Principal Component Analysis in Biometric, Pulp Quality and Anatomical Properties of Thronless Bamboo (Bambusa balcooa)

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N. Krishnakumar
S. Umesh Kanna
K. T. Parthiban


Aims: To estimate the impact, connection and association among the biometric attributes, pulping qualities and anatomical characters in Bambusa balcooa.

Place and Duration of Study: The study was conducted across the agro climatic regions viz., North Eastern Zone, Northern Zone, Western Zone, Cauvery Delta Zone and Southern Zone of Tamil Nadu, India during 2017-2018.

Methodology: The Principal Components Analysis (PCA) was examined to establish the numbers of clusters using Statistical Package for Social Studies (SPSS) version 16.0.1 software in order to identify the patterns of variation (PCA). The principal component analysis was computed using the equation PCA = Σa jXj.

Results: The PCA separated into three cluster principal components among the nineteen parameters studied. Out of nineteen principal components generated, twelve principal components had contributed positively on pulp yield. Among these twelve traits, maximum contribution to the pulp yield was observed by the traits viz., numbers of culms, hollocellulose, kappa number, tear index, burst index, fibre wall thickness and vessel diameter with respect to Bambusa balcooa.

Conclusion: The results showed some relationships between the biometric attributes, pulping qualities and anatomical characters in Bambusa balcooa. PCA was shown to be a useful tool for assessing the impact and connection for further research.

Thornless bamboos, PCA, impact & connection, biometric attributes, pulping qualities, anatomical characters, Bambusa balcooa

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How to Cite
Krishnakumar, N., Kanna, S. U., & Parthiban, K. T. (2019). Principal Component Analysis in Biometric, Pulp Quality and Anatomical Properties of Thronless Bamboo (Bambusa balcooa). International Journal of Environment and Climate Change, 9(6), 350-355.
Original Research Article


Deo Kumar Tamang, Dinesh Dhakal, Sambhawana Gurung, Sharma NP, Shrestha DG. Bamboo diversity, distribution pattern and its uses in Sikkim (India) Himalaya. International Journal of Scientific and Research Publications. 2013;3(2).

Gokul R. Genetic analysis and hybridization in Eucalyptus species. M.Sc. (For) Thesis. Tamil Nadu Agricultural University, Coimbatore; 1997.

Kovacic. A factor analysis of plant variables associated with architecture and seed size in dry bean. Euphytica. 1994;60: 171-177.

Krishnakumar N, Kanna SU, Parthiban KT, Shree MP. Growth performance of thorn less bamboos (Bambusa balcooa Roxb. and Bambusa vulgaris Schrader ex JC Wendland). Int. J Cur. Microbiol. App. Sci. 2017;6(4):32-39.

Kundu SK, Tigerstedt PMA. Geographic variation in seed and seedling traits of neem (Azadirachta indica) among 10 populations studied in growth chamber. Silvae Genet. 1997;46(2-3):129-137.

Paramathma M. Studies on genetic inheritance and interspecific crosses of Eucalyptus. Ph.D. Thesis. Tamil Nadu Agricultural University, Coimbatore; 1992.

Pinyopusarerk K, Williams ER, Luangviriyasaeng V, Puriyakorn B. Geographic variation in growth and morphological traits of Casuarina equisettifolia. Recent Casuarina Research and Development. (In. Proceedings of Third International Casuarina Workshop Da Nang, Vietnam). 1996;143-151.

Tewari DN. A monograph of Bamboo. International Book Distributors. Dehradun, India. 1996;495.

Vasic Mirjana, Jelica Gvozdanovic- Varge, Janko Cervenski. Divergence in the dry bean collection by PCA. Genitika. 2008;23-29.

Adams MJ. The principles of multivariate data analysis. Analytical Methods of Food Authentication. 1998;308.

Amy EL, Pritts MP. Application of principal component analysis to horticultural research. Hort Science. 1991;26(4):334-338.

Jeffers JNR. Two case studies in the application of principal component analysis. Applied Statistics. 1967;16:225–236.

Jobson JD. Applied multivariate data analysis: Categorical and multivariate methods. Springer-Verlag. New York. NY. USA. 1992;2:731.

Katwal RPS, Srivastva RK, Kumar S, Jeeva V. State of forest genetic resources conservation and management in India. Forestry Department; 2003.

Seal Hilary. Multivariate statistical analysis for biologists; 1964.

SPSS INC. SPSS version 16.0. Chicago, IL: SPSS Incorporated; 2007.