Paddy Doctor: A Visual Image Dataset for Paddy Disease Classification

One of the critical biotic stress factors paddy farmers face is diseases caused by bacteria, fungi, and other organisms. These diseases affect plants' health severely and lead to significant crop loss. Most of these diseases can be identified by regularly observing the leaves and stems under expert supervision. In a country with vast agricultural regions and limited crop protection experts, manual identification of paddy diseases is challenging. Thus, to add a solution to this problem, it is necessary to automate the disease identification process and provide easily accessible decision support tools to enable effective crop protection measures. However, the lack of availability of public datasets with detailed disease information limits the practical implementation of accurate disease detection systems. This paper presents Paddy Doctor, a visual image dataset for identifying paddy diseases. Our dataset contains 13,876 annotated paddy leaf images across ten classes (nine diseases and normal leaf). We benchmarked the Paddy Doctor using a Convolutional Neural Network (CNN) and two transfer learning approaches, VGG16 and MobileNet. The experimental results show that MobileNet achieves the highest classification accuracy of 93.83\%. We release our dataset and reproducible code in the open source for community use

Synthesis of citric acid using novel Aspergillus niveus obtained from agricultural wastes

Fungus belonging to the genus Aspergillus is considered highly important in the production of various types of enzymes and organic acids. Aspergillus species produce organic acids such as citric acid, itaconic acid, and malic acid, which are one of the most important alternate techniques for chemical processes. Citric acid is an important component in the manufacturing process of food and beverages, pharmaceuticals, cosmetics, toiletries, detergents, and other industries. In this work, A.niveus was isolated from the agricultural waste collected in Kotagiri, The Nilgiris, India. Submerged batch fermentation with a range of low-cost substrates, such as wheat flour, corn starch, and sweet potato, was used to successfully synthesize citric acid by the isolated fungus. In addition, production-related factors such as substrate concentration and incubation time were optimized. The maximum yield of citric acid was produced using A. niveus from corn starch at a concentration 7of 120 g/L after 168 hours at pH 3.2. Furthermore, with a degree of extraction of 91.96, citric acid was extracted from fermentation