- Searching for plants in botanic gardens.
- Searching for the best apple.
- Searching for pumpkins and squashes.
- Searching the Pomological Watercolor Collection.
- Searching for livestock.
- Searching for varietal turnover. And other kinds of impact.
Brainfood: Maize, Chickpea, CWR, Canola, Coconut, Avocado, Eggplant, Carrot, Watermelon, Citrus, Potato, Pearl millet, Roses
- A New Methodological Approach to Detect Microcenters and Regions of Maize Genetic Diversity in Different Areas of Lowland South America. Multiple disciplines identify 4 microcenters of maize diversity in the lowlands of South America.
- Historical Routes for Diversification of Domesticated Chickpea Inferred from Landrace Genomics. Genomics identifies both Indian and Middle Eastern traces in Ethiopian chickpeas.
- Crop wild relatives in Lebanon: mapping the distribution of Poaceae and Fabaceae priority taxa for conservation planning. Spatial analysis identifies a couple of key ex situ and in situ conservation areas for CWR in Lebanon.
- Analysis of gaps in rapeseed (Brassica napus L.) collections in European genebanks. Spatial analysis identifies a few key ex situ and in situ conservation areas for rapeseed wild relatives in Europe.
- Genomic and population characterization of a diversity panel of dwarf and tall coconut accessions from the International Coconut Genebank for Latin America and Caribbean. Characterization of various sorts identifies different Atlantic and Pacific coconut genepools in the Western Hemisphere.
- Pleistocene-dated genomic divergence of avocado trees supports cryptic diversity in the Colombian germplasm. Genomics identifies a uniquely Colombian avocado genepool.
- Analysis of >3400 worldwide eggplant accessions reveals two independent domestication events and multiple migration-diversification routes. Genomics identifies separate Southeast Asia and Indian areas of domestication, and limited exchange between them.
- Population genomics identifies genetic signatures of carrot domestication and improvement and uncovers the origin of high-carotenoid orange carrots. Genomics identifies wester-central Asia as the area of carrot domestication in the Early Middle Ages, and western Europe as the place where the orange variant was selected in the Renaissance.
- A Citrullus genus super-pangenome reveals extensive variations in wild and cultivated watermelons and sheds light on watermelon evolution and domestication. Pangenomics identifies a gene in wild Kordofan melons as promoting the accumulation of sugar in watermelon.
- Pangenome analysis provides insight into the evolution of the orange subfamily and a key gene for citric acid accumulation in citrus fruits. Pangenomics identifies south central China as the primary centre of origin of the genus Citrus.
- Pangenome analyses reveal impact of transposable elements and ploidy on the evolution of potato species. Pangenomics identifies wild species from North and Central America as having lots of genes for abiotic stress response, but also fewer transposable elements.
- Pangenomic analysis identifies structural variation associated with heat tolerance in pearl millet. Pangenomics identifies the key genes and structural variations associated with pearl millet accessions from the most hot and dry places.
- Dark side of the honeymoon: reconstructing the Asian x European rose breeding history through the lens of genomics. Genomics and other data identifies a shift from a European to a mainly Asian genetic background in cultivated roses during the 19th century, leading to a narrowing of genetic diversity.
Nibbles: Heirloom mixology, Renaissance breeding, Heirloom watermelon, Heirloom apples, British horses, Ancient grapes & wine, Potato cryo, Arboretum, Svalbard Global Seed Vault, Rice breeding
- A self-described seed mixologist calls for a science fiction, rather than historical, approach to growing heirloom varieties. Excellent reading.
- The Renaissance approach to genetic mixology explained in a new book The Perfection of Nature.
- Sometimes, though, you just want a good old watermelon.
- Or a good old apple.
- Or indeed ‘the Swiss army knife of equines.’
- Or you want to know what ancient people ate and drank.
- So it’s a good thing we have genebanks, genebanks, genebanks…
- Including for rice.
Nibbles: Crop diversity, Coloured rice, Saudi genebank, WorldVeg genebank, Mango genebank, USDA apple genebank, Green Revolution, Organic agriculture
- IFAD says we need diverse crops.
- KAUST says we need coloured rice.
- I hope it will go into Saudi Arabia’s new genebank.
- Genebank scientists says we need more collaboration.
- Goa thinks they need a new mango genebank.
- The USA already has an apple genebank.
- But will all these genebanks lead to a new Green Revolution…
- …or organic farming?
- Maybe both.
Brainfood: Food insecurity drivers, Agroecology & fertilizers, Overselling GMOs, Genomic prediction, Striga breeding, Farmers’ preferences, Farmers’ WtP, Diversity metrics
- Drivers and stressors of resilience to food insecurity: evidence from 35 countries. Diversify!
- The input reduction principle of agroecology is wrong when it comes to mineral fertilizer use in sub-Saharan Africa. …but that doesn’t mean agroecology is wrong. So, diversify your mind?
- Genetic modification can improve crop yields — but stop overselling it. Diversify your research teams.
- Genomic predictions to leverage phenotypic data across genebanks. Diversify your training set.
- Harnessing plant resistance against Striga spp. parasitism in major cereal crops for enhanced crop production and food security in Sub-Saharan Africa: a review. Diversity within the weed is almost as important as diversity in host resistance, and less studied.
- Farmers’ heterogeneous preferences for traits of improved varieties: Informing demand-oriented crop breeding in Tanzania. Breeders need to take into account farmer diversity too.
- Farmer Risk Preferences and Willingness to Pay for African Rice Landrace Seed: An Experimental Choice Analysis. Farmers are willing to pay for diversity.
- Too simple, too complex, or just right? Advantages, challenges and resolutions for indicators of genetic diversity. What’s the best way to measure diversity anyway?