Journal · 2025.04 · 11 min
What Taiwan Can Learn from the Dutch Smart-Greenhouse Model
A country smaller than Taiwan is one of the world’s largest agricultural exporters. The Netherlands relies not on land but on technology — above all, on greenhouses that manage themselves.
Imagine a greenhouse that, in the dead of night with no one there, knows how far to open the vents, how much to water, how much light to add — not science fiction, but what Wageningen University’s “Autonomous Cultivation” programme is building. A country smaller than Taiwan and short of winter light has never relied on land — but on greenhouses that manage themselves.
A Small Country, a Farming Giant
The Netherlands has limited arable land and high labour costs, yet ranks for years among the world’s leading agricultural exporters. The key is upgrading the greenhouse from a “facility” to a “system” — replacing land- and labour-intensity with technology-intensity.
The most closely watched of these efforts is the Autonomous Cultivation in Greenhouse Horticulture programme led by Wageningen University & Research.
Letting the Greenhouse Grow by Itself
The programme’s goal is bold: to build a greenhouse that can self-regulate anywhere in the world. It combines sensors with artificial intelligence (AI) to detect environmental and crop conditions in real time and make climate and cultivation decisions automatically — rather than relying entirely on a master grower’s experience and manual operation.
“A self-regulating greenhouse can maintain stable output while reducing labour, and raise overall labour productivity.”
— Wageningen University & Research
Three Takeaways for Taiwan
The Dutch experience can’t be copied wholesale, but its direction is worth studying. For Taiwanese agriculture, facing labour shortages and climate change, there are at least three lessons:
- Use technology to supplement labour: as rural labour shortages worsen, sensing and automation let limited manpower manage larger areas and make more precise decisions.
- Turn experience into data: convert a master grower’s knowledge into quantifiable, transferable parameters, reducing the risk of a knowledge gap between generations.
- Use stability against extremes: against increasingly violent weather, a controlled, automatically adjustable environment is the key line of defence for yield and quality.
Hwa-Nan believes Taiwan’s next step in agriculture lies not in chasing the flashiest tech buzzwords, but in laying a foundation for every greenhouse that can be operated long-term and upgraded step by step.