The Blossoming Potential of AI in Strawberry Production

Exclusives from Urban Ag News

By Tom Trush

Strawberry production in the controlled environment agriculture industry is poised for a transformative shift, thanks to advancements in artificial intelligence. 

As one of the most popular fruits globally, strawberries present unique challenges for commercial growers. Among the greatest is the ability to consistently produce high enough yields to be profitable.

Global production of strawberries (1961–2020) in million tonnes, showing production in each of the five continents (Source: FAO, 2023)

Key reasons contributing to this challenge include:

  • Fluctuating strawberry prices make it difficult for growers to predict profitability.
  • Shortages in labor, especially for harvesting, can affect yield and profitability.
  • Inconsistencies in temperature, humidity or light can reduce yield.
  • Pest and disease management can be costly and time-consuming.
  • Strawberries must reach the market while still fresh.
  • Production requires significant resources.

The fresh produce industry, including strawberry growers, struggles with predicting shelf life. According to OneThird, a Dutch tech firm, retailers often lose 10-40% of their profits from having to discard fruits and vegetables, including strawberries. 

This results in financial losses and has significant environmental costs, such as excessive fresh water consumption and CO2 emissions​​.

The shortage of fruit pickers has led to an increased interest in automated solutions such as crop-picking robots. For instance, a strawberry harvesting robot developed by Organifarms, named BERRY, uses image recognition software to determine which fruits are ready for harvest​​.

BERRY can assess ripeness, size, shape and the presence of defects in each strawberry. Beyond just picking strawberries, the robot also places them into containers. An integrated balance system ensures each one is properly filled.

The Role of AI in Overcoming Strawberry Growing Challenges

AI continues to help reshape strawberry production in controlled environments. Researchers in Taiwan have used AI to optimize growing conditions for white strawberries, resulting in loss rates dropping from 70% to 20%. This shows the potential of AI in enhancing crop yields and sustainability​​​​. 

Competitions in China have also highlighted AI’s effectiveness, with startups going head-to-head against experienced farmers to demonstrate capabilities in improving strawberry growth​​.

One example is the Duo Duo Smart Agriculture Competition in 2020. Organized by Pinduoduo and the China Agricultural University, the competition was held in collaboration with the United Nations’ Food and Agriculture Organization. Yield, taste and cost-effectiveness were the primary focus.

The AI teams registered a 175% higher growth rate in strawberry production compared to traditional methods. This was achieved by leveraging AI algorithms to control growth, demonstrating the impact AI can have on efficiency and productivity. 

The competition also highlighted the potential for earlier market access for strawberries, which could result in pricing advantages.

These developments in China’s strawberry cultivation underscore the role AI can play in modernizing agriculture. They provide insights and strategies growers can adapt to enhance food production and sustainability.

Besides growing conditions, optimizing both the climate and plant rootzone is also crucial for high-yield and quality strawberry production. Rootzone management includes factors such as moisture content, dissolved oxygen, nutrient concentration and temperature.

Dr. Youbin Zheng, environmental horticulture professor at the University of Guelph, explains that almost all crop husbandry in controlled environment plant production is based on human inputs, such as experience and available time for managing the climate and rootzone. Therefore, in intensive controlled environment production systems, the climate and rootzone are often far from optimized.

“AI can be used for controlling the climate system and fertigation automatically, with precise management of upstream, midstream and downstream data,” Zheng said. “Real-time data from sensor arrays in the berry greenhouses allow for intuitive integration of AI into greenhouse operations, assisting growers in making more logical, site-specific and data-based crop management decisions.”

Naturally, since controlled environment strawberry production is still an emerging sector, the use of AI in the field is equally new. For AI to be effective, gathering data is essential for future applications. 

For instance, Zheng points to the need for scientific data to prevent conditions such as strawberry tip burn. This is especially needed because the issue doesn’t appear immediately. Instead, it develops over time due to environmental conditions. 

“Without data, AI can’t preemptively avoid these harmful conditions, impacting plant health and yield,” Zheng added.

Dr. Chieri Kubota, a professor in the Department of Horticulture and Crop Science, and director of the Ohio Controlled Environment Agriculture Center at the Ohio State University, agrees that more data is necessary before growers can fully integrate AI into strawberry production.

“Data and knowledge on strawberry growth and development under controlled environments are still limited and, therefore, applications of AI are limited also,” she said. 

Besides data, she points to needing more physiological knowledge, particularly plant responses to environmental conditions.

In line with Kubota’s observations, one aspect that requires attention is the gap in knowledge about strawberries’ responses to environmental variables such as light and temperature. These factors are critical due to the crop’s sensitivity. 

In particular, different strawberry cultivars exhibit varying flowering responses, where light and temperature are significant influences. This specificity in response is important, says M.S. Karla Garcia, technical service specialist and consultant at Hort Americas, because greenhouse strawberry production is such a relatively new area of focus. 

“Most strawberry cultivars have been studied and classified based on their performance in field conditions,” she said. “So there’s a pressing need for cultivar-specific research to understand and effectively manage each type in controlled environments.”

Currently, Kubota’s team at OSU is collaborating with Koidra, a key player in AI-driven agriculture, to explore innovative ways for optimizing plant growth. Their focus includes understanding plant responses to various environmental factors and integrating this knowledge into AI algorithms. 

This collaboration aims to bridge the gap between current agricultural practices and advanced AI applications, paving the way for more efficient and sustainable production. 

Koidra’s Role in the Homegrown Innovation Challenge

Koidra is also seeking to make significant strides in strawberry production through the Homegrown Innovation Challenge. The challenge is aimed at extending the growing season of berries in Canada, addressing the country’s reliance on imported fresh produce and enhancing food security. 

Koidra’s project, “Autonomous Controlled Environment System for Year-Round Berry Production,” is being done in collaboration with Dr. Youbin Zheng and Dr. Xiuming Hao from Agriculture and Agri-Food Canada​​.

The team working under the project title “Autonomous Controlled Environment System for Year-Round Berry Production” in the Homegrown Innovation Challenge (Source: Koidra)

“Using advanced AI technology, our goal is not just to enhance yields,” said Koidra CEO, Kenneth Tran. “We’re looking to build off our success in previous projects to further define what’s possible in controlled environment agriculture. With strawberries, we’re striving for greater efficiency, sustainability and profitability.” 

Koidra’s AI solutions refine and optimize environmental parameters in greenhouses, such as temperature and CO2 levels, ensuring ideal growth conditions. This increases yield while also enhancing resource efficiency, making the growing process more sustainable​​. 

The company’s previous successes in autonomous greenhouse challenges with cucumbers and lettuce, where they achieved record yields and sustainability ratings, demonstrate the potential impact of their technology on strawberry growing​​.

The Future of AI in Strawberry Production

The integration of AI in strawberry farming is a step toward sustainable berry farming. It also represents a leap forward in the future of agriculture. 

The Homegrown Innovation Challenge underscores the need for education and collaboration in Canadian agriculture, setting a precedent for global agricultural practices. This initiative illustrates the key role of tech innovators and growers in shaping the future of food production​​​​.

AI offers a promising solution to the challenges faced by strawberry growers, particularly in controlled environment agriculture. Through initiatives such as the Homegrown Innovation Challenge and the pioneering work of companies such as Koidra, the strawberry industry is expected to see significant advancements. 

As AI continues to evolve, its role in agriculture is sure to expand, offering new opportunities for growers and contributing to a more sustainable and efficient food production system.

1 thought on “The Blossoming Potential of AI in Strawberry Production

  1. GM Strawberry that’s 2oz size, sweet and juicy ought to be genetically modified to be grown in AI controlled hydroponic environment together with Berry to pick strawberry

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.