Application of Artificial Neural Network in Agricultural

With the need for farming to become more efficient and environmentally sustainable to meet the demands of a growing global population, the application of artificial neural networks (ANNs) to inform and enhance agricultural practice and production is gathering momentum and interest.

This Reprint titled "Application of Artificial Neural Network in Agriculture" showcases fourteen high-quality research articles highlighting the use of ANNs and related technologies for pest detection, plant disease detection, nutritional monitoring and prediction, the classification of the phenology of beans, and the optimisation of egg production. We also present how ANNs may be used for predicting the power requirements of agricultural machinery and for dynamic behaviour forecasting of an indirect solar dryer.

The multidisciplinary nature of the articles presented will likely strongly appeal to researchers and scientists working in the areas of agricultural technology, communications engineering, computer science, data analytics, electronic engineering, information technology, image processing, and mathematical modelling.