Juan Landivar, director of the Texas A&M AgriLife Center in Corpus Christi, opened the 36^th annual Texas Plant Protection Association’s Conference Tuesday with a look into the future of agriculture.

“Artificial intelligence is the future, and Texas A&M AgriLife is uniquely positioned to take advantage of it,” Landivar said.

The possibilities for AI have increased significantly over the last decade, Landivar said during the two-day conference in Bryan, Texas.

He cited three areas where innovation has increased the reliability and efficacy of AI.

The ability to collect data, he said, has been key. “Satellites, drones, and improved sensors have enhanced our ability to collect data for use by AI.”

Juan Landivar, director of the Texas A&M AgriLife Center in Corpus Christi. (Photo by Shelley E. Huguley)

Advanced computer technology also plays a role. Landivar cited a report indicating that in the last eight years computer capacity has increased by 1,000 times.

Third is advancement in data analytics. “We can look for trends and patterns through millions of data points,” he said. “We have an enhanced ability to analyze data. The future is bright.”

He said projections indicate the AI market will experience a 30% growth in the next decade, topping $3 trillion by 2033.

Although agriculture is well positioned to take advantage of that growing market, he said few applications are currently available for growers. “But we are beginning to see agriculture companies develop specific models for agriculture.”

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The challenge for incorporating AI into agriculture is synthesis, using the data to make decisions wisely. “We need idea folks to get that data for the benefit of growers,” he noted.

Synergistic integration of technologies seeks to reduce production risks. Landivar credits graduate students with explaining how that will happen. “Using an AI tool, within seconds, they came up with: ‘Smart farming technologies can collect and analyze a vast amount of data, providing farmers with valuable insights about their operations. Real-time updates on farming practices, mapping, and crop insights allow farmers to better manage their operations and finances.’

“Texas A&M is uniquely positioned to take advantage of AI technology,” Landivar said, and take it to the field and farm office.

He said efforts will extend beyond the ag college and will include computer and data science as well as industry partners.

Landivar explained a prediction model being studied at the Corpus Christi center.

“The Digital Twin model for agriculture predicts outcome,” he said. The field is the physical aspect; data collected by drone, satellite, or other means, make up the digital equivalent.

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“Digital Twin offers the capability to predict yield accurately. A deep learning model can predict, within 10 to 6 weeks of harvest, a very accurate yield estimate, within 5% of real data,” Landivar said.

The model can predict multiple factors within the field, including biomass, carbon sequestration level, irrigation demand, plant growth regulator timing, and crop termination. “It is exciting.”

The Texas A&M Innovation Center will continue to develop means to incorporate the power of computer technology. “We hope to use AI to reduce production costs by analyzing costs and returns to reduce risk through the integration of technology,” Landivar said. “We have the capability to collect and analyze vast amounts of technology.”

He said a 2017 statement from the National Academy of Sciences underscores the opportunities available.

“The growing availability of data presents an opportunity to improve the resilience and efficiency of food and agricultural production on a scale unimaginable even one decade ago.”

And that capability, Landivar added, continues to grow exponentially.