To sustain the Earth’s population as it grows from 7.4 billion people to 8 billion by 2025, and then prepare for more population growth, agriculture must become more productive, efficient, sustainable, and environmentally conscious.
To help meet these challenges, AgriLife Research is working alongside people all over the world in developing technologies for remote sensing. These technologies, which can help advance agriculture worldwide, can also strengthen our state’s economy. Agriculture employs one of every seven working Texans and contributes $100 billion to Texas each year. Texas producers export live animals and meat, hides and skins, cotton and cottonseed, feed grains and products, and wheat and wheat products.
Below is an overview of AgriLife Research projects to apply remote sensing to precision agriculture and the management of natural resources.
Before we get to these projects, why are “remote sensing” and “precision agriculture” often mentioned together, sometimes interchangeably?
Remote sensing and precision agriculture share several common goals, technologies, and benefits.
Remote sensing involves
- sensors and recording devices—such as visual or infrared cameras
- platforms—ground, aerial, or space vehicles to carry the sensors
- equipment and methods for data storage, analysis, and interpretation
- a wide variety of applications beyond agriculture
- the possibility of tracking individual plants or animals over time
Remote sensing is not only used in agriculture, and one well-known example of remote sensing is radar.
- involves measuring varying aspects of a field (soil properties, elevation, crop conditions, etc.)
- applying optimized amounts of water, fertilizer, or pesticides in each area
- has traditionally employed sensors to measure field variability
- was enabled by the development of GPS and other sensing and automatic-control technologies
Precision agriculture aims to match farming practices to crop needs, which decreases costs and environmental risks. Improved remote sensing technologies can help with these goals by providing more highly detailed data more often.
How exactly can remote sensing help precision agriculture?
One major agricultural challenge is the data gathering and analysis involved in growing and breeding crops.
Looking at the life cycle of individual plants can enable plant breeders to pinpoint the most productive plants in various conditions and analyze these plant superstars’ genes. Researchers can use this information to breed plants that are better suited to various conditions.
To track each plant throughout its life, plant breeders could continually visit every plant with a ruler and take careful notes. Or, a remote sensing system could automatically visit hundreds of thousands of plants and record and analyze all the data. In short, new remote-sensing technologies enable high-throughput phenotyping. This approach allows breeders and geneticists to more quickly improve crops to make them more productive, drought-tolerant, and disease- and insect-resistant.
What’s more, remote sensing should be able to detect sick plants (by their color, their temperature, or, potentially, the chemicals they emit) to help direct the application of pesticides. Remote sensing can also help forecast the best time for harvesting by tracking the changing size or color of fruits.
Besides having many applications related to crops, remote sensing can also be used to track the numbers, locations, and health of animals; the numbers and types of invasive species; and the quality of forage.
So remote sensing can help with managing natural resources, too?
Yes. Remote sensing should be able to help monitor wildlife and forests, invasive species, water quality and quantity, and more.
Is remote sensing being used in all these ways now?
While remote sensing is being employed in precision agriculture, low data resolution and high cost have precluded many possible applications.
Remote sensing is starting to benefit from unmanned aircraft, which can collect more and higher-resolution images because they fly lower and slower than manned aircraft.
Researchers around the world are developing better sensors and platforms that allow for greater resolution. They are also finding better ways to store, transmit, analyze, and interpret astronomical amounts of data.
Ok, then. What are the remote sensing projects at AgriLife Research?
AgriLife researchers are involved in two large collaborations to develop remote sensing for precision agriculture and the management of natural resources. The teams are working near College Station and Corpus Christi, among other locations.
The Texas A&M Coordinated Agricultural Unmanned Aerial Systems Project (TAM-CAUAS) and Ground Vehicle Validation is a collaboration of more than 40 faculty members within The Texas A&M University System. Initiated and funded largely by AgriLife Research, the project also involves the Texas Engineering Experiment Station, the Center for Autonomous Vehicles and Sensor Systems, and the Center for Geospatial Applications and Technologies, as well as businesses and farmers. The research centers on an AgriLife research farm in Burleson County that grows 1,400 acres of corn, cotton, peaches, perennial grasses, sorghum, and wheat.
The other prominent collaboration involves the Texas A&M AgriLife Research and Extension Centers at Corpus Christi and Weslaco, Texas A&M University-Corpus Christi, and Texas A&M University-Kingsville. Using small test plots, this team is examining how remote sensing can help improve crop performance and rangeland management.
What did the teams accomplish this year in remote sensing?
The teams have accomplished much in the past year:
- Identified invasive plants in a field
- Measured stress tolerance in winter wheat
- Monitored the growth, maturity, and health of sorghum and cotton from planting to harvest
- Quantified crop height in sorghum and corn using two aerial systems
- Flew more than 100 research flights using unmanned aerial systems (UAS) after being granted Certificates of Authorization by the FAA in 2015
- Developed the first ground vehicle to clear mature corn and sorghum and sensor suites to validate findings made by UAS
- Developed optimal flight paths and ground control points for UAS
What will these teams work on next?
In 2016–2017, the teams plan to do all of the following:
Identifying farmers’ most pressing and relevant management needs
- In corn, measuring earliness, seedling vigor, stand counts, height, growth curves, and drought and heat resistance
- In cotton, assessing defoliation timing, nutrient optimization, irrigation timing, and root rot
- With sorghum, detecting biomass yield, grain yield, growth patterns, plant height, and sugarcane aphids
- In wheat, measuring stress tolerance, disease resistance, wheat rust, and yield potential
- In rangelands, quantifying biomass and maturity, distinguishing grass from invasive weeds, and determining the health or quality of pasture (fertility, drought, diseases)
- Identifying light wavelengths most useful for predicting stress in crops
- Identifying strategies for managing crop stress across different soil types
- Testing sensors to improve 3-D analysis of individual plants
And below are the teams’ longer-term goals:
- Improving the ability to translate data into quick corrective actions in the field
- Developing automated procedures to quantify crop responses to experimental treatments and assist in the selection of elite genotypes
- Monitoring the number, location, and health of animals
- Managing the carrying capacity of pastures
- Quickly detecting and differentiating between production constraints (water, fertility, diseases)
- Measuring the interactions between biotic and abiotic production constraints, such as insects and water
- Quantifying stressor severity
- Developing software to extract data and analyze seasonal changes in plant height, canopy cover, plant color, and canopy temperature
- Evaluating sensors and developing software to analyze cotton maturity, open boll counts, and yield
- Developing new precision management applications
- Integrating crop simulation models with remote sensing applications
Our remote sensing projects have reached the stage where they need more substantial funding to grow. The teams are finding commercial partners and applying for competitive government grants.