Artificial Intelligence in Tissue Culture Biotechnology and Corn Morphological Characteristics: A Path to a Sustainable Future

Ghasem Ahmadi¹

1) PhD student in Agriculture, Crop Plant Physiological Biotechnology, Azad University

IOI Code : ABFF-ABDEAE
Publication : 9th International Congress of Developing Agriculture, Natural Resources, Environment and Tourism of Iran(9icsda.ir)
Abstract :
    In recent years, AI has been recognized as one of the essential tools in biotechnology and plant tissue culture. This article examines the role of AI in improving the tissue culture process and morphological characteristics of corn, one of the most important crops in the world. Using advanced algorithms and machine learning, AI enables the analysis and optimization of cultivation conditions and helps identify effective patterns in plant growth and development. In this way, farmers can control their land anywhere and make the best decisions with useful information obtained from the tools. The Internet of Things can make agriculture easier, more accurate and with higher quality. That is, smart machines and sensors can recognize the needs of plants individually. Farmers can make separate decisions for each square meter of their land or even each animal and product. In short, the goal of the Internet of Things in the agricultural industry is to make it data-driven in order to perform scientific research and, as a result, increase productivity. The results show that the application of AI can lead to the improvement of desirable traits of corn, including grain size, plant height, and resistance to pests and diseases. This technology not only helps to increase production efficiency and reduce the consumption of natural resources, but also helps to realize food security and sustainable development. Finally, the integration of AI in tissue culture biotechnology, as an innovative solution, can help create a sustainable future that is resilient to environmental challenges.

Keywords : artificial intelligence crop and tissue corn morphology