Effectiveness of Generative AI Tool to Determine Fruit Quality: Watermelon Case Study - Serkan Ozdemir (Horticulturae)
To select a good quality watermelon, one needs the ability and experience to recognize specific patterns in its visual characteristics. As buyers usually cannot taste the watermelon beforehand, the outer patterns of a good quality watermelon may vary depending on the perspective of the purchaser. As a result, there is a gradual adoption of new generative artificial intelligence (AI) tools in the field of horticulture. These tools are expected to minimize bias in human perception when determining the quality of a watermelon based on its outer characteristics. This study aimed to compare the quality of watermelons selected by generative AI with a panel sensory evaluation test. The results of the two case studies indicate a significant difference in the quality of the generative AI-selected watermelons. As an average, watermelon evaluators favored the watermelons selected by ChatGPT as the best based on the Wilcoxon rank sum test and paired t-test (p < 0.05). In conclusion, watermelons can be selected by ChatGPT with minimal effort, promptly meeting consumer expectations.