The Application of Artificial Neural Network in Plant-Microbe Interaction and Future Crop Health Surveillance

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Plants are the most important constituents of our environment. Despite their function in producing energy by capturing photons from sunlight, they are the only source of atmospheric oxygen by the process of photosynthesis. Since the last 100 years, a huge amount of agrobiodiversity has been lost and many are at risk of extinction. The existing crop plants are also at the constant threat of different biotic and abiotic stress factors. Every year yield of the agricultural crops is curtailed dramatically by changing environmental pressure and associated pathogenic ingression. Many works are carried out in this field to demonstrate defense signaling in plants in response to either biotic or abiotic interactors. Artificial neural networking (ANN) system is a revolutionizing bioinformatic technology that can predict any problem with maximum logic depending on the weights given in different situations. The application of this ANN in predicting biological networks will be capable of changing the scenario of plant infection biology completely. In such context, the present article intends to demonstrate basic ANN and their probable application in future plant-microbe interactions to develop a sustainable agrosystem.