Detection of Nutrient Deficiency in Rice Plants Based on Leaf Image
Miftakhul Janah Sulastri, Dwi Ratna Sulistyaningrum, Hendro Nurhadi · 2021
In 2019 the yield of rice production experienced a considerable decline, one of which was caused by weather factors that resulted in drought on the land, so that the absorption of nutrients given to rice plants was not optimal. Seeing developments in the field of image technology, researchers used image processing and computer vision to determine the availability of nutrients contained in the image of rice leaves, by applying the feature extraction method. Feature extraction produces six feature values which are then used for detection using the Learning Vector Quantization (LVQ) method. The detection in this final project can recognize the image of rice plants lacking in nutrients N, P, and K which has an accuracy of 87.5