About this Research Topic
While the area of machine learning methods for smart agriculture is a rapidly expanding field of scientific research, several open research questions still need to be discussed and studied. For instance, using and improving machine learning methods for crop disease recognition, pest detection, plant species recognition, crop production prediction, precise fertilization, smart agricultural IoT, food material supply-chain security tracing, crop security, and other important issues in smart agriculture.
This Research Topic will introduce the new achievements with machine learning and artificial intelligence algorithms, experimental technology, software, pipeline model, and intelligent agriculture application. Original research and review articles are welcome.
Potential topics include but are not limited to the following:
• Internet of Things and its Application in Smart Agriculture
• Plant Disease Recognition and Prediction in Smart Agriculture
• Artificial Intelligence in Crop Yield Prediction in Smart Agriculture
• Machine Learning Methods for Plant Species Classification
• Block-chain based Methods for Security in Agricultural
• Deep Learning-based Methods for Plant Disease Recognition and Prediction
• New optimization methods for AI Algorithms in Smart Agriculture
• Robotics and Mechatronics in Smart Agriculture
• Agricultural Digitalization, Digital Twins in Smart Agriculture
• Big Data Technology in Smart Agriculture
• Food Material Supply-chain Security Tracing in Smart Agriculture
• Crop Security in Smart Agriculture
Keywords: Machine learning, Artificial Intelligence, Smart Agriculture, Big Data, Internet of Things
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.