Online identification and classification of Gannan navel oranges with Cu contamination by LIBS with IGA-optimized SVM
Lin Huang, Yangfan Chen, Jianbo Wang, Zhandong Cheng, Tao Lei, Huamao Zhou, Jiang Xu, Mingyin Yao, Muhua Liu, Tianbing Chen
Abstract
of SVM. LIBS spectral data from two types of navel orange samples with and without Cu contamination were selected as test datasets, and the classification results were compared with those of the standard genetic algorithm-support vector machine (GA-SVM). The investigation showed that the IGA-SVM can provide better classification of navel oranges based on analysis of the LIBS spectral data, and the classification accuracy can reach 98%, which provides significant guidance for the use of LIBS to quickly realize online screening of heavy metals in agriculture products.
Topics & Concepts
Navel orangeNavelContaminationIdentification (biology)Support vector machineChemistryComputer scienceArtificial intelligenceBotanyHorticultureBiologyAnatomyEcologyIdentification and Quantification in FoodSpectroscopy and Chemometric AnalysesTraditional Chinese Medicine Analysis