Maturity Level Classification of Moringa Leaf using DNN Algorithm

An Indian herb known as Moringa oleifera Lam has spread throughout tropical and subtropical areas as a localised therapeutic remedy. The Moringa has been used for millennia and in numerous civilizations all over the world to treat a variety of conditions, including cholera, bronchitis, chest congestion, anaemia, anxiety, asthma, blackheads, and other ailments. The medical benefits of Moringa leaves are plenty. Since Moringa leaf extract will be taken at different stages of the leaf growth, frequent monitoring and detection of the accurate growth level of the leaves required for the medicine or product preparation are paramount. Immature and tender Moringa leaves always exhibit high-quality antioxidant properties and has high vitamin C content than matured Moringa leaf. As the Moringa leaf matures, the colour and leaf texture also varies. The Chlorophyll content of the Moringa leaf varies as the Moringa leaf matures. Although the individual acquires, segregates and identifies the moringa leaf's maturity (tender, mature, immature) by perceiving the visible characteristics, growth and position of the leaves, it is not authentic and reliable at all times. The proposed study presents a moringa leaf classification algorithm by analysing the characteristics and texture of the Moringa leaf. Ten different features of the Moringa leaf are extracted from the leaf images. For classification, leaves of different maturity levels (mature, immature and tender) are used and the classification is done by using Deep Neural Network (DNN) with 98% accuracy.