Clubroot, a devastating soil-borne root disease, in Brassicaceae is caused by Plasmodiophora brassicae Woronin, an obligate biotrophic protist. Plant growth and development, as well as seed yield of Brassica crops,...

To promote sustainable development, the smart city implies a global vision that merges artificial intelligence, big data, decision making, information and communication technology (ICT), and the Internet-of-Things (IOT). These processes above are related for solving real life problems. Food is one of the basic needs of human being. World population is increasing day by day. So it has become important to grow sufficient amount of crops to feed such a huge population. But with the time passing by, plants are affected with various kinds of diseases, which cause great harm to the agricultural plant productions. Beside that many countries economy greatly depends on agricultural productivity and it's also a need for a coun try to attain agricultural productivity of basic agricultural product for the people of that particular country. Detection of plant disease through some automatic technique is beneficial as it requires a large amount of work of monitoring in big farm of crops, and at very early stage itself it detects symptoms of diseases means where they appear on plant leaves. In this paper surveys on different disease classification techniques that can be used for plant leaf disease detection.

Handoff decisions are usually signal strength based because of simplicity and effectiveness. Apart from the conventional techniques, such as threshold and hysteresis based schemes, recently many artificial intelligent techniques such as Fuzzy Logic, Artificial Neural Network (ANN) etc. are also used for taking handoff decision. In this paper, an Artificial Neural Network based handoff algorithm is proposed and its performance is studied. We have used ANN here for taking fast and accurate handoff decision. In our proposed handoff algorithm, Backpropagation Neural Network model is used.The advantages of Back propagation method are its simplicity and reasonable speed. The algorithm is designed, tested and found to give optimum results.Comment: 11 pages. arXiv admin note: text overlap with arXiv:1004.1794 by other author

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Salicylic acid (SA) is an effective elicitor for enhancing product formation in various agricultural practices. This study examined the diverse responses to physiological metabolites and the pathway modifications in broad-spectrum resistance-1 (BSR1) of Cajanus cajan after treatment with SA using a metabolomics technique. The significance of the SA function at the metabolite level was examined by treating C. cajan with various concentrations of SA and germinated by soaking in water for different time periods. The secondary metabolites were recovered and investigated by gas chromatography-mass spectrometry for all the periodic conditions. Chemometric analysis of the collected samples showed that the seeds responded to the SA treatment. Acetic acid increased in germinated seeds after the SA treatment. In addition, the up-regulated metabolite production was downregulated in the C. cajan seeds before germination. The levels of metabolites, including hyacinthin, furaneol, citramalic acid, palmitate, stearate, linoleate, tocopherol, glucobrassicin, syringol, and hydroxy acetophenone, were increased after the SA treatment compared to control. Hence, the SA-treated seedling is a potential bio-factory for nutraceutical products to provide significant health benefits to the human population.