Video series by Gábor Mészáros on genomic data analysis.
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Water stress, Dothistroma and remote sensing
Long-term effects of water stress on hyperspectral remote sensing indicators in young radiata pine
https://www.sciencedirect.com/science/article/abs/pii/S0378112721007970
Prediction of the severity of Dothistroma needle blight in radiata pine using plant based traits and narrow band indices derived from UAV hyperspectral imagery https://www.sciencedirect.com/science/article/abs/pii/S0168192322004804
Experiments in glasshouse
Blocking and re-arrangement of pots in greenhouse experiments: which approach is more effective?
https://plantmethods.biomedcentral.com/articles/10.1186/s13007-019-0527-4
Plant image analysis
The pliman (plant image analysis) package is designed to analyze plant images, particularly for leaf and seed analysis. It offers a range of functionalities to assist with various tasks such as measuring disease severity, counting lesions, obtaining lesion shapes, counting objects in an image, extracting object characteristics, performing Fourier Analysis, obtaining RGB values, extracting object coordinates and outlines, isolating objects, and plotting object measurements.
Pedigree pruning
ggroups: an R package for pedigree and genetic groups data https://link.springer.com/article/10.1186/s41065-020-00124-2
Most documents go through several versions (always more than you expected) before they are finally finished. Accordingly, you should do whatever possible to make the job of changing them easy.
First, when you do the purely mechanical operations of typing, type so subsequent editing will be easy. Start each sentence on a new line. Make lines short, and break lines at natural places, such as after commas and semicolons, rather than randomly. Since most people change documents by rewriting phrases and adding, deleting and rearranging sentences, these precautions simplify any editing you have to do later. —Brian W. Kernighan (1974)
Genetic competition
Good explanation on fitting competition models in forest genetic trials using asreml:
Competitive Genetics: Exploring the impact of direct and indirect genetic effects in tree breeding. https://vsni.co.uk/blogs/competitive-genetics
Based on the work by Joao Costa e Silva and Richard Kerr “Accounting for competition in genetic analysis, with particular emphasis on forest genetic trials” https://link.springer.com/article/10.1007/s11295-012-0521-8
Physics of coffee
I’m often fascinated by the lengths people will go to get something they like, as in “Reaching Fuller Flavor Profiles with the AeroPress” https://coffeeadastra.com/2021/09/07/reaching-fuller-flavor-profiles-with-the-aeropress/
Getting rid of convergence information in asreml
I am coding simulations where I call asreml() and it was taking longer than necessary, because it was sending the convergence information to the screen. The trick to get rid of that is to use the trace = FALSE option as in
asreml(trait_1 ~ 1, random = ~ mum, data = current_trial, trace = FALSE)Getting rid of bars and outliers in boxplots
Sometimes I am testing graphs and I want to get rid of the lines (coef = 0) and outliers (outlier.shape = NA), particularly if I’m overlapping points.
geom_boxplot(coef = 0, outlier.shape = NA)