Josh Bachman – NMSU Photo Robert Wojcikiewicz, left, and Emily Doss fly a drone for a geographic surveying experiment.
LAS CRUCES, N.M. – Researchers in the College of Agricultural, Consumer and Environmental Sciences at New Mexico State University are working to solve an array of real-world challenges – from tracking livestock.
Mexico State researchers
Big data is a loosely defined term for large datasheets collected and analyzed by researchers to reveal patterns, trends and associations, and predict behaviors and interactions. Many industries, including agriculture and farming, use big-data and super computing methods to identify solutions for some of the world’s most pressing challenges.
“With the world’s population expected to grow to more than billion by , there is an urgent need to produce more food on less land with less water and fewer”.
“The ability to collect enormous amounts of data is a reality,” Goldberg added. “Big data science moves that information to data analysis, machine learning, the development of decision-making tools, and the use of artificial intelligence and autonomous systems, including robotics. Implementation of big data science into agriculture will move technology development into solutions that will help solve some of agriculture’s most complex problems (Mexico State researchers) .”
Big data and emerging technologies
By implementing big data and emerging technologies. Goldberg said, agricultural producers can maximize efficient farming and ranching, save water, reduce chemical use, solve labor problems, and reduce food waste and contamination.
Currently, faculty members in the College of ACES and the Jornada. Experimental Range are leading collaborative research efforts that utilize big data and supercomputing.
Derek Bailey, a professor in the Department of Animal and Range Science, is using GPS tracking. And other sensors to monitor the welfare. Also productivity and sustainability of cattle and sheep on rangelands.
Large datasheets in the Randall Lab (Mexico State researchers)
Josh Bachman – NMSU Photo Hormat Shadgou Rhein, a Ph.D. student of Micro Biology, look over large datasheets in the Randall Lab with Jennifer Randall. A professor in the Department of Entomology, Plant Pathology and Weed Science. August , .
“Our lab is testing real-time and near real-time GPS tracking systems, accelerator ear tags. And other sensors that have promise for use by ranchers,” said Bailey, who has been tracking cattle since . “We combine these on-animal sensors with satellite imagery to simultaneously monitor forage resources and livestock behavior. Our group is working with animal breeding scientists at Colorado State University to identify genetic markers associated with cattle movement patterns grazing rugged rangelands.”
This will allow ranchers to select animals that use steep slopes and roam areas far from water sources. His goal, he said, is to use GPS tracking, sensor monitoring. Satellite imagery and genomics to develop “precision livestock management” systems. An approach that requires collecting, processing and analyzing large data sets (Mexico State researchers) .
“With technical improvements of sensors and associated reductions in equipment price. We can now track entire herds of cattle and collect movement data from accelerators at a rate of hertz.”
Using unmanned aerial vehicles
In future studies, Bailey hopes to start using drones to collect data. When that time comes, he will join other faculty members, including Niall Hanan. Who are already using unmanned aerial vehicles, or drones, and mexico in their research.
Hanan, a professor in the Department of Plant and Environmental Sciences, and his research group are working on environmental. And ecological data analysis using cloud-based computing as well as the high-performance computing facilities available at NMSU.
“ (Mexico State researchers) Our work includes analysis of satellite imagery using Google Earth Engine to better understand vegetation change in the dry lands of the southwestern United States, Africa and globally,” Hanan explained. “We also carry out computer-intensive analysis of UAV images and terrestrial lidar data to derive detailed three-dimensional vegetation structure information relevant to the productivity of shrub lands in the southwestern U.S. and globally,” he added.
Our data sets include large geospatial and climate data, such as optical and radar satellite imagery and global climate re-analyses. As satellite systems have developed, data volumes have increased exponentially. Prihodko said, “so we increasingly rely on big-data analysis techniques and high performance computers and cloud computing to process and analyze it.”
Developing artificial intelligence for agriculture
Earlier this year, College of ACES Dean Rolando Flores established an interdisciplinary team of researchers from four colleges. ACES, Arts and Sciences, Engineering and Business – to collaborate on a white paper focused on developing artificial intelligence for agriculture (Mexico State researchers).
“Over the next several years, these technologies will become increasingly prevalent in farming and ranching operations. Which will likely lead to the greatest increase in farming and ranching since mechanization,” Goldberg said. “These problems are complex, and development and implementation of big data. Artificial intelligence into agriculture requires researchers from across diverse disciplines to work together for solutions.”
She also oversees research in the Randall Lab, which she founded to focus on the genetic. Molecular mechanisms of plant development and plant-microbe interactions.
Randall is specifically interested in pecan development, including the molecular mechanisms involved in floral initiation, nutrient acquisition and salinity tolerance.