In its latest impact statement, the Multistate Research Fund highlights agricultural innovation through federal funds to collaborative research projects among land-grant universities. These Multistate Research Projects bring together scientists and Extension, private university, federal, international, and industry partners to tackle high-priority regional or national issues in agriculture.
Researchers at land-grant universities in multiple states are working together to develop automated systems that work well for specialty crops. Over the last five years, researchers identified key parameters associated with specialty crop production and developed sensors to detect and measure these parameters. Researchers designed mechanized devices and partnered with manufacturers and farmers to commercialize and implement new technologies.
Here are some of the farm automation highlights from Multistate Research Projects:
Automated devices help farmers map fruit yields and see if and where there are issues so they can make targeted, effective management decisions. Accurate estimates of yields also are important for marketing decisions. Data about the location of fruits and the geometry of tree branches are used to program machines to harvest orchards.
- University of Florida developed an autonomous robot that counts and maps the fruit on citrus
- University of California, Davis researchers developed fruit-picking bags and carts with instruments that map orchard
Automated disease detection and management technologies could mitigate losses of fruit crops.
- Pesticides cause millions of dollars in unintended crop losses when spray droplets drift onto non-target Iowa State University work is guiding the manufacturing of technology that reduces drift.
- Citrus growers used a heat treatment machine designed by University of Florida scientists on more than 80,000 trees to control the progress of citrus
- Washington State University developed unmanned aerial vehicles to deter birds that eat and damage fruit
Mechanized production and harvesting can prevent injuries due to manual labor and reduce harvest time and costs for farmers.
- 60% of the tomato processing industry has adopted machines designed by UC Davis to inspect tomato During a single season, the machines eliminate more than 200,000 repetitive motion hazards for workers.
- Farmers said a new pruning method recommended by Pennsylvania State University Extension would likely cut pruning time by 42% and save about $136 per
- Pennsylvania State University researchers designed a harvest-assist device that eliminated ladder falls and reduced the time apple pickers spent in awkward, dangerous postures from 65% to 43% of picking The device also increased the number of apples harvested per second by 50%.
- Washington State University scientists designed a robotic twining machine for hops, which will cut labor needs and
- University of Georgia researchers explore affordable automated technologies that will improve blueberry harvest efficiency, helping overcome labor shortages and high labor
- Mechanized weeding reduces the need for costly manual labor and chemicals, which can harm the environment and human University of Arizona and UC, Davis showed that automated in-row weeding machines reduce labor requirements by 30%.
Automation helps farmers conserve resources, save money, and reduce greenhouse gas emissions.
- University of Kentucky researchers demonstrated an autonomous diesel/electric hybrid
- Researchers discovered that automated robotic weeding systems are effective at much lower power levels than previously
Automated technology helps ensure quality and consumer satisfaction.
- Michigan State University and UC, Davis developed sensing technology capable of detecting internal and external defects, such as color vision and spectroscopy systems that automatically infer fresh produce
- Researchers developed an affordable automated system that accurately identifies mature tomatoes during processing, ensuring products have the superior flavor and
- Sensor data showed how to breed blueberries that can be machine harvested without being