Evaluating variation in seed quality attributes in Pinus patula clonal orchards using cone cluster analysis

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.