BASF’s vegetable seeds business and IUNU partner to advance digital phenotyping for the elevation and breeding of hydroponic lettuce varieties

The demand for high-quality, high-yielding, and sustainably produced vegetables continues to rise. BASF has long believed that to deliver seeds at the highest caliber and meet this rising demand, breeding must be data-driven. BASF chose to implement IUNU’s LUNA AI system in its breeding greenhouses to develop quantitative data on how plants are growing and to develop growth recipes for each individual variety.

“Growers who work with BASF Agricultural Solutions will benefit from this partnership”, says Adam Greenberg, CEO of IUNU. LUNA AI will facilitate BASF's efforts to accelerate lettuce breeding and variety development, which in turn make their way into your greenhouses. And beyond the quality of seed, those customers who have a LUNA AI system in their greenhouse will be able to work with BASF to create ideal growing environments based on recipes developed in the breeding facilities,”

According to Dr. Ena Hartig, Vice-President of R&D Vegetable Seeds, BASF, the overarching goal is to better position our hydroponic lettuce portfolio with our customers. “By implementing IUNU’s LUNA AI technology, we generate accurate and objective data about the performance of our varieties in similar growing systems and conditions to our customers", says Hartig.

BASF uses LUNA AI to continuously monitor and measure plant performance and to deliver these insights on plant performance to its lettuce customers. 

The world demands more production, but we have fewer growers and face continued labor shortages. Greenhouse and vertical farming customers are increasingly moving toward autonomous growing to produce more and better products without adding labor. Technologies like LUNA AI augment the best grower capabilities and help growers scale up production.

The collaboration fits the digital strategy of BASF's Vegetable Seeds Business to improve data-driven decision-making through collaboration with partners. “By developing and applying algorithms with additional phenotyping, our breeding teams will improve the output of our predictive breeding efforts,” says Hartig, “In our predictive breeding we bring together platforms and tools such as phenotyping, genomic selection, and statistics to help breeders make data-driven predictions of which lines will perform best in a given situation”