Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Estimation of Gene Actions and Character Association in F3 and F4 Generations of Little Millet Cross JK 8 X Peddasame Purple Early (Panicum miliare)


Affiliations
1 Project Coordinating Unit, Small Millets (U.A.S.) G.K.V.K., Bengaluru (Karnataka), India
     

   Subscribe/Renew Journal


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.
Subscription Login to verify subscription
User
Notifications
Font Size


  • 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.

Abstract Views: 371

PDF Views: 0




  • 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: 371  |  PDF Views: 0

Authors

B. Sujata
Project Coordinating Unit, Small Millets (U.A.S.) G.K.V.K., Bengaluru (Karnataka), India
C. Nandini
Project Coordinating Unit, Small Millets (U.A.S.) G.K.V.K., Bengaluru (Karnataka), India
M. Krishnappa
Project Coordinating Unit, Small Millets (U.A.S.) G.K.V.K., Bengaluru (Karnataka), India
Chandrashekhar Angadi
Project Coordinating Unit, Small Millets (U.A.S.) G.K.V.K., Bengaluru (Karnataka), India
Prabhakar
Project Coordinating Unit, Small Millets (U.A.S.) G.K.V.K., Bengaluru (Karnataka), India

Abstract


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