Artificial Intelligence in Agriculture Prof Dr Majeed Kadhim Abbas   Agriculture and its development, a fundamental economic consideration for any country, remains a major challenge today. It is estimated that more than 820 million people suffer from hunger.Furthermore, with the world's population projected to reach 9.1 billion by 2050, this will necessitate 70% more food production. In addition to the anticipated investments in agriculture, further investments will be required, otherwise, around 370 million people will suffer from hunger in 2050. The gap between increasing water demand and available water supplies is also expected to widen, and more than three billion people are likely to suffer from water scarcity in the foreseeable future.               The term "artificial intelligence" was first introduced at the Dartmouth Conference in 1955, where John McCarthy proposed conducting a study based on the premise that "every aspect of learning or any other feature of intelligence can be accurately described, in principle, so that a machine can be created to simulate it.” The definition of artificial intelligence has changed over time due to its rapid development. There is no single, universally accepted definition yet; however, commonly used definitions can be categorized into four main groups: artificial intelligence is a system that thinks like a human. it behaves like a human, and thinks or acts rationally. Artificial intelligence has also been defined as "a program that is worse than a human in dealing with a random world," meaning that artificial intelligence is a set of programs, with inputs and outputs, and also exists in a specific environment.                                                        Some applications of artificial intelligence include intelligent database retrieval, expert consulting systems, theorem proof, robotics, machine programming, scheduling problems, perception problems, etc. Currently, artificial intelligence, as a core area of computer science, has penetrated a variety of fields, such as education, healthcare, finance and manufacturing, due to its ability to handle problems that humans cannot solve efficiently.                   McKinion and Lemmon first attempted to apply artificial intelligence to agriculture in 1985 to create GOSSYM, a simulation model of the cotton crop using an expert system to improve cotton production under specific irrigation conditions,fertilization, weed control, climate, and other factors. In the current state of artificial intelligence in agriculture, three significant achievements can be highlighted: soil management, weed management, and the use of the Internet of Things.                                                                                                                       Soil management: Soil is one of the most important factors for successful agriculture. As the primary source of nutrients, soil stores water, nitrogen, phosphorus, potassium, and other essential materials for healthy crop growth and development. Through proper soil management, negative factors, such as pathogens and soil-borne pollutants, can be reduced. For example, artificial intelligence can be used to map soils, helping to clarify the needs and relationships between different soil layers and their proportions underground. Weed management: Weeds are one of the biggest factors that reduce a farmer's expected profit. For example, if weed infestations are not controlled, there may be a 50% reduction in the yield of bean and corn crops. Competition from weeds can also cause a 48% decrease in wheat yield. Weeds compete with crops for resources such as water, nutrients, and sunlight, and some are even toxic and a threat to public health. Although spraying is often used to control weeds, however, it has a potential negative impact on public health, and its overuse can pollute the environment.Prof Dr Majeed Kadhim Abbas   Agriculture and its development, a fundamental economic consideration for any country, remains a major challenge today. It is estimated that more than 820 million people suffer from hunger.Furthermore, with the world's population projected to reach 9.1 billion by 2050, this will necessitate 70% more food production. In addition to the anticipated investments in agriculture, further investments will be required, otherwise, around 370 million people will suffer from hunger in 2050. The gap between increasing water demand and available water supplies is also expected to widen, and more than three billion people are likely to suffer from water scarcity in the foreseeable future.               The term "artificial intelligence" was first introduced at the Dartmouth Conference in 1955, where John McCarthy proposed conducting a study based on the premise that "every aspect of learning or any other feature of intelligence can be accurately described, in principle, so that a machine can be created to simulate it.” The definition of artificial intelligence has changed over time due to its rapid development. There is no single, universally accepted definition yet; however, commonly used definitions can be categorized into four main groups: artificial intelligence is a system that thinks like a human. it behaves like a human, and thinks or acts rationally. Artificial intelligence has also been defined as "a program that is worse than a human in dealing with a random world," meaning that artificial intelligence is a set of programs, with inputs and outputs, and also exists in a specific environment.                                                        Some applications of artificial intelligence include intelligent database retrieval, expert consulting systems, theorem proof, robotics, machine programming, scheduling problems, perception problems, etc. Currently, artificial intelligence, as a core area of computer science, has penetrated a variety of fields, such as education, healthcare, finance and manufacturing, due to its ability to handle problems that humans cannot solve efficiently.                   McKinion and Lemmon first attempted to apply artificial intelligence to agriculture in 1985 to create GOSSYM, a simulation model of the cotton crop using an expert system to improve cotton production under specific irrigation conditions,fertilization, weed control, climate, and other factors. In the current state of artificial intelligence in agriculture, three significant achievements can be highlighted: soil management, weed management, and the use of the Internet of Things.                                                                                                                       Soil management: Soil is one of the most important factors for successful agriculture. As the primary source of nutrients, soil stores water, nitrogen, phosphorus, potassium, and other essential materials for healthy crop growth and development. Through proper soil management, negative factors, such as pathogens and soil-borne pollutants, can be reduced. For example, artificial intelligence can be used to map soils, helping to clarify the needs and relationships between different soil layers and their proportions underground. Weed management: Weeds are one of the biggest factors that reduce a farmer's expected profit. For example, if weed infestations are not controlled, there may be a 50% reduction in the yield of bean and corn crops. Competition from weeds can also cause a 48% decrease in wheat yield. Weeds compete with crops for resources such as water, nutrients, and sunlight, and some are even toxic and a threat to public health. Although spraying is often used to control weeds, however, it has a potential negative impact on public health, and its overuse can pollute the environment. University of Al-Mustaqbal, ranked first among private universities in Iraq