Iowa State scientists usher in cyber-agricultural future – Iowa State University

Report on Cyber-Agricultural Systems and Alignment with Sustainable Development Goals

Introduction: A New Discipline for Sustainable Agriculture

Researchers at Iowa State University are pioneering a new discipline, Cyber-Agricultural Systems (CAS), to address significant agricultural challenges and foster the development of smart, connected farms. This initiative, led by Professor Soumik Sarkar and Professor Asheesh “Danny” Singh, integrates mathematics, engineering, and computer science to revolutionize agricultural practices. The development of CAS directly supports the achievement of multiple United Nations Sustainable Development Goals (SDGs) by creating more efficient, resilient, and sustainable food production systems.

The Core Framework of Cyber-Agricultural Systems

CAS provides a comprehensive framework that builds upon, yet is distinct from, precision and smart agriculture. As outlined in the journal Trends in Plant Sciences, this framework is defined by three primary components that work in synergy to optimize farm management and resource use.

1. Data Absorption: This involves the collection of vast amounts of data from a multitude of sources, including sensors and cameras on satellites, drones, and ground-based robots. The data captures information on plant health, soil conditions, pests, diseases, weather, and environmental factors, providing a comprehensive digital overview of the agricultural landscape.
2. Modeling: The collected data is utilized to create sophisticated models that can answer critical questions and generate predictive insights into crop performance, resource needs, and potential environmental stressors. This component leverages machine learning and artificial intelligence to turn raw data into actionable intelligence.
3. Decision-Support Applications: Based on the modeling results, digitally-based tools are developed to provide specific recommendations for farm management. These applications assist farmers in making informed decisions, such as identifying a specific plant disease and receiving immediate management recommendations.

Contributions to Global Sustainable Development Goals (SDGs)

The implementation of CAS technologies offers substantial contributions to several key SDGs, transforming agriculture into a more sustainable and productive sector.

• SDG 2: Zero Hunger: CAS directly addresses food security by enhancing agricultural productivity. Technologies such as autonomous tractors guided by soil maps and robotic harvesters enable farmers to achieve higher yields. Advanced systems like the AgGym resource use deep reinforcement learning for precise plant stress mitigation, increasing yield recovery and bolstering the food supply.
• SDG 12: Responsible Consumption and Production: A central tenet of CAS is resource efficiency. By enabling variable-rate planting and tailored fertilizer applications, the system ensures that inputs are used precisely where needed, minimizing waste. This approach helps farmers reduce the use of chemicals and costly inputs, promoting sustainable production patterns and improving their return on investment (ROI).
• SDG 9: Industry, Innovation, and Infrastructure: CAS represents a significant innovation in the agricultural industry. The development of Smart Connected Farms (SCFs), Digital Twins (DTs) for virtual farm modeling, and the integration of the Internet of Things (IoT) are transforming agricultural infrastructure. This technological advancement is critical for building resilient and modern agricultural systems.
• SDG 8: Decent Work and Economic Growth: By automating certain tasks, CAS helps address agricultural labor shortages. More importantly, it fosters economic growth by creating new, high-skilled jobs and career paths in agricultural technology, data science, robotics, and machine learning. Iowa State University is supporting this transition by launching new curricula, courses, and micro-credentials to prepare students for these future opportunities.

Fostering Partnerships for the Goals (SDG 17)

The advancement of CAS is driven by strong multi-stakeholder partnerships, a core principle of SDG 17. This collaborative approach ensures that innovations are relevant, practical, and widely adopted.

• Academic and Industry Collaboration: Researchers at Iowa State University work closely with farmers and agricultural organizations, such as the Iowa Soybean Association (ISA), to co-develop solutions for challenges like adverse weather preparedness and input optimization.
• International Cooperation: The university has been instrumental in organizing international Machine Learning for Cyber-Agricultural Systems (MLCAS) conferences in locations including the United States, India, and Japan, building a global community dedicated to solving agricultural grand challenges.

Future Directions and Challenges

While the field of CAS is advancing rapidly, several areas require further development to realize its full potential. Future work will focus on addressing key challenges and expanding educational outreach.

• Analyzing and securely storing vast amounts of agricultural data.
• Improving rural connectivity to support data-intensive technologies.
• Enhancing digital security to protect farm-level data.
• Establishing clear protocols for controlling and sharing sensitive farm data.

Iowa State University remains at the forefront of this evolution, continuously developing new research initiatives and educational programs through its College of Agriculture and Life Sciences and Extension services to equip the workforce with the skills needed for the future of agriculture.

Which SDGs are addressed or connected to the issues highlighted in the article?

• SDG 2: Zero Hunger

  The article focuses on agricultural innovations like Cyber-Agricultural Systems (CAS) designed to increase farming efficiency and productivity. It explicitly mentions achieving “higher yields with lower inputs,” which directly contributes to ending hunger, achieving food security, and promoting sustainable agriculture.

• SDG 4: Quality Education

  The article highlights the development of new educational programs at Iowa State University to support the growth of CAS. It mentions “new curricula,” “new courses on artificial intelligence,” “micro-credentials,” and “training programs for workforce development” to equip students and workers with the necessary skills for future jobs in this high-tech agricultural sector.

• SDG 8: Decent Work and Economic Growth

  The development and adoption of CAS technologies are presented as a driver of economic growth for the agricultural sector. The article notes that these systems help farmers improve their “ROI” (return on investment) and create “new types of jobs and careers,” contributing to productive employment.

• SDG 9: Industry, Innovation, and Infrastructure

  The core of the article is about innovation in the agricultural industry. It describes the creation of a “new discipline, cyber-agricultural systems (CAS),” which integrates engineering, computer science, and agriculture. It also touches on infrastructure challenges like “rural connectivity” and “digital security” that are crucial for deploying these technologies.

• SDG 12: Responsible Consumption and Production

  The article emphasizes that CAS enables more sustainable production patterns. Technologies like “tractors steering autonomously… to deliver tailored doses of fertilizer” and strategies designed for “less chemicals and at lower cost” point directly to the efficient use of natural resources and the reduction of chemical inputs in farming.

What specific targets under those SDGs can be identified based on the article’s content?

1. SDG 2: Zero Hunger

   • Target 2.3: By 2030, double the agricultural productivity and incomes of small-scale food producers. The article supports this by describing how CAS helps farmers “achieve higher yields with lower inputs” and improve their “ROI,” directly impacting productivity and income.
   • Target 2.4: By 2030, ensure sustainable food production systems and implement resilient agricultural practices. The article discusses creating “response-agile farms” and preparing for “adverse weather,” which aligns with building resilient and sustainable agricultural systems.

2. SDG 4: Quality Education

   • Target 4.4: By 2030, substantially increase the number of youth and adults who have relevant skills, including technical and vocational skills, for employment, decent jobs and entrepreneurship. The article directly addresses this by mentioning the launch of “new curricula,” “courses on artificial intelligence,” and “workforce development” programs to prepare students for “new types of jobs and careers” in CAS.

3. SDG 8: Decent Work and Economic Growth

   • Target 8.2: Achieve higher levels of economic productivity through diversification, technological upgrading and innovation. The entire article is an example of achieving this target through the technological upgrading of the agricultural sector with CAS, leading to increased efficiency and new economic opportunities.

4. SDG 9: Industry, Innovation, and Infrastructure

   • Target 9.5: Enhance scientific research, upgrade the technological capabilities of industrial sectors… and encourage innovation. The article showcases this target through the work at Iowa State University in creating a “new discipline” and developing CAS, supported by research funding from institutions like the USDA and NSF.

5. SDG 12: Responsible Consumption and Production

   • Target 12.2: By 2030, achieve the sustainable management and efficient use of natural resources. The article provides clear examples, such as using “soil maps to deliver tailored doses of fertilizer” and developing strategies that use “less chemicals,” which are direct methods for the efficient use of resources.

Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

1. For Targets 2.3 and 2.4:

   • Crop Yield: The phrase “achieve higher yields” directly implies that crop yield (e.g., bushels per acre) is a key metric for success.
   • Farmer Profitability (ROI): The farmer’s statement that these systems “have a lot of potential to help our ROI” suggests that the return on investment is a measurable indicator of economic viability and productivity.
   • Input Efficiency: The mention of “lower inputs” and “less chemicals” implies that progress can be measured by the reduction in the volume of fertilizers and chemicals used per unit of land or output.

2. For Target 4.4:

   • Number of New Educational Programs: The article mentions “new curricula,” “new courses,” and “micro-credentials.” The number of these programs developed and launched can serve as an indicator of progress.
   • Student Enrollment: The number of students enrolling in these new CAS-related courses and programs would be a direct measure of the increase in adults gaining relevant skills.

3. For Target 9.5:

   • Research and Development Funding: The article explicitly lists funding sources like the “USDA National Institute of Food and Agriculture” and the “National Science Foundation.” The amount of funding dedicated to CAS research is a clear indicator of investment in innovation.
   • Adoption Rate of New Technologies: The mention of farmers as “early adopters of CAS-type equipment” implies that the number or percentage of farms using these technologies (drones, autonomous tractors, etc.) is a key indicator of technological upgrading.

Table of SDGs, Targets, and Indicators

Source: newswise.com