Refine your search
Co-Authors
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Nandini, C.
- Genetic Variability, Heritability, Genetic Advance and Character Association Studies in F3 Generation of Cross JK8 X Peddasame (Purple Late) in Little Millet (Panicum miliare L.)
Abstract Views :330 |
PDF Views:3
Authors
Affiliations
1 University of Agricultural Sciences, G.K.V.K., Bengaluru (Karnataka), IN
1 University of Agricultural Sciences, G.K.V.K., Bengaluru (Karnataka), IN
Source
Asian Journal of Bio Science, Vol 11, No 2 (2016), Pagination: 244-249Abstract
Genetic variability, correlation and path analysis was carried out for yield and yield components in 542 F3 progeny lines developed by crossing JK8 x Peddasame (purple late) in little millet during Kharif 2015. Seven biometrical characters were studied for estimating genotypic co-efficient of variation (GCV), phenotypic co-efficient of variation (PCV), genetic advance, heritability (broad sense), genetic advance as per cent of mean, correlation co-efficient and path co-efficient among themselves. High GCV and PCV were observed for number of productive tillers per plant and per plant yield. High heritability was observed for plant height and 1000 seed weight. Number of productive tillers per plant showed maximum genetic advance as per cent of mean followed by grain yield per plant, panicle length and plant height. High heritability coupled with moderate genetic advance as per cent of mean were observed for plant height and 1000 seed weight. Grain yield per plant possessed significant positive correlation with plant height, panicle length, number of productive tillers per plant and 1000 seed weight. Number of productive tillers per plant imparted maximum direct effect on grain yield followed by panicle length, 1000 seed weight and plant height.Keywords
Correlation, Genetic Advance, Genotypic Co-Efficient of Variability, Heritability, Path Analysis, Phenotypic Co-Efficient of Variability.
References
- Allard, R.W. (1960). Principles of plant breeding. John Wiley and Sons Inc., U.S.A.
- Bharadwaj, C.H., Mishra, R., Satyavathi, T., Rao, S.R. and Kumar, K. S. (2007). Genetic variability heritability and genetic advance in some new plant type based crosses of rice (Oryza sativa L.). Indian J. Agric. Res., 41(3): 189-194.
- Burton, G.W. (1952). Quantitative inheritance in grasses. In: Proc. of the 6th International Grassland Congress, pp. 277-283.
- Dewey D.R. and Lu, K. H. (1959). A correlation and path co-efficient analysis of components of crested wheatgrass seed production. Agron. J., 51: 515-518.
- Gowda, M.V.C., Prabhu, T.G. and Bhat, R.S. (1996). Variability and association of late leaf spot resitance and productivity in two crosses of groundnuts. Crop. Improv., 23 (1) : 44-48.
- Idris, A.E., Justin, F.J., Dagash, Y.M.I. and Abuali, A.I. (2012). Genetic variability and inter relationship between yield and yield components in some rice genotypes. American. J. Exp. Agric., 2 (2): 233-239.
- John, K.,Vasanthi, R.P. and Venkateswarlu, O. (2007). Variability and correlation studies for pod yield and its attributes in F2 generation of six Virginia x Spanish crosses of groundnut (Arachis hypogaea L.). Leg. Res., 30 (4) : 292-296.
- Johnson, H.W., Robinson, H.F. and Comstock, R.E. (1955). Estimates of genetic and environmental variability in soybean.Agron. J., 47: 314-318.
- Khan, A.H., Mahmood, T. and Shah, S. A. (1992). Path co-efficient analysis of morphological parameters with seed yield in Raya. Pak. J. Agric. Res., 3 : 334-337.
- Lush, J. L. (1940). Intra – sire correlation and regression of offspring on dams as a method of estimating heritability of characters. In: Proc. of American Soc. of Animal Prod., 33: 293 – 301.
- Miller, P.A., Williams, C. H. F., Robinson and Comstock, R. E. (1958). Estimates of genotypic and environmental variances and co-variances in upland cotton and their implications in selection. Agron. J., 50 : 126 -131.
- Mohammadia, S.A., Prasanna, B. M. and Singh, N. N. (2003). Sequential path model for determining interrelationship among grain yield and related characters in maize. Crop Sci., 43 : 1690-1697.
- Nandini, B., Ravishankar, C. R., Mahesha, B., Shailaja, H. and Kalyana, M. K. N. (2010). Study of correlation and path analysis in F2 population of finger millet. Int. J. Plant Sci., 5 (2) : 602-605.
- Nirmalakumari, A.K. Salini and Veerabadhiran, P. (2010). Morphological characterization and evaluation of little millet (Panicum sumatrense Roth. ex. Roem. and Schultz.) Germplasm. Electronic. J. Pl. Breed.,1(2): 148 - 155.
- Panse, V. G. (1957). Genetics of quantitive characters in relation to plant breeding. Indian J. Genetic. Pl. Breed., 17: 318-328.
- Parameshwarappa, K.G. and Girish, K.B. (2007). Genetic analysis of pod yield and other confectionary traits in large seeded groundnut (Arachis hypogaea L.). J. Oilseeds Res., 24 (3) : 237-240.
- Rafiq, C.M., Rafique, M., Hussian, A. and Altaf, M. (2010). Studies on heritability, correlation and path analysis in maize (Zea mays L.). J. Agric. Res., 48 : 35-38.
- Reddy, P.A.V., Sekar, M.R., Ranganatha, A.R.G. and Dhanraj, A. (2001). Genetic variability and heritability for seed yield and its components in sesame (Sesamum indicum L.). J. Oilseeds Res., 18 (2) : 173-175.
- Sharathbabu, K.S., Shantakumar, G. and Salimath, P. M. (2008). Genetic variability and character association in white ragi (Eleusine coracana Gaertn). Karnataka J. Agric. Sci., 21 (4) : 572-575.
- Stansfield, W.D. (1986). Theory and problems of genetics. M. C. Grow Hill Book Co. New York USA. pp. 220-221.
- Vetriventhan, M. and Nirmalakumari, A. (2007). Studies on variability parameters in pearl millet [Pennisetum glaucum (L.) R. Br.]. Madras Agric. J. 94: 118-120.
- Estimation of Gene Actions and Character Association in F3 and F4 Generations of Little Millet Cross JK 8 X Peddasame Purple Early (Panicum miliare)
Abstract Views :276 |
PDF Views:0
Authors
Affiliations
1 Project Coordinating Unit, Small Millets (U.A.S.) G.K.V.K., Bengaluru (Karnataka), IN
1 Project Coordinating Unit, Small Millets (U.A.S.) G.K.V.K., Bengaluru (Karnataka), IN
Source
International Journal of Agricultural Sciences, Vol 13, No 1 (2017), Pagination: 119-123Abstract
An investigation was carried out in F3 and F4 segregating generations of little millet to study gene interactions and correlation for yield and its component traits during Kharif 2015 and summer 2016 at UAS, GKVK, Bengaluru. Most of the characters studied were positively skewed and were being governed by several genes indicating quantitative inheritance. Characters seed yield per plant, number of productive tillers per plant and days to maturity were positively skewed indicating complementary gene action hence, to maximize the genetic gain in these characters require intense selection from the existing variability. Panicle length showed negatively skewed distribution indicating duplicate gene action hence, genetic gain will be rapid under mild selection. Seed yield and associated characters showed leptokurtic distribution indicated the involvement of few genes in inheritance of these traits. Seed yield per plant had significant positive association with days to 50 per cent flowering, plant height, number of productive tillers per plant, panicle length and days to maturity. This indicates that selection could be practiced for these component characters to increase seed yield. Variance for majority of the characters has decreased in F4 over F3 generation indicated over the generation variability in population has decreased due to increase in homozygosity.Keywords
Correlation, Skewness, Kurtosis, Gene Interaction, Little Millet.References
- Ajay, B. C., Byregowda, M., Veerakumar, G. N., Ganapathy, K. N., Meena, M., Prashanth, Babu H. and Renna, M. (2016). Genetic association and frequency distribution in segregating generations derived from pigeonpea crosses. Indian J. Genet., 76 (2):181-186.
- Choo, T. M. and Reinbergs, E. (1982). Analysis of skewness and kurtosis for detecting gene interaction in a double haploid population. Crop Sci., 22: 231-235.
- Fisher, R.A., Immer, F. A. and Tedin, O. (1932).The genetical interpretation of statistics of the third degree in the study of quantitative inheritance. Genetics, 17:107-124.
- Fisher, R. A. (1950). Statistical methods for research workers. 11th Ed., Oliver and Bond, LONDON, UNITED KINGDOM.
- Goulden, C. H. (1939). Methods of statistical analysis. John Wiley and Sons, NEWYORK, U.S.A.
- Hammer, O., Harper, D. A. T. and Ryan, P. D. (2001). PAST: Paleontological statistics software package for education and data analysis. Palaeontologia Electronica, 4 : article 4 9pp.
- Kotch, G. P., Ortiz and Ross, W. M. (1992). Genetic analysis by use of potato haploid populations. Genome., 35: 103-108.
- Nandini B., Ravishankar, C. R., Mahesha, B., Shailaja, H. and Kalyana, M. K.N. (2010). Study of correlation and path analysis in F2 population of finger millet. Internat. J. Plant Sci., 5 (2): 602 - 605.
- Pooni, H. S., Jinks, J. L. and Cornish (1977). The causes and consequences of non-normality in predicting the properties of recombinant inbred lines. Heridity, 38: 329-338.
- Preetha, S. and Raveendren, T.S. (2008). Genetic appraisal of yield and fibre quality traits in cotton using interspecific F2, F3 and F4 populations. Internat. J. Integr. Biol., 3 : 136-142.
- Robson, D. S. (1956). Application of K4 statistics to genetic variance component analysis. Biometrics, 12:433-444.
- Roy, D. (2000). Plant breeding-the analysis and exploitation of variability. Narosa Publishing House, NEW DELHI, INDIA.
- Samak, A.N.R., Hittalamani, S., Shashidhar, N. and Hanumareddy, B. (2011). Exploratory studies on genetic variability and genetic control for protein and micronutrient content in F4 and F5 generations of rice (Oryza sativa L.). Asian J. Plant Sci., 10: 376-379.
- Sharathbabu, K.S., Shantakumar, G. and Salimath, P. M. (2008). Genetic variability and character association in white ragi (Eleusine coracana Gaertn). Karnataka J. Agric. Sci., 21(4): 572-575.
- Snedecor, G. W. and Cochron, W. G. (1967). Statistical methods. 6th Ed., Oxford and IBH Publishing Co. Pvt. Ltd., New Delhi, India, pp. 553.
- Sulistyowati, Y., Trikoesoemaning,Tyas, Sopandie, D., Ardie, S. W and Nugroho, S. (2015).Estimation of genetic parameters and gene actions of sorghum [Sorghum bicolor (L.) Moench] tolerance to low P condition. Internat. J. Agric. & Agric. Res., 7 (3) : 38-46.
- Zhang, G. and Zhou, W. (2006). Selection intensity and progress in improving population performance may be greater under complementary interaction than under duplicate interaction. J. Genetics, 85: 45-51.
- Character Association and Path Analysis in F8 Recombinant Inbred Line Population of the Cross NRCG 12568 × NRCG 12326 in Groundnut (Arachis hypogea L.)
Abstract Views :186 |
PDF Views:0
Authors
Affiliations
1 Department of Genetics and Plant Breeding, University of Agricultural Sciences, G.K.V.K., Bengaluru (Karnataka), IN
1 Department of Genetics and Plant Breeding, University of Agricultural Sciences, G.K.V.K., Bengaluru (Karnataka), IN
Source
Asian Journal of Bio Science, Vol 7, No 1 (2012), Pagination: 55-58Abstract
The present study was undertaken to study the correlation and path association for ten growth and physiological traits related to water use efficiency in groundnut during Kharif 2010. The base material comprised of 196 F8 recombinant inbred line population developed by crossing NRCG 12568 and NRCG 12326 through single seed descent method. Genotype NRCG 12568 and NRCG 12326 are diverse for trait Carbon Isotopic Discrimination. The studies on Phenotypic and genotypic correlation coefficients revealed that pod yield per plant had strong positive correlation with pods per plant, kernel yield per plant, sound mature kernel percentage indicating that improvement in these characters will lead to improvement in yield. Whereas significant negative association was observed for pod yield per plant with days to fifty per cent flowering and shelling percentage. Among these characters kernel yield per plant recorded maximum direct effect on pod yield per plant whereas all other characters recorded low direct effects. Sound mature kernel percentage, pods per plant and SLA recorded maximum indirect effect on pod yield plant through kernel yield per plant. The results of the study revealed that the character kernel yield per plant and specific leaf area could be given emphasis for selection of genotypes with high yield coupled with high water use efficiency.Keywords
Correlation, Path Analysis, Carbon Isotopic Discrimination, Water Use Efficiency, Direct and Indirect Effects.- Genetic Analysis of Heterosis for Seed Yield and its Components in Sunflower (Helianthus annuus L.)
Abstract Views :184 |
PDF Views:0
Authors
B. K. Athoni
1,
C. Nandini
2
Affiliations
1 All India Co-Ordinated Research Project on Sunflower, Zonal Agricultural Research Station, U.A.S., G.K.V.K., Bengaluru (Karnataka), IN
2 Department of Genetics and Plant Breeding, University of Agricultural Sciences, G.K.V.K., Bengaluru (Karnataka), IN
1 All India Co-Ordinated Research Project on Sunflower, Zonal Agricultural Research Station, U.A.S., G.K.V.K., Bengaluru (Karnataka), IN
2 Department of Genetics and Plant Breeding, University of Agricultural Sciences, G.K.V.K., Bengaluru (Karnataka), IN
Source
Asian Journal of Bio Science, Vol 7, No 1 (2012), Pagination: 77-83Abstract
A study was undertaken to assess the magnitude of heterosis involving seventeen inbred lines of sunflower. The inbred comprised of five new male sterile lines and twelve diverse restorer lines (six branching and six non-branching) which were crossed in all possible combinations. The resulting 60 F1 hybrids along with their parents were studied for the extent of heterosis during summer 2006 for nine characters by adopting line × tester analysis, considerable average heterosis was observed for all characters studied. Highest magnitude of average heterosis was observed for seed yield per plot (150.34) followed by seed yield per plant (118.86), head diameter (26.79), plant height (15.32), thousand seed weight (7.49) and oil content (2.13) for the characters days to 50 per cent flowering, the hybrids recorded negative average heterosis. Percentage contribution of component characters, viz., thousand seed weight, plant height and head diameter towards expression of heterotic effect for seed yield was to the extent of 15.06, 30.82 and 53.86 per cent, respectively.Keywords
Heterosis, Sunflower, Inbred Lines, Line × Tester Analysis.- Performance of Branching and Non-Branching Restorer Lines in Producing Heterotic Hybrids of Sunflower (Helianthus annuus L.)
Abstract Views :162 |
PDF Views:0
Authors
B. K. Athoni
1,
C. Nandini
1
Affiliations
1 All India Co-ordinated Project on Sunflower, University of Agricultural Sciences, G.K.V.K., Bengaluru (Karnataka), IN
1 All India Co-ordinated Project on Sunflower, University of Agricultural Sciences, G.K.V.K., Bengaluru (Karnataka), IN
Source
Asian Journal of Bio Science, Vol 7, No 1 (2012), Pagination: 101-105Abstract
To know the performance of branching and non branching restorer lines of sunflower in producing high yielding and high oil content hybrids, a study was undertaken at University of Agricultural Sciences, Dharwad to assess the magnitude of heterosis involving seventeen inbred lines of sunflower. The inbred comprised of five new male sterile lines and twelve diverse restorer lines (six branching and six non-branching) which were crossed in all possible combinations during Kharif-2005. The resulting 60 F1 hybrids along with their parents were studied for the extent of Heterosis during Summer 2006 for nine characters by adopting line × tester analysis, considerable average heterosis was observed for all characters studied. Highest magnitude of average heterosis was observed for seed yield per plot (150.34) followed by seed yield per plant (118.86), head diameter (26.79), plant height (15.32), thousand seed weight (7.49) and oil content (2.13) for the characters days to 50 per cent flowering, the hybrids recorded negative average heterosis. Percentage contribution of component characters, viz., thousand seed weight, plant height and head diameter towards expression of heterotic effect for seed yield was to the extent of 15.06, 30.82 and 53.86 per cent, respectively.Keywords
Heterosis, Sunflower, Branching, Non Branching, Line × Tester Analysis.- Effects of Habitual Physical Activity Level (PAL) on Simple Visual and Auditory Reaction Time in Healthy Indian Adults
Abstract Views :607 |
PDF Views:0
Authors
Affiliations
1 East Point College of Medical sciences and Research Centre, Bangalore, Karnataka, IN
1 East Point College of Medical sciences and Research Centre, Bangalore, Karnataka, IN
Source
International Journal of Physiology, Vol 8, No 1 (2020), Pagination: 142-147Abstract
Aim To find the correlation between physical activity level(PAL) and simple visual and auditory reaction time(SVRT and SART), which are tests for cognition .
Material and Method: One hundred(100) healthy volunteers of both the genders(males 52 and females 48), aged between 18 and 50 years were recruited. Reaction time (RT), is defined the elapsed time between the presentation of a stimulus and the subsequent behavioral response to occur. Subjects were presented with red light for VRT and pure tone sound stimuli for ART. Reaction time is a measure of the coordination between the sensory and motor system occurs. The physical activity level (PAL) was determined by administering a physical activity level questionnaire developed by the Division of Nutrition, St. John’s Medical College, Bangalore. The PAL of an individual classified as follows: sedentary<1.4 moderately active 1.55 to 1.75, and heavily active .1.75.
Result: Statistical analysis of data was done by one-way ANOVA with Post-hoc by Turkey HSD test. The results were found to be significant. There is a negative correlation between the SVRT and PAL with R2 value of 0.006; SART and PAL with R2 value of 0.001 .
Conclusion: In this study we observed that when there is increase in the PAL, there is significantly faster ART and VRT. Therefore, more physically active individuals have better reaction times and are more coordinated at motor tasks when compared to less physically active.
Keywords
BMI( Body Mass Index), Auditory Reaction Time(ART), Visual Reaction Time(VRT), PAL(Physical Activity Level).References
- Mondal S, Van Belle S India’s NCD strategy in the SDG era: are there early signs of a paradigm shift? Global Health. 2018 Apr 25;14(1):39. doi: 10.1186/s12992-018-0357-6.
- Bharti AV, Sandhya N, V az M The development and characteristics of physical activity level questionnaire for epidemiological studies in urban middle class Indians. Indian J Med Res 2000; 111: 95-102
- Bouchard C, Shephard RJ, Stephens T. Physical activity, fitness and health. Champaign, IL: Human Kinetics, 1994:77-88.
- Shephard RJ. How much physical activity is needed for good health. Int J Sports Med 1999;20:23–7.
- Teichner, Warren H. Recent studies of simple reaction time. Psychological Bulletin 51.2 (1954):128.
- T.G.Matthew Pain and A. Hibbs, “Sprint Starts and the Minimum Auditory Reaction Time,” Journal of Sports Sciences, Vol. 25, No. 1, 2007, pp. 79-86.
- Duke-Elder S. Franciscus Cornelis Donders. Br J Ophthalmol. 1959;43:65–8
- Welford AT. Choice reaction time: Basic concepts. In: Welford AT, editor. Reaction Times. New York: Academic Press; 1980. pp. 73–128.
- Luce RD. London: Academic Press; 1968. [Last accessed on 2011 Aug 08]. Information Theory of Choice. Reaction Times. Available from http:// www.biology.clemson.edu/bpc/bp/Lab/110reaction.htm.
- Levitt S and Gutin B Multiple choice reaction time and movement time during physical exertion. Research quarterly 1971;42: 405-410
- Kashihara K and Nakahara Y. Short term effect of physical exercise at lactate threshold on choice reaction time. Perceptual and Motor Skills 2005 100;2: 275-291.
- Ainsworth BE, Haskell WL, Herrmann SD, Meckes N, Greer JL, Vezina J, Basett DR. Jr, Tudor - Locke C, Whitt- Glover MC, Jacobs DR. Jr., Leon AS. 2011 Compendium of Physical Activities: a second update of codes and MET values Med Sci Sports Exerc. 2011 Aug;43(8):1575-8, doi:10 1249/MSS.0b03e31821 ecs
- Thomas JI, Venkatesh D. A comparative study of the effects of superbrain yoga and aerobic exercise on cognitive functions. National Journal of Physiology, Pharmacy and Pharmacology. 2017;7(9):895.
- 14.Jain A, Bansal R, Kumar A, Singh KD A comparative study of visual and auditory reaction times on the basis of gender and physical activity levels of medical first year students. Appl BasicMed Res 2015 May-Aug ; 5(2): 124-127
- Karia RM, Ghuntla TP, Mehta HB, Gokhle PA, Shah CJ. Effect of gender difference on visual reaction time: A study on medical students of Bhavnagar region. IOSR-PHR. 2012;2:452-4
- R. Niruba and Maruthy KN. Assessment of auditory and visual reaction time in Type 2 Diabetes- A case control study. Al Ameen J MedSci (2011)4(3):274-279
- Physical Activity Guideline Advisory Committee. Physical Activity Guideline Advisory Committee Report. Washington(DC): US Department of Health and Human Services; 2008. p 23.
- Skandan KP, Mehta SK, Mehta YB, Gaur HK.Visuo motor co-ordination time in normal children. Ind Ped 1980; 17: 275-278.
- Gavkare AM, Nanaware NL, Surdi AD. Auditory reaction time, visual reaction time and whole body reaction time in athletes. Indian Medical Gazette2013; June: 214-219.
- Jain AK. Manual of Practical Physiology. New Delhi: Avichal Publishing Company, 2000;p291
- Shenvi D and Balasubramanian P. A comparative study of visual and auditory reaction time in males and females. Indian J Physiol Pharmacol, 1994; 38: 229-231.
- Nikam LH and Gadkari JV. Effect of age, gender and body mass index on visual and auditory reaction times in healthy Indian population. Indian J Physiol Pharmacol 2012; 56(1): 94- 99.
- Gunstad J, Lhotsky A, Wendell CR, Zonderman AB. Longitudinal Examination of Obesity and Cognitive Function: Results from the Baltimore Longitudinal Study of Aging Neuroepidemiology.2010 May; 34(4): 222–229.
- Weuve J, Kang JH, Manson JE, Breteler MMB, Ware JH, Grodstein F. Physical Activity, Including Walking, and Cognitive Function in Older WomenJAMA. 2004;292(12):1454-1461. doi:10.1001/jama.292.12.1454
- Erickson KI, Hillman C, Stillman CM, Ballard RM, Bloodgood B, Conroy DE et al. Physical Activity, Cognition, and Brain Outcomes: A Review of the 2018 Physical Activity Guidelines. Med Sci Sports Exerc. 2018 Jun ;51(6): 1242-1251.