Syngenta is using advanced research technologies, including artificial intelligence (AI), data analytics and robotics, to evaluate new tomato varieties at its TomatoVision research facility in Maasland. The site is focused on collecting and analyzing large volumes of data to support tomato breeding and variety selection, including varieties compatible with automated harvesting systems.
TomatoVision functions primarily as a research and development location. According to Syngenta, approximately 90 percent of activities at the site are dedicated to generating data to support decision-making in tomato breeding.
The facility is an "active greenhouse," meaning its internal climate can be precisely controlled using specialized equipment. This allows researchers to monitor climate conditions, crop performance and yield in detail. Traditional breeding techniques are combined with digital tools and advanced analytics to evaluate varieties at different stages of development, from early concepts through to taste testing.
The greenhouse covers approximately 14,000 square meters and is designed to replicate real-world growing conditions. It includes both lit and unlit cultivation areas, full climate control systems, and dedicated spaces for evaluation and demonstrations. Each year, hundreds of tomato varieties are tested at the site, with only a small percentage—typically between one and three percent—progressing to commercial release.
"This is the place where we see our hybrids for the first time in the right conditions," said Haoyang Duo, Senior Breeder at TomatoVision. "We use molecular markers to increase breeding efficiency and to combine desirable traits more effectively."
Each potential variety is assessed against a defined product profile, which includes criteria such as taste, fruit quality, shelf life, and production characteristics. The objective is to integrate multiple traits into a single hybrid that meets market requirements.
Robotics are also incorporated into the research process. Automated harvesting systems are used to assess how different plant structures perform under machine harvesting conditions. Some tomato varieties grow in dense clusters, which can present challenges for robotic harvesters. Research at TomatoVision aims to identify plant architectures that are more suitable for automation.
Machine learning is used to improve robotic performance over time, allowing systems to adapt to different varieties and harvesting conditions. According to Syngenta, this work is intended to support growers who are exploring automation as a response to labor availability challenges.
In addition to technology-driven research, biological processes remain central to operations. Bees are used for pollination inside the greenhouse, supported by supplemental feeding due to the low pollen levels of tomato flowers. Beneficial insects are also introduced to help manage pests.
The facility operates under strict phytosanitary protocols to protect plants and research activities, particularly in response to tomato brown rugose fruit virus (ToBRFV). The virus can spread rapidly and significantly reduce yield and fruit quality.
Syngenta has been developing tomato varieties with resistance to ToBRFV, including varieties with intermediate resistance launched in recent years. Research continues on developing tomatoes with multiple sources of resistance using conventional breeding methods supported by data-driven tools.
According to Syngenta, the research conducted at TomatoVision is intended to support the development of tomato varieties with improved disease resistance, production efficiency and compatibility with evolving agricultural practices.
For more information:
Syngenta Vegetable Seeds
www.syngentavegetables.com/
