Jeff Jeffers, Director of ADAI's Shipping Point Inspection (SPI) Division, carries particular weight because of who it comes from: the team that runs farmer stock peanut grading across Alabama, and one that hasn't watched See Produce from a distance, but has observed and worked alongside the company throughout development.
What ADAI found
Director Jeffers writes that See Produce's prototype foreign-material sorting system, which uses AI camera-based learning technology, identifies and separates foreign material, loose-shelled kernels, and in-shell peanuts "with impressive accuracy.
The letter singles out the system's ability to recognize raisins, underdeveloped peanuts that fool the untrained eye, and correctly classify them as foreign material in line with current grading standards, a level of precision Director Jeffers says reflects both a deep understanding of peanut grading requirements and a strong application of machine learning.
ADAI also notes progress beyond foreign material sorting: identifying damaged peanuts and accurately counting individual peanuts within an image, a capability that could replace the traditional seed-counting methods used in shelled stock inspection today. And it points to See Produce's broader vision of integrating multiple grading machines into a single, streamlined system that could meaningfully modernize grading room operations.
What comes next
The letter also credits the collaborations behind the work, noting that See Produce has worked closely with ADAI's Shipping Point Inspection Division, the USDA Agricultural Research Service (ARS), and HudsonAlpha in Alabama, partnerships Director Jeffers says reflect both the credibility of the work and the trust See Produce has built within the agricultural and research communities. Looking ahead, the letter confirms that See Produce is working toward deploying multiple prototype units across Georgia, Alabama, and Florida for evaluation during the 2026 Farmers' Stock season.
Director Jeffers closes with his own assessment: he calls See Produce a forward-thinking, highly capable team whose work has the potential to meaningfully impact the efficiency and effectiveness of agricultural inspection programs, and says the technology warrants serious consideration and support from stakeholders interested in advancing agricultural innovation.
