Brainfood: Digitizing collections, Bean core, Livestock diversity, Maya & maize, Fish stocks & CC, Save the weed, Flaw CWR, Italian agrobiodiversity
- Cross-validation of a semantic segmentation network for natural history collection specimens. Computers can distinguish the herbarium label from the actual specimen and other stuff on the sheet, helping with the whole automatic digitization thing, but it takes some really fancy math.
- The landscapes of livestock diversity: grazing local breeds as a proxy for domesticated species adaptation to the environment. Medium fancy math used to map breed diversity in the Iberian Peninsula for different livestock species and relate it to environmental factors.
- South-to-north migration preceded the advent of intensive farming in the Maya region. Sort of like tomato, but the other way around. Plenty of math involved, but behind the scenes, thankfully.
- Timing and magnitude of climate-driven range shifts in transboundary fish stocks challenge their management. Huge amount of data and very fancy math shows fish are in trouble.
- A Core Set of Snap Bean Genotypes Established by Phenotyping a Large Panel Collected in Europe. Ok, even I can follow the math on this one.
- Assessment of biogeographic variation in traits of Lewis flax (Linum lewisii) for use in restoration and agriculture. Very approachable math shows which populations of a CWR can best be used for restoration, and where; and also for domestication and breeding.
- An updated checklist of plant agrobiodiversity of northern Italy. Very useful use of very basic maths. Key number: only 43% of the PGR on the list are conserved ex situ.
- Cannabis, the multibillion dollar plant that no genebank wanted. No math needed to figure out weed needs a genebank.
Source: https://agro.biodiver.se/2022/04/brainfood-32/
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