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Journal of Forests

June 2020, Volume 7, 1, pp 1-8

Evaluating Variation in Seed Quality Attributes in Pinus Patula Clonal Orchards using Cone Cluster Analysis

Jesse Omondi Owino

,

Peter Murithi Angaine

,

Alice Adongo Onyango

,

Samson Okoth Ojunga

,

John Otuoma

Jesse Omondi Owino 1 ,

Peter Murithi Angaine 1 Alice Adongo Onyango 3
Samson Okoth Ojunga 1 John Otuoma 5

  1. Rift Valley Ecoregion Research Program Kenya Forestry Research Institute (KEFRI)Londiani, Kenya. 1

  2. Rift Valley Ecoregion Research Program Kenya Forestry Research Institute (KEFRI)Londiani, Kenya; Department of Natural Resources Management Faculty of Environment and Resources Development Egerton University Egerton, Kenya. 3

  3. Lake Victoria Basin Ecoregion Research Program Kenya Forestry Research Institute (KEFRI) Kisumu, Kenya. 5

Pages: 1-8

DOI: 10.18488/journal.101.2020.71.1.8

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Article History:

Received: 16 March, 2020
Revised: 20 April, 2020
Accepted: 22 May, 2020
Published: 12 June, 2020


Abstract:

Clonal seed orchards are majorly established for the production of seed of known quality attributes. However, these seed sources often cross-pollinate over the years, forming new varieties of unknown seed quality traits. Given the long period that it takes forestry tree species to naturalize through provenance trials, it is desirable to develop rapid techniques for assessing seed quality traits to support the expansion of clonal seed sources. We evaluated the variability in seed quality among Pinus patula clonal seed orchards based on three physical cone characteristics (length, diameter, and weight) using cluster analysis and Principal Component Analysis. The results indicated that cone length was the significant component controlling for the groupings, with width and weight having almost similar influencing power as factors. Cluster analysis identified five optimal natural groupings out of a possible 14 clusters. The optimal groups had values that could easily be used in the grading of cones. The results suggest that cluster analysis holds promise for tree improvement specialists as a rapid, unbiased, and novel technique for assessing clonal seed material at a reasonably affordable cost. It is expected that future seed harvests in Pinus patula seed orchards will target cone length as an indicator of superior seed quality.
Contribution/ Originality
This study uses a new estimation methodology based on P. patula cone morphometric characteristics. The length of cone, the diameter of cone, the weight of cone and seed yield per cone from clonal seed orchards of in Londiani, Kenya are assessed using principal component analysis and cluster analysis methodologies.

Keywords:

Pinus patula, Cone characteristics, Principal component analysis, Cluster analysis, Seed quality, Seed yield.

Reference:

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Statistics:

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Funding:

This study received no specific financial support.

Competing Interests:

The authors declare that they have no competing interests.

Acknowledgement:

Authors are sincerely grateful to Kenya Forestry Research Institute’s management for the support They were accorded during the entire process of this work including the long-term management of the seed orchards from which cones used in this study was conducted. Their special thanks go to the following persons: Richard Siko for assistance with cone collection; Lydia Khibali and Jared Ogembo for laboratory support in cone measurements; Hutchson Githinji for driving the team to the field and finally Peter Erukia for sourcing and supply of materials and equipment.

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