scholarly journals Yield stability of rapeseed genotypes under drought stress conditions

2019 ◽  
Vol 79 (01) ◽  
Author(s):  
Mehdipour Sara ◽  
Rezaeizad Abbas ◽  
Azizinezhad Reza ◽  
Etminan Alireza
Keyword(s):  
Genotype X Environment ◽  
Genotype By Environment ◽  
Biplot Analysis ◽  
Gxe Interaction ◽  
Cropping Season ◽  
Moisture Regimes ◽  
Ammi Model ◽  
Gxe Interactions ◽  
Cropping Seasons ◽  
Poor Stability

Genotype by Environment (GxE) interactions of 29 rapeseed genotypes in normal irrigation and irrigation cut off from flowering and silique formation stages have been worked out from the data recorded during three cropping seasons. Combined variance analysis showed a significant variation for year (cropping season), moisture regimes, genotype, genotype x moisture regimes and genotype x year interactions. Results of AMMI model analysis showed that three first genotype x environment principal components (PC) were significant at 1% level of probability and fourth PC at 5% level. These four components explained 35.6, 24.4, 18.4 and 14.8 per cent of the GxE sum of squares, respectively. According to AMMI2 biplot analysis, genotypes such as L155, Neptune, Elvise, Jerry, GkGabriella, Sw102, GKH0224, Julius, GKH3705 and Sarigol were positioned in the center of the biplot so had the least GxE interaction and showed the most general compatibility. Based on simultaneous selection, winter type of genotypes namely, GKH2624, SW102, HW118, GKH3705, Wpn6 and L72 were identified as high yielding and stable whereas, spring genotypes namely, Zabol10, Dalgan, Jerome and Hyola4815 were identified as low yielding with poor stability.

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

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 Wheat genotypes evaluated for GxE interactions in Central Zone of the country by AMMI analysis

2021 ◽  
Vol 23 (3) ◽  
pp. 341-345
Author(s):  
AJAY VERMA ◽  
Keyword(s):  
Principal Components ◽  
Central Zone ◽  
Sum Of Squares ◽  
First Year ◽  
Wheat Genotypes ◽  
Biplot Analysis ◽  
Gxe Interaction ◽  
Ammi Analysis ◽  
Gxe Interactions ◽  
Second Year

Highly significant effects of environments, GxE interaction and genotypes were observed for cropping years 2017-18 and 2018-19. Further analysis of interactions sum of squares bifurcated into seven significant multiplicative interactions principal components to assess the performances of genotypes as per AMMI based measures. For the first year of study wheat genotypes (G5, G6, G7) had top ranked by EV2, D2, ASV, ASV1 and ASTAB2 measures. MASV & MASV1 pointed towards G7, G8, G6 wheat genotypes. Association among these measures displayed graphically in a biplot analysis. Largest cluster comprised of D2, D3, D5, D7, ASV, ASV1, ASTAB2, EV2, EV3, EV5, ASTAB3, ASTAB5, ASTAB7 measures. Wheat genotypes (G1, G11, G3) pointed by EV2, D2, ASV, ASV1 and ASTAB2 values for the second year. MASV settled for G11, G7, G13 whereas MASV1 pointed towards G11, G7, G2. Biplot analysis based on first two PC’s observed largest group had clubbed measures D2, ASV, ASTAB2, EV5, MASV, MASV1, EV3, D3, D5, D7, EV7, ASTAB3 ASTAB5, ASTAB7. AMMI based measures would be useful to identify and recommend genotypes with high, stable and predictable yield across environments.

scholarly journals Assessing the effects of genotype-by-environment interaction on epigenetic, transcriptomic, and phenotypic response in a Pacific salmon

2021 ◽  
Author(s):  
Kris A Christensen ◽  
Jérémy Le Luyer ◽  
Michelle T T Chan ◽  
Eric B Rondeau ◽  
Ben F Koop ◽  
...  
Keyword(s):  
Growth Rate ◽  
Liver Tissue ◽  
Coho Salmon ◽  
Pacific Salmon ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Gxe Interaction ◽  
Differentially Methylated Genes ◽  
Gxe Interactions ◽  
Term Analysis

Abstract Genotype-by-environment (GxE) interactions are non-parallel reaction norms among individuals with different genotypes in response to different environmental conditions. GxE interactions are an extension of phenotypic plasticity and consequently studying such interactions improves our ability to predict effects of different environments on phenotype as well as the fitness of genetically distinct organisms and their capacity to interact with ecosystems. Growth hormone transgenic coho salmon grow much faster than non-transgenics when raised in tank environments, but show little difference in growth when reared in nature-like streams. We used this model system to evaluate potential mechanisms underlying this growth rate GxE interaction, performing RNA-seq to measure gene transcription and whole-genome bisulfite sequencing to measure gene methylation in liver tissue. Gene ontology (GO) term analysis revealed stress as an important biological process potentially influencing growth rate GxE interactions. While few genes with transcription differences also had methylation differences, in promoter or gene regions, many genes were differentially methylated between tank and stream environments. A GO term analysis of differentially methylated genes between tank and stream environments revealed increased methylation in the stream environment of more than 95% of the differentially methylated genes, many with biological processes unrelated to liver function. The lower nutritional condition of the stream environment may cause increased negative regulation of genes less vital for liver tissue function than when fish are reared in tanks with unlimited food availability. These data show a large effect of rearing environment both on gene expression and methylation, but it is less clear that the detected epigenetic marks are responsible for the observed altered growth and physiological responses.

scholarly journals Genotype x Environment interaction, stability, and adaptability in progenies of Eucalyptus urophylla S.T. BLAKE using the AMMI model

2018 ◽  
Vol 67 (1) ◽  
pp. 51-56 ◽  
Author(s):  
S. Pupin ◽  
P. H. M. Silva ◽  
F. A. Piotto ◽  
A. C. Miranda ◽  
D. U. G. Zaruma ◽  
...  
Keyword(s):  
Experimental Design ◽  
Environment Interaction ◽  
Eucalyptus Urophylla ◽  
Genotype X Environment ◽  
Breast Height ◽  
Gxe Interaction ◽  
Geographical Regions ◽  
Ammi Model ◽  
Progeny Tests ◽  
Environmental Stratification

AbstractOne of the determinant factors in the success of breeding pro­grams that aim to select genotypes for different geographical regions is understanding the interaction between genotypes and environments (GxE). The objectives of this study were to evaluate GxE interaction, stability, and adaptability, and deter­mine the need for environmental stratification of open pollina­ted progenies of Eucalyptus urophylla. Five progeny tests were established in study areas with different environmental condi­tions in southeast and mid-west Brazil. We used a complete randomized block experimental design with 138 to 167 proge­nies, and variations in the numbers of replicates and plants per plot. The trait measured was diameter at breast height (DBH) at two years of age and the AMMI method was used to determine patterns of GxE interaction. Significant effects were detected for genotypes, environments, and for GxE interaction. The effect of environment was responsible for the greatest propor­tion of the phenotypic variation, followed by the effect of genotypes and GxE interaction. Some progenies with greater productivity and stability were identified, although stability is not associated with productivity. The stratification of the selec­tion in three specific environments is necessary due to the occurrence of a complex GxE interaction.

Lowland Rice Yield as Affected by Straw Incorporation and Inorganic Fertilizer Over Cropping Seasons in Fluvisol

2014 ◽  
Vol 3 (1) ◽  
pp. 129-141
Author(s):  
Brahima Koné ◽  
Zadi Florent ◽  
Gala bi Trazié Jeremie ◽  
Akassimadou Edja Fulgence ◽  
Konan Kouamé Firmin ◽  
...  
Keyword(s):  
Grain Yield ◽  
Rice Variety ◽  
Mineral Fertilizer ◽  
Lowland Rice ◽  
Inorganic Fertilizer ◽  
Cropping Season ◽  
Significant Difference ◽  
Straw Incorporation ◽  
Cropping Seasons ◽  
Fertilizer Effect

Grain yield stabilization of lowland rice over cropping seasons was explored using different compositions of inorganic fertilizers (NPK, NPKCa, NPKMg, NPKZn, NPKCaMg, NPKCaZn and NPKCaMgZn) and straw incorporation (3, 6, 9, 12 and 15 tha-1 ). No fertilizer and no straw amended plot was the control in a split-plot design with three replications laid in a Fluvisol of Guinea savanna in Centre Cote d’Ivoire. Three weeks old nursery rice variety NERICA L19 was transplanted. No significant difference of grain yield was observed between the different treatments excluding the highest yields recorded for treatments NPKMg (5.09 tha-1 ), NPKZn (5.15 tha-1 ) and NPKCaéMg (5.31 tha-1 ) compared with 12 (3.95 tha1 ) and 15 tha-1 (4.14 tha-1 ) as straw rates respectively. Grain yield declining trend was more pronounced for mineral fertilizer treatments showing twice greater depressive effect of cropping cycle compared with the straw especially, for treatments characterized by highest grain yield in the first cropping season and similar grain yields were recorded for both sources of nutrient in the third cropping cycle. Of slowness of nutrients releasing by straw, highest grain yield was expected for this soil amender within a longer period of cultivation whereas, unbalance soil micronutrients should be relevant to studious declining yield under inorganic fertilizer effect. Nevertheless, the straw rate of 12 tha-1 supplying 0.58% of NPK as mineral fertilizer equivalent can be recommended for sustaining lowland rice production in the studied agro-ecosystems unless for three cropping seasons.

Using AMMI approach to delineate genotype by environment interaction and stability of barley (Hordeum vulgare L.) genotypes under northern Indian shivalik hill conditions

2020 ◽  
Vol 80 (03) ◽  
Author(s):  
Om Prakash Yadav ◽  
A. K. Razdan ◽  
Bupesh Kumar ◽  
Praveen Singh ◽  
Anjani K. Singh
Keyword(s):  
Hordeum Vulgare ◽  
Grain Yield ◽  
Principal Component ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Hordeum Vulgare L ◽  
Genotype By Environment ◽  
Biplot Analysis ◽  
Principal Component Axis ◽  
Ammi Analysis

Genotype by environment interaction (GEI) of 18 barley varieties was assessed during two successive rabi crop seasons so as to identify high yielding and stable barley varieties. AMMI analysis showed that genotypes (G), environment (E) and GEI accounted for 1672.35, 78.25 and 20.51 of total variance, respectively. Partitioning of sum of squares due to GEI revealed significance of interaction principal component axis IPCA1 only On the basis of AMMI biplot analysis DWRB 137 (41.03qha–1), RD 2715 (32.54qha–1), BH 902 (37.53qha–1) and RD 2907 (33.29qha–1) exhibited grain yield superiority of 64.45, 30.42, 50.42 and 33.42 per cent, respectively over farmers’ recycled variety (24.43qha–1).

scholarly journals Seed Yam Production Using High-Quality Minitubers Derived from Plants Established with Vine Cuttings

Agronomy ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 978
Author(s):  
Beatrice Aighewi ◽  
Norbert Maroya ◽  
Lava Kumar ◽  
Morufat Balogun ◽  
Daniel Aihebhoria ◽  
...  
Keyword(s):  
Block Design ◽  
Research Station ◽  
International Institute ◽  
Tropical Agriculture ◽  
Single Node ◽  
Cropping Season ◽  
Randomized Complete Block Design ◽  
The World ◽  
Cropping Seasons ◽  
Set Up

Yam (Dioscorea spp.) is a valuable food security crop in West Africa, where 92% of the world production occurs. The availability of quality seed tubers for increased productivity is a major challenge. In this study, minitubers weighing 1, 3, and 5 g produced from virus-free single-node vine cuttings of two improved yam varieties (Asiedu and Kpamyo) growing in an aeroponics system were assessed for suitability in seed production at a population of 100,000 plants ha−1. A 3 × 2 factorial experiment with randomized complete block design and three replications was set up during the cropping seasons of 2017 to 2019 at the International Institute of Tropical Agriculture Research Station in Kubwa, Abuja, Nigeria. Results showed field establishments of 87%–97.8%. Yields differed with minituber size, variety, and cropping season; the highest was 31.2 t ha−1 in 2019 and the lowest, 10 t ha−1 in 2018 from 5 and 1 g Kpamyo minitubers, respectively. The estimated number of tubers produced per hectare by 1, 3, and 5 g minitubers was 101,296, 112,592, and 130,555, with mean weights per stand of 159.2, 187.3, and 249.4 g, respectively. We recommend using less than 6 g minitubers for seed yam production due to their high multiplication rates.

scholarly journals GROWTH DYNAMICS OF SESAME CULTIVARS

2018 ◽  
Vol 31 (4) ◽  
pp. 1062-1068
Author(s):  
Rayanne Maria Paula Ribeiro ◽  
José Ricardo Tavares de Albuquerque ◽  
Manoel Galdino dos Santos ◽  
Aurélio Paes Barros Júnior ◽  
Leilson Costa Grangeiro ◽  
...  
Keyword(s):  
Block Design ◽  
Growth Dynamics ◽  
Plant Performance ◽  
Physiological Processes ◽  
Cropping Season ◽  
Physiological Indexes ◽  
Crop Cycle ◽  
Beginning Of Flowering ◽  
Cropping Seasons ◽  
Physiological Complexity

ABSTRACT Sesame is a plant with high morphological and physiological complexity, with great variability in growth habit. Quantitative growth analysis is an accessible and accurate tool for evaluating plant development and the contribution of different physiological processes to plant performance. In view of this, the purpose of this study was to evaluate the growth of sesame cultivars in two cropping seasons in the conditions of Mossoró-RN. Two experiments were conducted in Horta Didactics of UFERSA. The experimental delineation in each time was a randomized complete block design with four replications. The treatments were arranged in split plots where each experimental plot contained different sesame cultivars, CNPA G2, CNPA G3 and CNPA G4, and the subplots represented seven collection times, 21, 35, 49, 63, 77, 91 and 105 days after sowing (DAS). The growth of the sesame cultivars was slow at the beginning of the crop cycle, intensifying at the beginning of flowering (after 35 DAS). Among the physiological indexes studied, CNPA G4 cultivar was more efficient in relation to growth and varied depending on the cropping season.

scholarly journals Hill drop sowing of soybean with different number of plants per hole

2018 ◽  
Vol 48 (5) ◽  
Author(s):  
Esmael Lopes dos Santos ◽  
Victor José Agassi ◽  
Alessandro Sartor Chicowski ◽  
Julio Cezar Franchini ◽  
Henrique Debiasi ◽  
...  
Keyword(s):  
Plant Density ◽  
Block Design ◽  
Agronomic Performance ◽  
Soybean Cultivars ◽  
Lack Of Information ◽  
Cropping Season ◽  
Randomized Complete Block Design ◽  
Cropping Seasons

ABSTRACT: In the last few cropping seasons, some soybean producers have tested the application of a hill drop sowing method, usually from three to four seeds every 30 to 40cm. However, there is a lack of information in the literature about the effect of this practice on soybean performance. Thus, the objective of this study was to evaluate the effect of a hill drop sowing with different number of plants per hole on soybean performance. The study was conducted in Londrina - PR, Brazil, during the 2013/14, 2014/15 and 2016/17 cropping seasons. The experiment was a randomized complete block design with four replications and a 2x5 factorial scheme. The first factor consisted of two soybean cultivars, BRS 359RR and NK 7059RR analyzed in the first two cropping seasons and BRS 359RR and BRS 1010IPRO in the last cropping season. The second factor was constituted by five in-hill hole-spacing treatments (HS) (8, 16, 24, 32 and 40cm), with rows spaced 50cm apart. To maintain the same plant density in all treatments (270,000 plants ha-1), sowing was performed manually, being then thinned out. After thinning, the distribution was one plant per hole at HS8, 2 plants at HS16, 3 plants at HS24, 4 plants at HS32, and 5 plants at HS40. The agronomic performance of soybean in hill drop sowing with different number of plants per hole is similar to that of an equidistant distribution of plants.

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