Rapeseed-Mustard is an important oilseed crops and contributes around 23.2 per cent of the total oilseed production in India. The production of Rapeseed-Mustard is widely effected by rapeseed-mustard diseases. Alternaria blight [Alternaria brassicae (Berk.) Sacc.], white rust [Albugo candida (Pers.) Kuntze] and White rot [Sclerotinia sclerotiorum (Lib.) de Bary] downy mildew complex, powdery mildew, white rot of rapeseed-mustard are the diseases that are quoted frequently in the states where the crops are grown in India. The identification of disease is the difficult task. If the diseases identified timely, the control measures can be applied effectively. Now a day the use of digital technology can produce high quality digital images including photos and clips of healthy and infected plants easily that can play very important role in disease identification. Digital images can be seen and shared easily among the experts. Image can be examined on camera screen literally the second they are captured and downloaded to a computer for closer inspection within minutes. In present study a computerised expert tool image based Rapeseed-Mustard disease expert system was developed to help extension personals, researchers and farmers in identification and management of these diseases. The expert system uses a hierarchical classification and a mix of the text description, photographs and artistic pictures. The system involves two main sub-tasks, namely, diagnosis and management. The system designed and developed using Visual Basic as front-end and Microsoft Access-2000 as back-end software

Keyword: Rapeseed-Mustard; Disease