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The expert lecture titled “Use of Artificial Intelligence in Plant Breeding” was organized with the objective of introducing researchers, faculty members, and students to the emerging role of artificial intelligence (AI) in transforming modern plant breeding practices. The event aimed to bridge the gap between conventional breeding approaches and advanced computational technologies that are increasingly shaping agricultural research and crop improvement programs worldwide.

The session began with an overview of the challenges faced by traditional plant breeding, including long breeding cycles, complex genotype–environment interactions, limitations in phenotyping accuracy, and the increasing demand for climate-resilient and high-yielding crop varieties. The speaker emphasized that while conventional breeding methods have significantly contributed to agricultural productivity, the growing global population, climate change, and shrinking agricultural resources necessitate faster and more precise breeding strategies. In this context, artificial intelligence has emerged as a powerful tool capable of accelerating decision-making and improving selection efficiency.

The expert elaborated on the fundamental concepts of artificial intelligence, machine learning, and deep learning, explaining their relevance to agricultural data analysis. Particular attention was given to the integration of AI with genomics, phenomics, and environmental datasets. The use of AI algorithms in predicting genotype performance, identifying desirable traits, and optimizing parental selection was discussed in detail. Examples were presented demonstrating how machine learning models can analyze large datasets to identify patterns that may not be easily detectable through conventional statistical approaches.