Spatial analysis increases efficiency of progeny testing of Chinese fir

• DOI: 10.1007/s11676-016-0341-z
• Publication Date: 2016-11-19T05:08:27Z
• Authors: Liming Bian; Renhua Zheng; Shunde Su; Huazhong Lin; Hui Xiao; Harry Xiaming Wu; Jisen Shi
• Keywords: Cunninghamia; Tree (set theory); Variance components; Tree breeding

We used spatial, global trend and post-blocking analysis to examine the effectiveness of a progeny trial in tree breeding program for Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) on hilly site with an environmental gradient from hill top bottom. Diameter at breast height (DBH) data had significant spatial auto-correlations among rows columns. Adding first-order separable autoregressive term more effectively modelled variation than did incomplete block (IB) model experimental design. The also accounted effects design factors greatly reduced residual variances. relative IB improved estimation genetic parameters variance 13 19% DBH height, respectively; heritability increased 35 51% gain 3–5%. Fitting not improve analyses under model. use or combined is recommended forest trials, particularly local sites.