Barath Raghavan, an associate teacher at USC Viterbi, is pioneering “computational agroecology,” a novel technique to sustainable farming that makes use of computational tools to design varied, optimum farming environments. The researchers have conceived agriculture as a search through a “state area,” which makes up all possible configurations of a system, such as a farm, making it possible for farmers and researchers to check out, imitate and find optimum combinations of various elements like crop selection, soil type, climate condition, irrigation, and insect control, potentially transforming farming planning and strategies.
A computer science study provides an innovative new method to consider farming and its possible benefits for farming.
The difficulty is further enhanced by problems such as environment change, depletion of natural resources, soil degradation, and the ecological impact of fossil fuel-dependent farming. Theres a pushing requirement for change, but the question is, what type should this alter take?
In action to this, Barath Raghavan, an associate teacher of computer system science at USC Viterbi, is turning conventional farming practices on their head. He is spearheading the development of computational tools that might possibly transform the way farmers conceive, implement, and manage sustainable farming techniques.
Horticulture lover and computer researcher Barath Raghavan is reassessing traditional farming practices. Credit: Noe Montes
Raghavan, a member of the California Rare Fruit Growers company, presently grows more than 150 various edible plants in his backyard. A years ago, he began to combine his interests by looking into how computing could make agriculture more sustainable.
Raghavan calls this new area of research study “computational agroecology,” unifying innovation and farming know-how to establish diverse agricultural landscapes based on natural communities. From crop selection to planting to irrigation, the technique allows farmers to check out thousands of various prospective styles to enhance food production without fossil fuel-derived pesticides.
” How can we create an environment that is as productive and sustainable as a natural forest, but instead of producing food for wildlife, its producing food for people?” said Raghavan.
” Its an exceptionally difficult problem due to the fact that creating an ecosystem is a very complex, dynamic, natural system. Were trying to construct computing tools that can determine how environments work, so we can grow food plentifully and sustainably.”
” A completely brand-new method to consider agriculture”
In a brand-new paper recently published in PNAS Nexus, Raghavan and his associates propose “a totally brand-new method to consider farming and the benefits it can have for research and farming,” stated Raghavan.
In this study, the scientists reconceptualize agriculture as an explore a “state area,” which represents all possible configurations of a system– in this context, agricultural land.
To much better comprehend the idea of a state space, think of a box of blocks: each block might be red, blue, or yellow. The state area would consist of all the possible ways to organize these blocks, such as all red, blue, or green, or a combination of the 3 colors.
In the very same method, a state space for an agricultural system might consist of all the possible variables that the system can take– such as crop or soil type, weather condition conditions, bug, fertilization, or watering control.
This enables farming researchers and farmers to check out the different paths and methods readily available– taking various “blocks” or variables and positioning them together to see what works.
Essentially, a farming “sandbox” to figure out optimal setups to increase crop yield, improve sustainability, and discover entirely brand-new combinations of crops that grow well together.
For example, the framework enables analytics and machine learning that could allow researchers to analyze the patterns between crop yield and soil moisture content or mimic growing different kinds of crops together for biodiversity.
” Once we can envisage a farm this way, we can then reframe lots of research concerns and farming preparing questions as an explore the area of all possible states the farm could perhaps wind up in, with certain states being more desirable than others,” stated Raghavan.
” This permits us to compare and contrast different approaches to farming, check out and combine techniques, and after that search the state space in simulation for brand-new farming techniques that have actually never been attempted before and where trial and error in the real life would be far too costly and lengthy.”
” Playing a chess game with nature”
In Southern California, farmers have actually just recently found that premium coffee can grow plentifully in between avocado trees. Figuring out the best way to do that, and maybe even add another couple of crops that work well together, is site specific.
” Each farmer does not have the time or ability to do trial and error for years to determine the best way to grow a half lots crops on their land,” stated Raghavan.
” Instead, with the conceptual structure and eventually software structure of state spaces, a farmer could spell out a goal– such as varied harvest with high yield and possible high earnings for a specific piece of land– and have the system check out the state area and produce possible plant mixes, placement, and management strategies that meet the farmers requirements.”
Raghavan compares the process to “playing a chess game with nature, but one that is both competitive and collective.”
” Youre making relocations on the chessboard, which is your land, and nature is making moves too. Bugs are going to consume one crop; a flood is going to damage another. What we are constructing is a computational structure that permits you to check out all the various ways that you might play this video game of chess with nature so that we can create the finest one for your land.”
The group consisting of Raghavan recently received a grant from the U.S. Department of Agricultures National Institute of Food and Agriculture for their research study in this area. Now, the group is overcoming possible usage cases with farmers and scientists to incorporate specific use cases and to develop software that can make it simple to explore and mimic state spaces.
Reference: “State areas for farming: A meta-systematic style automation structure” by Bryan Runck, Adam Streed, Diane R Wang, Patrick M Ewing, Michael B Kantar Barath Raghavan, 16 March 2023, PNAS Nexus.DOI: 10.1093/ pnasnexus/pgad084.
The challenge is further magnified by problems such as climate modification, exhaustion of natural resources, soil degradation, and the ecological effect of fossil fuel-dependent agriculture. Theres a pushing need for modification, however the concern is, what form should this alter take?
” Youre making relocations on the chessboard, which is your land, and nature is making moves too. Pests are going to consume one crop; a flood is going to damage another. What we are constructing is a computational structure that permits you to explore all the different methods that you might play this game of chess with nature so that we can come up with the finest one for your land.”