Keeping up with research

It is impossible to be up to date in research. Some people try, but I gave up a long time ago. Even if my whole job was reduced to reading new material, I could not keep up with the volume of journal articles. The first time I was aware of this, it produced a sense of defeat or existential dread; it was overwhelming. Then I had to dig into my (theoretical) inner Buddhist and just let go: there is no point on keeping with the news.

I convinced myself that it was much better to understand a small core of ideas—mostly the breeder’s equation, mixed linear models, context specific information about my crops—and the rest was anchoring new stuff into the core. Say that I got NIR spectra relationships; that’s new responses (y) in my model. Or genomic data, that’s a bunch of X, or simply a corrected pedigree or enriched numerator relationship matrix. Perhaps we got hyperspectral drone data; we have some new tree crown metrics that may end up as X, competition indices that may enrich the right-hand side of the models, etc.

I believe one feels ’less panicky’ about new stuff if one can link it somewhere in the model, or graft it to one’s knowledge model, to sound like dealing with trees. I don’t need to keep on pressing Ctrl+R on new research, but only figure out it fits in my well-understood abstraction of the world.