Penn State has started a three-year program to train doctoral fellows as AI 'envoys' to help orchard managers apply AI and precision tools for climate-smart tree-fruit farming. Backed by more than $738,000, the interdisciplinary effort aims to speed pest detection, improve breeding for heat tolerance and share best practices with farmers. The piece also notes environmental trade-offs—AI data centers can consume large amounts of electricity and up to 5 million gallons of water daily—and highlights mitigation options such as renewables, efficiency and household energy upgrades.
Penn State Trains Doctoral 'AI Envoys' To Help Orchards Adapt to Climate Change
Photo Credit: Penn State
Penn State has launched a three-year program to train a handpicked cohort of doctoral fellows as artificial intelligence 'envoys' who will help orchard managers apply AI and precision tools to improve tree-fruit production and adapt to changing climate conditions.
Program Overview
The interdisciplinary initiative, led by associate professor Long He, is supported by more than $738,000 in government and university funding. Fellows will receive training from experts across fields, and gain professional development through research opportunities, mentorship, career planning and public outreach. The program also includes plans for international knowledge-sharing with farmers and industry partners.
'They'll be trained by a diverse team of experts and get opportunities to grow professionally—through research, mentorship, career planning, and public speaking. By the end, these doctoral fellows will become leaders in using AI to improve farming and adapt to climate change,' said Long He, the project leader.
Potential Benefits for Orchards
Broader adoption of AI in tree-fruit farming could speed detection and response to pests, diseases and other stressors made worse by warming temperatures. AI can also accelerate breeding and genetic research: for example, teams at the University of Maryland are developing apple varieties with greater heat tolerance to withstand intensifying heat waves.
Environmental Trade-Offs
At the same time, the computing infrastructure that powers advanced AI requires significant electricity and cooling. Many data centers still draw power from fossil-fuel-heavy grids, and large facilities can consume substantial volumes of water for cooling—reportedly up to 5 million gallons per day, according to the Environmental and Energy Study Institute.
'Just because this is called "cloud computing" doesn't mean the hardware lives in the cloud. Data centers are present in our physical world, and because of their water usage, they have direct and indirect implications for biodiversity,' said Noman Bashir, a fellow and postdoctoral researcher at MIT.
How to Reduce the Footprint
The article highlights ways to lower AI's environmental impact: powering data centers with renewables, improving energy and water efficiency, and using distributed or edge computing where appropriate. Large companies—such as Meta—are investing in renewable electricity for data centers, and homeowners can reduce household emissions by installing rooftop solar and energy-efficient appliances like heat pumps.
Consumer programs and tools (for example, solar-matching services) can help households find vetted installers and compare quotes to lower costs and energy bills.
Public Questions and Program Goals
The use of automation and robotics in food production raises public questions about cost savings, labor impacts and food-system resilience. A key aim of Penn State's program is to build collaborative links among universities, industry and farmers so new AI tools are practical, equitable and environmentally conscious.
'Our hope is that the doctoral students trained in our program emerge as scientists ready to lead innovation in climate-smart agriculture,' He said.
The program seeks to balance innovation with attention to environmental trade-offs, preparing participants to advise farmers and shape how AI is deployed in real-world agriculture.
