Dersleri yüzünden oldukça stresli bir ruh haline sikiş hikayeleri bürünüp özel matematik dersinden önce rahatlayabilmek için amatör pornolar kendisini yatak odasına kapatan genç adam telefonundan porno resimleri açtığı porno filmini keyifle seyir ederek yatağını mobil porno okşar ruh dinlendirici olduğunu iddia ettikleri özel sex resim bir masaj salonunda çalışan genç masör hem sağlık hem de huzur sikiş için gelip masaj yaptıracak olan kadını gördüğünde porn nutku tutulur tüm gün boyu seksi lezbiyenleri sikiş dikizleyerek onları en savunmasız anlarında fotoğraflayan azılı erkek lavaboya geçerek fotoğraflara bakıp koca yarağını keyifle okşamaya başlar


Genetic Analysis and Traits Association in F2 Intervarietal Populations in Rice Under Aerobic Condition | OMICS International
ISSN: 2375-4338
Rice Research: Open Access
Make the best use of Scientific Research and information from our 700+ peer reviewed, Open Access Journals that operates with the help of 50,000+ Editorial Board Members and esteemed reviewers and 1000+ Scientific associations in Medical, Clinical, Pharmaceutical, Engineering, Technology and Management Fields.
Meet Inspiring Speakers and Experts at our 3000+ Global Conferenceseries Events with over 600+ Conferences, 1200+ Symposiums and 1200+ Workshops on Medical, Pharma, Engineering, Science, Technology and Business

Genetic Analysis and Traits Association in F2 Intervarietal Populations in Rice Under Aerobic Condition

Farhad Kahani and Shailaja Hittalmani*
Marker Assisted Selection Laboratory, Genetics and Plant Breeding, University of Agricultural Sciences, GKVK, Bangalore 560065, India
Professor and University Head, Genetics and Plant Breeding, University of Agricultural Sciences, GKVK, Bangalore-560065, India
Corresponding Author : Shailaja Hittalmani
Professor and University Head
Genetics and Plant Breeding
University of Agricultural Sciences
GKVK, Bangalore 560065, India
Tel: 91-8023624967
Received October 02, 2015; Accepted October 21, 2015; Published October 25, 2015
Citation: Kahani F, Hittalmani S (2015) Genetic Analysis and Traits Association in F2 Intervarietal Populations in Rice Under Aerobic Condition. J Rice Res 3:152. doi:10.4172/2375-4338.1000152
Copyright: © 2015 Kahani F, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Related article at Pubmed, Scholar Google

Visit for more related articles at Rice Research: Open Access


Genetic variability studies provide basic information concerning the genetic properties of the population based on which breeding methods could be formulated for further improvement of the crop. The estimates of heritability, coefficients of variability and genetic advance was computed in F2 segregating populations of 15 crosses for 14 characters including drought and yield contributing traits under aerobic condition during dry season 2012. The estimates of phenotypic coefficients of variation (PCV) were high and moderate for days between flowering and maturity (10.71%), number of tillers plant (19.70%), number of panicles plant (21.44%), 100 grain weight (g) (27.01%), panicle exertion (14.75%), panicle length (cm) (12.90%), leaf width (cm) (20.96%), straw weight (g) (30.99%) and yield (g) (34.04%)in different crosses. High heritability coupled with high and moderate genetic advance was observed for all the plant traits observed. Correlation studies revealed that Grain yield plant-1 was positively and significantly correlated with number of tillers, number of panicles, grain length and straw weight. However Grain yield plant-1 was negatively significantly correlated with Days to flowering, Days to maturity, Plant Height, 100-grain weight, Grain width and Leaf width

Rice; Aerobic; Genetic variability; Heritability; Genetic advance
Rice is the life and the prince among cereals as this unique grain helps to sustain two thirds of the world’s population. Asia is the biggest rice producer and consumer, accounting for 90 per cent of the world’s production and consumption of rice. Except Antarctica, it is grown in all the continents, occupying 159 million hectare area and producing 683 million tones (equivalent to 456 million tons of milled rice); In Asia, more than 50% of all water used for irrigation is for rice. About 55% of the rice area is irrigated and accounts for 75% of the total rice production in the world. Being an extravagant consumer of water, rice uses around 5000 liters of fresh water to produce 1 kg of rice. The increase in depletion of fresh water resources is a major threat to the traditional way of rice cultivation. Efforts are therefore underway to develop water saving technologies such as alternate wetting and dry continuous soil saturation, irrigation at fixed soil moisture tensions varying from 0 to 40 kPa, or irrigation at an interval of 1-5 days after disappearance of standing water. To combat this problem water-saving rice production system like, aerobic rice cultivation is being popularized to obtain optimum yield with less water consumption. True aerobic rice system (ARS) is a new production system in which rice is grown under non-puddled, non-flooded, and non-saturated soil conditions. Thus in ARS, soils are kept in aerobic situation almost throughout the rice growing season. As already pointed out, ARS aims at growing rice without puddling and flooding under non-saturated soil conditions as other upland crops. The driving force behind ARS is water economy and reported a saving of 73% in land preparation and 56% during crop growth. The work on developing varieties suitable for ARS started only recently and is generally restricted to screening available varieties [3-15].
Moreover before launching any breeding programme, a breeder should have a thorough knowledge on nature and magnitude of genetic variability, heritability, genetic advance, genetic divergence and character association in a crop species. Since yield is inherited in a complex way and is influenced by the environment path coefficient analysis will be an added advantage to the breeder in crop improvement programme. The study on above aspects is essential to identify superior genotypes. The crosses between the genotypes with maximum genetic divergence would be responsible for improvement as they are likely to yield desirable recombinants in the progeny. Keeping in view the genetic studies in aerobic rice were undertaken to estimate the genetic component of variance for yield and yield components involving aerobic cultivars and to compute the heritability, coefficients of variability and genetic advance in F2 segregating populations of the 15 crosses for 14 characters.
Materials and Methods
Crossing, development of f1 and f2 populations
Fifteen F2 populations were generated using di allel mating design of rice by crossing 6parental genotypes viz., Moroberekean, Gandhasala, IR-50, IM-90, IM-114 and OYC-145. Staggered sowing of the selected parental genotypes was done to achieve synchronization in the flowering for effective crossing programme to generate F1. The seedlings were raised during dry season 2011 following all the recommended agronomic practices. At panicle emergence and flowering stage, the florets of female parents were hand emasculated early in the morning, before 7 a.m. and later the pollen was collected from male parent and dusted on to the stigma around 11 a.m which is the ideal time for effective pollination. To avoid contaminations from foreign pollens, emasculated panicle were covered with butter paper packet. The seeds set on female plants were harvested, around 25-27 days after crossing event. Fifteen crosses were effected in a pair wise combination during dry season 2011, at K block, UAS, Bangalore.
Evaluation of F2 generation population
The F2 seeds of all the 15 crosses of rice were directly sown in the field under moisture scarce aerobic situation during dry season-2012 with single seeds per hill at spacing of 25 × 25 cm. On an average of 300 population size for each cross was maintained along with two rows parental lines. Mean values were utilized for statistical analysis and the characters observed for eliciting the information are: days to flowering, days between flowering and maturity, days to maturity, plant height (cm), number of tillers plant, number of Panicles plant-1, productive tillers plant-1, mother panicle weight (g), 100 grain weight (g), panicle length (cm), panicle exertion (± cm), leaf length (cm), leaf width (cm), grain length (mm), grain breadth (mm), straw weight (g) and grain yield plant-1 (g).
Statistical analysis
The observations recorded in respect of all the above quantitative traits were subjected to following standard statistical analysis: Descriptive statistics Sunderaraj et al. (1972), Mean, Range, Standard error, Variance, Skewness and Kurtosis. The mean values of quantitative traits were used to estimate coefficients of skewness and kurtosis using ‘SPSS’ software program, Genetic variability parameters, Coefficients of Variation Burton and, Phenotypic coefficient of variation (PCV), Heritability (h2)Johnson et al., (1955), Genetic advance (GA) [16-18].
GA = K h2 σp
Results and Discussion
Genotypic coefficient of variation, phenotypic coefficient of variation, heritability in narrow sense, genetic advance and genetic advance as percentage of means were estimated for yield and quality in F2 generation as presented in Table1. Expectedly phenotypic coefficient of variation (PCV) was higher than genotypic coefficient of variation (GCV) in all the characters studied. The difference between PCV and GCV is probably due to environmental effects. High heritability estimates for all the characters except panicle excretion and straw weight suggesting that the environmental factors did not affect greatly the phenotypic performance of these traits. Highest PCV (34.04%) and GCV (33.58%) were observed for grain yield plant-1. PCV generally ranged between 2.67% for grain width to 34.04 % for grain yield plant-1. Similarly, GCV ranged between 2.12% for grain width to 33.58% for grain yield plant-1. A similar finding of higher PCV than GCV was also reported by [2,10,15]. Generally, heritability in broad sense estimate varied from 19.67% for panicle exertion and 99.95% for leaf width, respectively. Similarly, genetic advance was ranged between 0.16% for panicle excretion and 21.36% for plant height. A joint consideration of GCV, heritability broad sense and genetic advance revealed that 100-grain weight (27.01, 99.20 and 16.18%), leaf width (20.96, 99.95 and 11.46%) and grain yield plant-1 (33.58, 96.12 and 16.04%) combined high GCV, high heritability broad sense and moderate genetic advance. Thus, high estimates of GCV and heritability could be good predictors of seed yield in rice. Hence selection based on the phenotypic performance will be reliable and effective. Furthermore, moderate to high heritability, GCV and GA% in a mean could be explained by additive gene action and their improvement could be achieved through mass selection [19-21] (Table 1).
Correlation studies revealed that Grain yield plant-1 was positively significantly correlated with number of tillers, number of panicles, grain length and straw weight. These results suggest that selection to improve rice yield directed by phenotype of these traits may be effective [20]. However Grain yield plant-1 was negatively significantly correlated with days to flowering, days to flowering, days to maturity, plant height, 100-grain weight, grain width and leaf width. Similar findings were also recorded by [22] for days to flowering (Table 2).
The path analysis is a useful parameter to understand more clearly the association among different variables as recorded by simple correlation values. It helps to partition the overall association of particular variables with dependent variable into direct and indirect effects. While dealing with a more complex character like grain yield, it enables the breeder to specifically identify the important component trait of such a nature and differential emphasis can be laid on those characters for selection. Table 3 shows the results of the path analysis for the examined traits. Path coefficient analysis of yield and its component traits revealed that Straw weight (0.42) had the highest positive direct effect on grain yield. The Number of tillers plant-1(0.30) was the second most important character
it showed highest positive direct effect on grain yield [23] reported that indirect selection based on number of productive tillers per plant, harvest index and biomass per plant can be adopted for enhancement of grain yield as it showed positive direct effect on grain yield per plant. The number of tillers plant-1 had negative indirect effect on grain yield via number of panicles (-0.22), similar results were also reported by [24,25]. The traits that have direct affect on grain help to select them directly to enhance the yield. The lower residual effect indicated that different characters other than the characters considered in this study influence the grain yield considerably (Table 3 and Figure 1).
An overall consideration of the results revealed that grain yield plant-1 could be improved through selection for traits number of tillers, number of panicles, grain length and straw weight which were positively correlated with grain yield plant-1. High heritability estimates for all the characters except for panicle excretion and straw weight revealed that selection for these characters will have to be carried in advance segregating generations.
We express the opportunity to thank various funding agencies including DBT, New Delhi, NICRA, Hyderabad, India for carrying this work at University of Agricultural Sciences, GKVK, Bangalore, India.



Tables and Figures at a glance

Table icon Table icon Table icon
Table 1 Table 2 Table 3


Figures at a glance

Figure 1
Post your comment

Share This Article

Article Usage

  • Total views: 15082
  • [From(publication date):
    November-2015 - Dec 09, 2023]
  • Breakdown by view type
  • HTML page views : 10286
  • PDF downloads : 4796