You may already be eating leafy greens that grow without soil, sunlight or ever being touched by human hands. Vertical farming has gained interest from growers and major investors around the world as a way to provide nourishing food, especially in urban areas. Gail Taylor, a vertical agriculture researcher and chair of the UC Davis Department of Plant Sciences, offered this perspective in an article recently published in The Guardian:
Severe flooding throughout the Midwest — which triggered a delayed growing season for crops in the region — led to a reduction of 100 million metric tons of net carbon uptake during June and July of 2019, according to a new study. Professor Troy Magney, Plant Sciences, UC Davis, co-authored the study.
Troy Magney, Dept. of Plant Sciences, is using methods such as hyperspectral imaging – a remote sensing technique – to measure plant water stress, nutrient status, biomass, and photosynthesis in order to make informed decisions about water and fertilizer management. This is important for global agriculture in the future.
A driverless, autonomous weed cultivator is being tested at UC Davis, uprooting weeds with wheels of fingers as it travels. Steve Fennimore, Plant Sciences, is working with Simon Belin at Naio Technologies. The goal is to reduce labor, costs, and herbicide use.
Drone-mounted cameras are being used to determine fertilizer needs in agricultural crops, which also helps growers reduce crop fungal diseases. Bruce Linquist and Luis Espino address the use of drones (or unmanned aerial vehicles; UAVs) in rice production.
Breeding crops has been practiced for millennia — new technology has greatly enhanced the ability of plant breeders to feed the world’s growing population, while spearheading a new era of agriculture in harmony with nature and people. Sustainability, Disease resistance, and Labor efficiency are pressing issues in plant breeding.
Understanding the steps in metabolic and biochemical pathways is difficult to determine. Scientists at UC Davis and Ben-Gurion University applied machine learning (artificial intelligence) techniques to this problem in tomatoes, and predicted new, previously unknown metabolic pathways.
These interdisciplinary projects help develop new partnerships, long-term collaborations, and opportunities to advance the health for people, animals, and the planet.
