| 1 | Students become familiar with the fundamental components of digital imaging in agriculture—such as pixel structure, color spaces, and image preprocessing techniques—and grasp the theoretical underpinnings of these concepts within smart greenhouse production processes. |
| 2 | Students collect agricultural data by effectively using image processing hardware and analyze the structural characteristics of this data in a digital environment. |
| 3 | By learning AI-based object recognition algorithms, students explain the chemical or biological changes involved in plant health analysis and maturity detection processes using visual data. |
| 4 | Students relate productivity and developmental processes in plant physiology to digital imaging methods and apply principles for identifying potential developmental issues and deficiencies in plants. |
| 5 | Students identify productivity issues and stress conditions encountered in agricultural production using image processing technologies and develop sustainable solution proposals. |
| 6 | Students develop an awareness of professional responsibility while conducting agricultural analyses—using appropriate imaging techniques in Agriculture 4.0 and smart greenhouse applications—and determining productivity-focused digital management strategies. |