Predicting properties of cereals using artificial neural networks: A review

This communication reports the use of artificial neural networks (ANN) in cereals and analyzes the major contribution of ANN in cereals (barley, corn, maze, oats, paddy, rice, rye and wheat) for prediction, forecasting, analysis and assessment, viz., cereal production; cereal yield; cereal quality; moisture; nitrogen and protein in cereals; water requirement of cereals; crop detection; monitoring and positioning; grain identification; grain quality; barley production; colour and tannin; rice husk; forecasting market share; deoxynivalenol content in grain, etc. This article would be very valuable for agriculturalists, cereal researchers, food scientists, nutritionists, academicians and students, so that they can follow a suitable methodology according to their exact requirements for conducting research.