Analysis of early tree height in forest genetic trials is enhanced by including a spatially correlated residual

By João Costa e Silva, G. Dutkowski, A. R. Gilmour. 2001

133 citations recorded by the source corpus.

Subfields: Genetics, Management Science and Operations Research, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/daf5175bd7439000c9c7b43158f52340eb8dcb4c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

1. A. R. Gilmour
2. João Costa e Silva
3. Hubert Wellendorf
4. Alexandre Aguiar
5. G. Dutkowski

In Management Science and Operations Research

1. A. R. Gilmour
2. João Costa e Silva
3. Hubert Wellendorf
4. Alexandre Aguiar
5. G. Dutkowski

In Nature and Landscape Conservation

1. A. R. Gilmour

Citations in the corpus

• Spatial analysis methods for forest genetic trials (2002, methodology): “While there is no a priori way of identifying which ones this might be, our results, and those of Costa e Silva et al. (2001), suggest that where variation is purely continuous in nature, then most design effects will be much reduced if not eliminated.”
• Spatial analysis enhances modelling of a wide variety of traits in forest genetic trials (2006, methodology): “Recent work on spatial analysis in forest genetic trials (Costa e Silva et al. 2001; Dutkowski et al. 2002), based on the work of Gilmour et al. (1997), has recommended that the standard analytical model using experimental design features be augmented with a spatial component in the form of separabl”