Pc science might help farmers discover different crops and sustainable farming strategies

Chickpeas intercropped with flax on a farm in Stanford, Mont. Credit score: USDA NRCS Montana

People have remodeled half of the world’s land to domesticate eight principal crops: maize (corn), soy, wheat, rice, cassava, sorghum, candy potato, and potato. These crops present nearly all of energy consumed by folks worldwide. With the growing international inhabitants, there’s a have to broaden agricultural manufacturing even additional.

Nonetheless, many consultants argue that increasing fashionable industrialized agriculture, which closely depends on artificial fertilizers, chemical pesticides, and high-yield seeds, shouldn’t be sustainable ecologically or economically. Farmers and scientists really feel trapped in a system that they imagine shouldn’t be the suitable approach to feed a rising world inhabitants.

The problem is creating a meals system that’s each wholesome and various whereas assembly the wants of societies. Scaling up different strategies like natural farming has confirmed troublesome in comparison with industrial agriculture.

As a pc scientist and a crop scientist, we’ve got proposed a brand new method to handle this drawback. Drawing on the idea of abstraction from pc science, which summarizes and organizes information and ideas computationally, we will analyze and take motion with out consistently specializing in inside particulars.

Trendy agriculture quickly intensified within the mid-Twentieth century, due to technological developments comparable to artificial fertilizer and statistical strategies for improved plant breeding. Though this led to elevated meals manufacturing, it additionally had detrimental results on the setting. Massive-scale agriculture contributes to local weather change, water air pollution, and biodiversity loss.

Many farmers and agricultural researchers within the US want to domesticate a wider vary of crops and undertake extra sustainable farming strategies. Nonetheless, they wrestle to determine techniques that carry out properly, significantly in a altering local weather. Sustainable farming techniques require deep native information and complete understanding of crops, climate patterns, local weather modeling, and extra.

Our new method includes viewing agricultural techniques as state areas, an idea generally utilized in pc science to resolve advanced issues. On this framework, a farm and its structure symbolize a single state throughout the state house. Farmers are consistently looking for higher states and avoiding undesirable ones. Each human actions and pure processes shift the farm from one state to a different.

By making use of this state house view, we broaden choices for farmers past the restricted decisions supplied by present farming techniques. Our framework permits customers to think about higher-level methods, comparable to intercropping (rising totally different crops collectively) or discovering administration methods that swimsuit particular items of land. By exploring the state house, farmers can decide the most effective mixture of strategies, species, and places to attain their objectives.

For example, intercropping has proven nice potential, with sure plant combos benefiting one another’s development. Examples embrace the “three sisters” technique utilized by Indigenous farmers, the place corn, beans, and squash are grown collectively. The corn supplies assist for the beans, whereas the squash shades the bottom and prevents weeds. Micro organism on the bean crops’ roots provide nitrogen to all three crops.

Our goal is to rework this framework into software program that allows farmers to mannequin agriculture as state areas. This may assist customers discover different designs and reduce the expensive trial and error at the moment concerned in testing new concepts in farming. The software program will enable customers to specify their targets, and a synthetic intelligence agent will carry out a search throughout the farm state house to determine successful methods.

We imagine that agricultural techniques should not adequately leveraging the wealth of information and plant range obtainable. By combining this data computationally, we will make agriculture extra productive, wholesome, and sustainable in a quickly altering world.

Supplied by: The Dialog

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