Fruit Disease Prediction using Artificial Intelligence

  • S. Yagnasree, Amirineni Rama L Padmaja, M. Umarani


Big Data Analytics (BDA) offers a stupendous part where there is a want of rebellious performance in managing massive quantity of facts th at handles 4 traits such as Volume Velocity, Variety and Veracity. Agriculture is one of the fields which generate information constantly protecting all four traits with excellent growth. There are a number of challenges in processing agricultural records which deals with variety of structured and unstructured format. One of the challenges in agriculture industry comprises of fruit disease detection and control. For this purpose, farmers had to monitor fruits continuously from harvest till its growth period. But this task is not an easy one. Hence it requires proposing an efficient clever farming method which will help for better yield and growth with less human efforts. Image processing is a technique which will diagnose and classify external sickness within fruits through various images. For the control of the disease in the initial stage itself several images of the day-to-day condition of the fruit has to be monitored where a slight change calls for a remedy. As the number of images increases obviously big data come into play. This paper discusses the existing system in fruit disease detection and also proposes disease prediction using machine learning over big-data.

How to Cite
S. Yagnasree, Amirineni Rama L Padmaja, M. Umarani. (2022). Fruit Disease Prediction using Artificial Intelligence. Design Engineering, (1), 2501 - 2510. Retrieved from