Statistics

SUMMARYGenotype by environment (G×E) interaction effects are of special interest for breeding programmes to identify adaptation targets and test locations. Their assessment by additive main effect and multiplicative interaction (AMMI) model analysis is currently defined for this situation. A combined analysis of two former parametric measures and seven AMMI stability statistics was undertaken to assess G×E interactions and stability analysis to identify stable genotypes of 11 lentil genotypes across 20 environments. G×E interaction introduces inconsistency in the relative rating of genotypes across environments and plays a key role in formulating strategies for crop improvement. The combined analysis of variance for environments (E), genotypes (G) and G×E interaction was highly significant (P<0·01), suggesting differential responses of the genotypes and the need for stability analysis. The parametric stability measures of environmental variance showed that genotype ILL 6037 was the most stable genotype, whereas the priority index measure indicated genotype FLIP 82-1L to be the most stable genotype. The first seven principal component (PC) axes (PC1–PC7) were significant (P<0·01), but the first two PC axes cumulatively accounted for 71% of the total G×E interaction. In contrast, the AMMI stability statistics suggested different genotypes to be the most stable. Most of the AMMI stability statistics showed biological stability, but the SIPCF statistics of AMMI model had agronomical concept stability. The AMMI stability value (ASV) identified genotype FLIP 92-12L as a more stable genotype, which also had high mean performance. Such an outcome could be regularly employed in the future to delineate predictive, more rigorous recommendation strategies as well as to help define stability concepts for recommendations for lentil and other crops in the Middle East and other areas of the world.

scholarly journals Interaksi Genotipe x Lingkungan Hasil dan Komponen Hasil 14 Genotipe Tomat di Empat Lingkungan Dataran Rendah

2015 ◽  
Vol 43 (1) ◽  
pp. 59
Author(s):  
Suprayanti Martia Dewi ◽  
Sobir , ◽  
Muhamad Syukur
Keyword(s):  
Stability Analysis ◽  
Block Design ◽  
Fruit Weight ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Genotype X Environment ◽  
Gxe Interaction ◽  
Superior Genotype ◽  
Ammi Model ◽  
The Stability

Genotype x environment interaction (GxE) information is needed by plant breeders to assist the identification of superior genotype. Stability analysis can be done if there is a GxE interaction, to show the stability of a genotype when planted in different environments. This study aimed to estimate the effects of genotype x environment interaction on yield and yield components of fruit weight per plant as well as to look at the stability of 14 tomato genotypes at four lowland locations. The study was conducted at four locations, namely Purwakarta, Lombok, Tajur and Leuwikopo. Experiments at each location was arranged in a randomized complete block design with three replications. Stability analysis was performed using the AMMI model. Fruit weight, fruit diameter, number of fruits per plant and total fruit weight per plant characters showed highly significant genotype x environment interactions. Variability due to the effect of GxE interaction based on a AMMI2 contributed by 88.50%. IPBT3, IPBT33, IPBT34, IPBT60 and Intan were stable genotypes under AMMI model.<br />Keywords: AMMI, multilocation trials

Principal Component Analysis and Stability of Genotypes in French Bean (Phaseolus vulgaris L.)

2021 ◽  
Author(s):  
B. Rajasekhar Reddy ◽  
Maneesh Pandey ◽  
J. Singh ◽  
P.M. Singh ◽  
N. Rai
Keyword(s):  
Principal Component Analysis ◽  
Stability Analysis ◽  
Principal Components ◽  
Block Design ◽  
Principal Component ◽  
Component Analysis ◽  
French Bean ◽  
Pod Yield ◽  
Randomized Block Design ◽  
Stable Yield

Background: Principal component analysis and Finlay-Wilkinson stability analysis were carried out at research farm of ICAR-Indian Institute of Vegetable Research, Varanasi to identify diverse french bean genotypes for green pod yield and suitable genotypes for stable yield and yield related parameters.Methods: All the 24 genotypes were laid out in randomized block design with two replications during winter, 2017 and 2018. Principal component analysis and stability analysis was done to identify the diverse and stable genotypes.Result: Eight principal components were observed and the maximum variability was concentrated in the first three principal components PC1, PC2 and PC3 which contributed to 68.61% variance. Cluster analysis from principal component scores formed three clusters with a maximum of seventeen genotypes in cluster I followed by six genotypes in cluster II and one genotype in cluster III. High heritability was observed for 10 pod weight, number of pods per cluster and number of seeds per pod and moderate heritability was observed for yield per plant. Finlay-Wilkinson stability analysis identified the stable genotypes viz., FMGCV 1378, FMGCV 0958, Arka Suvidha, Valentino, Banoa and VRFBB-14-2 for green pod yield per plant, Cartagenta for pod length (cm) and Paulista, Slender Pack, Arka Suvidha, Valentino, FMGCV 0958, Banoa, FORC 6V 1136, VRFBB-14-1, VRFBB-14-2 for number of pods per plant.

scholarly journals Performance of ‘Valência’ sweet orange grafted on trifoliate orange hybrid rootstocks

2021 ◽  
Vol 56 ◽  
Author(s):  
Allan Ricardo Domingues ◽  
Ciro Daniel Marques Marcolini ◽  
Carlos Henrique da Silva Gonçalves ◽  
Carlos Eduardo Alves da Silva ◽  
Sergio Ruffo Roberto ◽  
...  
Keyword(s):  
High Performance ◽  
Production Efficiency ◽  
Sweet Orange ◽  
Block Design ◽  
Principal Component ◽  
Tree Size ◽  
Trifoliate Orange ◽  
Rangpur Lime ◽  
Northwestern Region ◽  
High Production

Abstract The objective of this work was to evaluate tree size, production, and fruit quality of ‘Valência’ sweet orange (Citrus sinensis) grafted on various trifoliate orange rootstocks, in order to select genotypes with a high performance. Twenty rootstock genotypes were evaluated, including trifoliate orange hybrids with mandarin (citrandarins) and with grapefruit (citrumelos), as well as ‘Rangpur’ lime. The experiment was implemented in the northwestern region of the state of Paraná, Brazil, in a 6.0×2.5 m spacing, in a sandy soil under subtropical and rainfed conditions. The statistical model used was the randomized complete block design with four replicates and four trees per plot. Tree size and fruit yield and quality were analyzed during three consecutive harvest seasons. Data were subjected to the analysis of variance, and means were grouped by the Scott-Knott test. Principal component analysis and agglomerative hierarchical clustering were also carried out. F.80-18, F.80-5, and F.80-3 citrumelos and IPEACS-239 citrandarin are adequate rootstock options for ‘Valência’ sweet orange, with dwarf trees and a high production efficiency. These rootstocks, except F.80-18, are also adequate options to obtain oranges with good industrial properties.

scholarly journals Genotype × Environment (G × E) Interaction in Southernpea [Vigna unguiculata (L.) Walp] Genotypes in the Southeastern USA

HortScience ◽  
1998 ◽  
Vol 33 (4) ◽  
pp. 596c-596
Author(s):  
John C. Alleyne ◽  
Teddy E. Morelock ◽  
Clay H. Sneller
Keyword(s):  
Vigna Unguiculata ◽  
Principal Component ◽  
Visual Assessment ◽  
Yield Potential ◽  
Environment Interaction ◽  
Interaction Patterns ◽  
Genotype Environment Interaction ◽  
Principal Component Axis ◽  
Biological Interpretation ◽  
Testing Environments

Genotype by environment (G × E) effects in Regional Cooperative Southernpea trials for the southeastern United States were investigated to characterize the extent, pattern, and potential impact of G × E on seed yield of southernpea [Vigna unguiculata (L.) Walp] genotypes. The structure of G × E effects was investigated using the Additive Main Effect and Multiplicative Interaction (AMMI) method. AMMI analyses revealed a highly significant genotype × environment interaction, most of which was partitioned into a genotype × location component of variance. AMMI first principal component axis scores stratified environments into two groups that minimized variation within groups. Biological interpretation of groupings and visual assessment of the AMMI biplot, revealed high-yielding genotypes interacting positively with one group of environments and conversely, low-yielding genotypes interacting positively with the other group. There were some significant rank changes of genotypes as yield potential varied across environments. Some environments showed similar main effects and interaction patterns indicating that most of the G × E effects could be captured with fewer testing sites, and consequently redundancy of some testing environments over years.

scholarly journals Genetic Divergence and GGE Bi-plot Analysis of Multi-environment Trial Data of Barley (Hordeum vulgare L.) to Identify “Ideal” Genotype

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Pramod Kumar Saroj
Keyword(s):  
Stability Analysis ◽  
Plant Height ◽  
Genetic Divergence ◽  
Block Design ◽  
Trial Data ◽  
Yield Potential ◽  
Ge Interaction ◽  
Yield Data ◽  
Plot Analysis ◽  
Barley Genotypes

The present research revealed the study of genetic divergence and genotype (G) main effect and genotype by the environment (GE) interaction (G × GE) bi-plot analysis for multi-environmental trial data using yield data of three years. Since, genotypes were planted in 2017 in two dates like early and lates own condition hence, there was very slight differences in their yield so both the environments come together as compared to third environment (2018) which for from the two locations of year 2017. The objective of this study was to determine the effects of genotype, environment and their interaction on grain yield and to identify stable barley genotypes. The field experiment comprising of 69 barley genotypes laid out in a Randomized Block Design with three replications during Rabi 2016-2017. The extent of genetic variability, association between yield and yield components, frequency distribution of 25 top best genotypes in response to yield in three different environments, yield stability analysis and genetic diversity was studied. For stability analysis yield data of current year for one location and yield data of two locations/environments of previous year have been used. Field observations were recorded on six important characters days to 50% flowering, days to maturity, effective tillers per plant, plant height with awn, plant height without awn and 1000 grain weight (g). The result of bi-plot analysis using yield data of three years revealed that AXIS1 explained 57.6 per cent variation while AXIS2 was explained 31.07 per cent variation. Since, genotypes were planted in 2017 in two dates like early and late sown condition hence, there was very slight differences in their yield so both the environments come together (Figure1) as compared to third environment (2018) which for from the two locations of year 2017. Our result indicate that line G69 recommended as most stable genotype for yield potential and stability whereas lines G9, G55, G67 and G68 were consider as superior genotypes.

scholarly journals Yield and photosynthetic attributes of sunflower cultivars grown under supplemental irrigation in the semiarid region of the Brazilian Northeast

2020 ◽  
Vol 55 ◽  
Author(s):  
Luciana Marques de Carvalho ◽  
Hélio Wilson Lemos de Carvalho ◽  
Claudio Guilherme Portela de Carvalho
Keyword(s):  
Photosynthetic Efficiency ◽  
Block Design ◽  
Field Trials ◽  
Photosynthetic Performance ◽  
Oil Yield ◽  
Yield Potential ◽  
Semiarid Region ◽  
Supplementary Irrigation ◽  
Severe Water Deficit ◽  
Brazilian Northeast

Abstract: The objective of this work was to identify the sunflower (Helianthus annuus) cultivar with the highest yield potential for cultivation in the semiarid region of the Brazilian Northeast, under field conditions, with supplementary irrigation. Plant photosynthetic performance and yield were determined in field trials. The experiments were carried out in a randomized complete block design with 12 cultivars planted at 0.70x0.30 m. Net photosynthetic rates above 27 μmol m-2 s-1 and average achene yield of 2,364.68 kg ha-1 and oil yield 961.96 of kg ha-1 were determined. This performance was achieved due to: high stomatal conductance in 'Aguara 4', 'BRS 322', and 'CF101', low water loss through transpiration in 'M 734', 'BRS 321', 'BRS 324', 'BRS 387', and 'Helio 251', or high-intrinsic photosynthetic efficiency in 'Helio 251' and 'BRS 387'. Most cultivars provided grain amounts and oil contents similar to those of cultivars grown in the largest Brazilian producing areas. The cultivars that provide the highest yield in the Brazilian semiarid region, when grown under supplementary irrigation, are 'Aguara 4', 'CF 101', and 'BRS 322' with a high achene and oil yield, and 'M 734' with high achene yield. The less susceptible cultivars to severe water deficit are 'Helio 251' and 'BRS 387' with a high-intrinsic photosynthetic efficiency.

scholarly journals Potensi Kuantitatif dan Kualitatif 10 Galur Unggul Baru Padi Jenis Pandan Wangi

2017 ◽  
Vol 16 (2) ◽  
Author(s):  
Jaenudin Kartahadimaja ◽  
Eka Erlinda Syuriani ◽  
Marlinda Apriyani
Keyword(s):  
Amylose Content ◽  
Block Design ◽  
Yield Potential ◽  
Milled Rice ◽  
Potential Yield ◽  
Yield And Quality ◽  
Honestly Significant Difference ◽  
Significant Difference ◽  
Research Goal ◽  
High Yielding Varieties

Rice is a staple food that is very dominant for Indonesia. Production of rice in 2014 asmany as 70,85 million tons of milled rice, 0,61% lower than production in 2013. Oneway to increase production is the use of high yielding varieties. Polinela have toassemble ten new rice lines Pandan wangi species which have superior appearance.The research goal is to test the potential yield and quality of rice ten new rice strains.The study was conducted in Polinela for 6 months. The study was conducted usingRandomized Completely Block Design ( RCBD ).The treatment consisted of ten strainsof rice, is repeated three times. The variables measured were (1) dry milled grainyield per hectare; (2) the levels of amylose and amylopectin. Qualitative variablesmeasured were the texture and the smell of ricewith organoleptic method. Quantitativedata were analyzed by analysis of variance, if there is a difference between thetreatment continued with Test Honestly Significant Difference (HSD) on the real levelof 0.05. Heritability of quantitative variables were observed calculated to estimatewhether the variable-variable controlled bygenetic factors or environment?The resultsshowed the new rice lines Polinela assemblies have a range of potential outcomes ofmilled rice ( GKG ) between 6.47 to 9.79 tonnes/ha,amylose content is low tomoderate, very fluffier texture until fluffier rice.Keywords: yield potential, new rice strains

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