Principal component analysis of growth traits in Aseel native chicken
PCA of Growth in Aseel Chicken
467 / 294
Authors
-
AMIT KUMAR
Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly (U.P.), India
Author
-
SANJEEV KUMAR
Bihar Animal Sciences University, Patna (Bihar), India
Author
-
MANJARI PANDEY
Department of Animal Genetics and Breeding, College of Veterinary and Animal Sciences, Kishanganj, (Bihar), India
Author
-
SAKSHI VAISHNAV
Regional Sericulture Research Station (Laxmipur), Sahaspur, Dehradun (Uttarakhand), India
Author
-
ANUJ CHAUHAN
Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly (U.P.), India
Author
-
ROSHNI CHAND
Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly (U.P.), India
Author
Keywords:
Aseel Chicken, Bartlett’s Test, Body weight, Kaiser-Meyer-Olkin Test, PCAAbstract
Aseel is a well-recognised native chicken breed, known for its endurance, fighting skills, majestic gait and higher tolerance for heat and stress conditions etc., and is being used for development of superior crosses for backyard poultry farming. This study investigated relationship between earlier body weights with the subsequent weights until the market age, i.e., 20-week. Records of chick weight (n=620) and weights at bi-weekly intervals (n=1070) were analysed for Principal Component Analysis (PCA) using IBM-SPSS version 26. All the coefficients were significant (p≤0.01) and positive, indicating that trait has good predictability, which could be useful in chalking out of selection and improvement programs. Low to moderate correlations were estimated between juvenile body weights with weight at marketable age (0.10-0.55) while the correlations were higher (0.63 - 0.95) thereafter. Kaiser-Meyer-Olkin measure of sample adequacy and Bartlett’s test of sphericity and communality at different ages were also calculated, which revealed adequacy of samples for PCA. The selected two components collectively explain the 79.46% of total variability present in the dataset. The first component explained 66.51% variability while the second component accounts for 12.94% variability. It was concluded that PCA is an excellent tool for reducing the recording of number of traits or dimension of the original data. Further, the extracted principal components were useful in prediction of body weight at market age in Aseel native chicken
Downloads
References
1. Ajayi, F.O., Ejiofor, O. and Ironkwe, M.O. 2008. Estimation of
2. body weight from linear body measurements in two
3. commercial meat-type chicken. Global Journal of
4. Agricultural Science, 7: 57-59.
5. Amao, S.R. 2018. Application of principal component analysis
6. on the body morphometric of Nigerian indigenous chickens
7. reared intensively under southern guinea savanna condition
8. of Nigeria. Journal of Environmental Issues and Agriculture
9. in Developing Countries, 10: 1-12.
10. Bartlett, M.S. 1950. Tests of significance in factor analysis. British
11. Journal of Psychology, 3: 77-85.
12. Basic Animal Husbandry Statistics (BHAS). 2019. Ministry of
13. Animal Husbandry, Dairying and Fisheries, Ministry of
14. Agriculture, Government of India. (www.dahd.nic.in.).
15. Brody, S. 1964. Bioenergetics and growth; with special reference
16. to the efficiency complex in domestic animals. Hafner Press,
17. Reinhold, New York, USA.
18. Dalal, D.S., Ratwan, P. and Yadav, A.S. 2019. Genetic evaluation
19. of growth, production and reproduction traits in Aseel and
20. Kadaknath chickens in agro climatic conditions of northern
21. India. Biological Rhythm Research, 53: 40-49.
22. Dalal, D.S., Ratwan, P., Malik, B.S., Patil, C.S. and Kumar, M.
23. 2020. Principal component analysis of morphological traits
24. of synthetic White Leghorn chicken. Indian Journal of
25. Animal Science, 90: 1551-1555.
26. Dalton, H.A., Wood, B.J., Widowski, T.M., Guerin, M.T. and
27. Torrey, S. 2017. An analysis of beak shape variation in two
28. ages of domestic turkeys (Meleagris gallopavo) using
29. landmark-based geometric morphometrics. PLoS One, 12:
30. e0185159.
31. Egena, S.S.A., Ijaiya, A.T., Ogah, D.M. and Aya, V.E. 2014.
32. Principal component analysis of body measurements in a
33. population of indigenous Nigerian chickens raised under
34. extensive management system. Slovak Journal of Animal
35. Science, 47: 77-82.
36. Girija, S., Tyagi, J.S., Mariappan, A.K., Faslu Rahman, A.T.,
37. Sharma, S., Singh, T., Srivastava, V. and Kolluri, G. 2023.
38. Studies on production and biochemical profile in indigenous
39. and exotic chicken challenged with velogenic Newcastle
40. disease virus (vNDV). Indian Journal Poultry Science, 58:
41. 191-194.
42. Haunshi, S., Niranjan, M., Shanmugam, M., Padhi, M.K., Reddy,
43. M.R., Sunitha, R. and Panda, A.K. 2011. Characterization
44. of two Indian native chicken breeds for production, egg and
45. semen quality, and welfare traits. Poultry Science, 90: 314-
46. 320.
47. Jha, D.K., Prasad, S., Soren, S.K. and Bharti, A. 2013. Production
48. performance of indigenous chicken in intensive farming
49. systems. Indian Journal of Poultry Science, 48: 105-108.
50. Johnson, R.A. and Wichern, D.W. 2007. Applied multivariate
51. statistical analysis. Prentice Hall International. INC., New
52. Jersey.
53. Kaiser, H.F. 1960. The application of electronic computers to
54. factor analysis. Educational and Psychological
55. Measurement, 20: 141-151.
56. Kumar, A. 2022. Genetic analysis of Body weights and Growth
57. Trends in Aseel Native Chicken. M.V.Sc. Thesis, Deemed
58. University IVRI, Izatnagar.
59. Kumar et al. / PCA of Growth in Aseel Chicken
60. Indian Journal of Poultry Science (2024) 59(3): 241−246 / 245
61. 246
62. Kumar, M., Dahiya, S., Ratwan, P. and Sheoran, N. 2022. Evaluation
63. of morphological traits in Aseel and Kadaknath breeds under
64. backyard poultry farming using principal component
65. analysis. Turkish Journal of Veterinary & Animal Science,
66. 46: 356-365.
67. Kumar, S. and Pandey, M. 2021. Developing crosses for backyard
68. production as per location and farmer’s preference. In:
69. Specialized Training Course on “Backyard Poultry
70. Farming”, ICAR-CARI, Izatnagar (ISBN No. 978-93-
71. 5457-311-8), pp 59-67.
72. Maharani, D., Hariyono, D.N., Putra, D.D., Lee, J.H. and
73. Sidadolog, J.H. 2019. Phenotypic characterization of local
74. female duck populations. Indonesian Journal of Asia-Pacific
75. Biodiversity, 12: 508-514.
76. Nayak, N., Bhanja, S. K., Eaknath, B., Chakurkar, Sahu, A. R. and
77. Kumar, S. 2021. Effect of mid-embryonic thermal
78. conditioning on zootechnical performance, immunecompetence and expression profiling of HSP70 gene in
79. backyard chicken variety. Indian Journal of Poultry Science,
80. 56: 253-259.
81. Ogah, D.M. 2011. Assessing size and conformation of the body of
82. Nigerian indigenous turkey. Slovak Journal of Animal
83. Science, 44: 21-27.
84. Ogah, D.M., Alaga, A.A. and Momoh, M.O. 2009. Principal
85. component factor analysis of the morpho-structural traits
86. of Muscovy duck. International Journal of Poultry Science,
87. 8: 1100-1103.
88. Pandey, M., Kumar, S., Chandrahas, Kumar, A., Chaudhari, C.P.,
89. Kanarkhedkar, H.L. and Meena, R. 2022. Comparative
90. study of growth and layer economic traits in Aseel and
91. Kadaknath chicken breeds under intensive rearing system.
92. The Pharma Innovation Journal, SP-11: 1553-1557.
93. Pinto, L.F.B., Packer, I.U., De Melo, C.M.R., Ledur, M.C. and
94. Coutinho, L.L. 2006. Principal components analysis applied
95. to performance and carcass traits in the chicken. Animal
96. Research, 55: 419-425.
97. Pundir, R.K., Singh, P.K., Singh, K.P. and Dangi, P.S. 2011. Factor
98. analysis of biometric traits of Kankrej cows to explain body
99. conformation. Asian-Australasian Journal of Animal
100. Science, 24: 449-456.
101. Rajkumar, U., Haunshi, S., Paswan, C., Raju, M.V.L.N., Rao, S.R.
102. and Chatterjee, R.N. 2017. Characterization of indigenous
103. Aseel chicken breed for morphological, growth, production,
104. and meat composition traits from India. Poultry Science,
105. 96: 2120-2126.
106. Saikhom, R., Sahoo, A.K., Taraphder, S., Pan, S., Sarkar, U., Ghosh,
107. P.R. and Baidya, S. 2017. Principal component factor
108. analysis of morpho-structural traits of Haringhata Black
109. chickens. Indian Journal of Animal Health, 56: 211-218.
110. Saikhom, R., Sahoo, A.K., Taraphder, S., Pan, S., Sarkar, U., Ghosh,
111. P.R. and Baidya, S. 2018. Principal component analysis of
112. morphological traits of Haringhata Black chickens in an
113. organized farm. Exploratory Animal and Medical Research,
114. 8: 64-68.
115. Singh, A. (2023). Livestock Production Statistics of India - 2023.
116. https://www.researchgate.net/publication/
117. 376799772_Livestock_Production_Statistics_of_India_-
118. _2023. PDF Accessed March 11, 2023.
119. Singh, P., Kumar, S., Singh, H. N., Singh, D. P., Jaiswal, G. and
120. Meena, S. R. 2009. Genetics of immunocompetence traits
121. in Kadaknath native chicken. Indian Journal of Poultry
122. Science, 44: 173-176.
123. SPSS Statistical Package for Social Sciences. 2007. SPSS Inc., 444
124. Michigan Avenue, Chicago, IL, USA.
125. Udeh, I. and Ogbu, C.C. 2011. Principal component analysis of
126. body measurements in three strains of broiler chicken.
127. Science World Journal, 6: 11-14.
128. Yakubu, A., Kuje, D. and Okpeku, M. 2009. Principal components
129. as measures of size and shape in Nigerian indigenous
130. chickens. Thai Journal of Agricultural Science, 42: 167-
131. 176
