Basil Plant Growth Analysis
Machine Learning technique is used in many applications in agricultural such as yield prediction algorithms, pest and diseases detection, and automatic harvest systemetc. However, not a lot of work can be found applying machine learning technique in plant growth analysis. Plant growth prediction modeling is useful for a better planning and decision making in modernagriculture. In this project, we have planted 12 basil plants and monitored the environmental parameters of the plants through the whole growth cycle in 3 months. A digital plant-growing system was designed to capture the humidity, temperature and image of the plants every 30 minutes. This system is controlled by an Arduino micro-controller, equipped with a camera, humiditysensors, and temperature sensors. The growth of the plants is captured by detecting size of the leaves using computer vision techniques. The relationship between growth of the plants and the environmental parameters is modeled using different machine learning models. A comparison of the modeling results using different models is provided. The relationship between the plant growth and the environmental parameters have been analyzed. The growth behavior learned from growing basil plants can be used as an example to guidegrowing other similar herbal plants in the future. The knowledgegained in this research project and the data analysis method used in this project can be beneficial togrowing plants of other species.
Keywords - Machine Learning, Plant Growth, Prediction, Environmental Parameters