Fast Recognition Method of Strawberries' Maturity Level Based on Neural Network and Near Infrared Spectra

[Objective] To explore the method for the rapid detection of strawberries' maturity level and the improvement of the automatic strawberry picking level.[Method] The strawberries' spectral information around 350-2 500 nm was collected,and the first derivative of the strawberries' spectral information was drawn for carrying out a principal components analysis.The six points which contributed the largest in the principle components were obtained.The five additional feature points aside each crest feature points were picked out as main feature points,and 58 strawberries were selected randomly to made up a 60×58 array as training set.The array was imported to BP neural network which was built of Matlab for training.[Result] To test the neural network model by the strawberries samples of test set,the distinguishing rate could reach up to 93.1%.[Conclusion] To identify the maturity degree of strawberries by near infrared spectra is practicable.