- Benefit–Cost Analysis of Increased Funding for Agricultural Research and Development in the Global South. Fancy model says funding agricultural research is great value for money. Ok, let’s see if we can find some examples.
- Exploring CGIAR’s efforts towards achieving the Paris Agreement’s climate-change targets. Yeah, but in designing such research to mitigate climate change there should be more complete integration of food-systems perspectives.
- Crop species diversity: A key strategy for sustainable food system transformation and climate resilience. Now there’s a nice thing to integrate into your climate change adaptation and integration research.
- Cultivating success: Bridging the gaps in plant breeding training in Australia, Canada, and New Zealand. Gonna need more plant breeders also, though.
- Artificial intelligence in plant breeding. Yeah, and probably more artificial intelligence too.
- Wheat genetic resources have avoided disease pandemics, improved food security, and reduced environmental footprints: A review of historical impacts and future opportunities. Great advances have been made (even without AI) by wheat breeders, but there’s still a lot of untapped diversity out there.
- Harnessing landrace diversity empowers wheat breeding. For example in the A. E. Watkins landrace collection.
- Enhanced radiation use efficiency and grain filling rate as the main drivers of grain yield genetic gains in the CIMMYT elite spring wheat yield trial. Gotta wonder if there’s a limit though.
- Origin and evolution of the bread wheat D genome. Maybe we can squeeze a bit more out of the D genome. I wonder what AI says about that.
- The Role of Crop Wild Relatives and Landraces of Forage Legumes in Pre-Breeding as a Response to Climate Change. As above, but for a bunch of forages.
- Stakeholder Insights: A Socio-Agronomic Study on Varietal Innovation Adoption, Preferences, and Sustainability in the Arracacha Crop (Arracacia xanthorrhiza B.). Here’s an interesting methodology to evaluate the impact of new varieties designed and developed by AI (or not).
- Deep genotyping reveals specific adaptation footprints of conventional and organic farming in barley populations — an evolutionary plant breeding approach. An initial, diverse barley population is allowed to adapt to contrasting organic and conventional conditions for 2 decades and diverges considerably genetically as a result. Don’t need AI to predict that. Perhaps more surprisingly, analysis suggests organic-adapted populations need to be selected for root traits to catch up in yield.
- Natural selection drives emergent genetic homogeneity in a century-scale experiment with barley. What is it with barley breeding and long-term experiments? This one shows that a hundred years of natural selection has massively narrowed genetic diversity. Why aren’t there long-term wheat experiments? Or are there?
- Association study of crude seed protein and fat concentration in a USDA pea diversity panel. Really high protein peas are possible. No word on whether kids will like them any better. Let’s check again in a hundred years?
- Telomere-to-telomere Citrullus super-pangenome provides direction for watermelon breeding. Forget sweetness and disease resistance, maybe one of these wild species will help us grasp the holy grail of seedlessness. Wait, let me check on the whole cost-benefit thing for this.
- An indigenous germplasm of Brassica rapa var. yellow NRCPB rapa 8 enhanced resynthesis of Brassica juncea without in vitro intervention. Sort of like that wheat D genome thing, but for mustard. I do wonder why we don’t try crop re-synthesis a lot more.
- Special issue: Tropical roots, tubers and bananas: New breeding tools and methods to meet consumer preferences. Why involving farmers in all of the above could be a good idea.