A Review of Analyzing Different Agricultural Crop Yields Using Artificial Intelligence

The advancement of Artificial Intelligence (AI), in particular Deep Learning (DL), has made it possible to interpret gathered data more quickly and effectively in this new digital era. To draw attention to development advancements in deep learning across many industries. Agriculture has been one of the most affected areas in recent advancements of the current globalized world agriculture plays a vital role and makes significant contributions. Over the years, agriculture has faced several difficulties in meeting the growing demands of the global people, which has creased over the last 50 years. Different forecasts have been made regarding this extraordinary population expansion which is expected to grasp almost 9 billion persons worldwide by 2050. More than a century ago, different technologies were brought into agriculture to solve issues related to crop cultivation. Many mechanical technologies are accessible today, and they are evolving at an amazing rate. To support their demands and help them optimize their crop yields based on data and task automation need innovative techniques to aid farmers. This will transform the agricultural industry into a new dimension. Therefore, this study’s primary goal was to present a thorough summary of the most current developments based on research interconnected with the digitization of agriculture for crop yields including fruit counting, crop management, water management, weed identification, soil management, seed categorization, disease detection, yield forecasting and harvesting of yields based on Artificial Intelligence Techniques.

@article{Bathini2025,
  title     = {A Review of Analyzing Different Agricultural Crop Yields Using Artificial Intelligence},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {1},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Vijaya Bathini and K. Usha Rani},
  doi       = {10.14569/IJACSA.2025.01601122},
  url       = {https://doi.org/10.14569/IJACSA.2025.01601122}
}