Category: linkedin

  • In between plant and animal breeding 1: economic weights

    In between plant and animal breeding 1: economic weights

    Unless you live in paradise and you have a single objective trait—so your whole breeding objective is “more X”—you have to take into account trade-offs between traits. On the genetics front we deal with this via genetic correlations, but on the value front we have to figure out how much is an extra unit of…

  • Carbon

    Carbon

    I am fascinated by trees, those cute and enormous organisms made out of air. The idea that I can hug the trunk of a little seedling I planted a quarter of a century ago, or stand next to a thousand-year-old alerce is mind blowing. I am also fascinated by the idea of providing products and…

  • Even worse than pedigree errors: selecting for the wrong thing

    Even worse than pedigree errors: selecting for the wrong thing

    Imagine this: you have been patiently assessing trees for wood density (selection criterion) thinking that you’re improving wood stiffness (objective trait). Stiffer trees produce stiffer and more dimensionally stable wood, higher value, more profit. Your choice of density sounds reasonable, on average denser wood tends to be stiffer… except that wood is not getting stiffer.…

  • In between plant and animal breeding 1

    In between plant and animal breeding 1

    Let’s start with the obvious: trees are plants and—unless you are breeding Ents—they do not walk around. Therefore, the first obvious statement is that tree breeding heavily relies on experimental designs to account for environmental variability. But trees are much larger and long-lived than corn or potatoes, so we need much larger trials, in land…

  • Do I have pedigree errors?

    Do I have pedigree errors?

    We just finished a genetic analysis, got breeding values for all our selection criteria, combined them with genetic parameters and economic weights in a selection index (I) that predicts the total genetic-economic value in dollars (H). We rank our trees from best to worst, perhaps with some constraint on relatedness, and go to the field…