Research Of Optimization Modelling Methods On Determination Of Fruit Quality By Visible And Near Infrared Spectroscopy

Fruit,as an important food source,is more and more important.Visible and near infrared spectroscopy(Vis-NIR)technology has been widely used by testing fruit quality because of its advantages of lossless,fast and environment-friendly.At the same time,the paper has been published for many years and the actual application has become old news.However,some problems still need to be solved due to the diversity,complexity and particularity of fruit.For example,a model is used to predict the quality of different varieties or similar fruits to optimize the model’s adaptability;the model’s variable dimension is simplified through scientific and reasonable processing of data;the introduction of new optimization thinking reflects the objectivity and comprehensiveness of fruit quality evaluation;the accuracy of the model is improved through some measures.The specific results are as follows:(1).On the basis of the particularity of fruit samples and combing with data of pear samples,three aspects were puted forward the operation details.These three aspects are sample information collection,information correlation and information prediction.The above laid the theoretical foundation for the further researches.(2).Development and research of general quantitative model.Three different varieties of melons(Manao,Jinhongbao and Xizhoumi)were selected to study the generality of fruit quantitative prediction model.After the spectral pretreatments,the spectral consistency,the corresponding chemical information and the penetrating capacity of the spectrum were considered.A general model of SSC of three melon was established in the preselected 750 nm～950 nm band,and it was concluded that the stylar-end of melon was more suitable for evaluating its quality.The 24 variables were selected by the competitive adaptive reweighted sampling(CARS)algorithm,and most of the selected variables had certain physical and chemical meanings,while there was a large regression coefficient.The results showed that the accuracy and reliability of the model were improved to some extent after variables selection.(3).Variable simplification and research of discriminant model.Using the Vis-NIR to conduct a diffuse transmission of the sample,the PLS-LDA model was used to distinguish the browning of the"Fuji" apple without damaging the sample.Through the competitive adaptive reweighted sampling(CARS)algorithm,0.34%of the variables could be selected effectively to judge the browning of apple,and the accuracy rate was 100%.It is simpler to judge the browning model by integrating peak area(PA),which is less accurate than the CARS-PLS-LDA model.Compared with the full-wavelength model,the accuracy rate of PA-PLS-LDA model was also improved,and it could meet certain requirements.(4).Development and research of comprehensive factor index model.Quality parameters in ’Friar’plums were assessed non-destructively during low temperature storage using Vis-NIR.Throughcorrelation coefficient method,the effective band of each parameter was selected to model and therelationship between parameters was revealed through regression coefficient curves.The parameters’factor weightings were calculated using factor analysis(FA)to build a comprehensive PLS model forfurther assessment.The comprehensive PLS model could not only preliminarily predict the variousparameters of the ’Friar’ plums during low temperature storage,but also could predict the physiological status of ’Friar’ plums,which realized the feasibility of establishing comprehensive prediction model.(5).Optimization and research of color compensation model.Focusing on phenomenon of several parameters changes of the ’Friar’ plums during low temperature storage period.The correlations among parameters were revealed through a variety of data processing methods,and the factors influencing the non-destructive testing model of visible/near-infrared spectra were proposed.The results showed it had a certain relationship among parameters during the low temperature storage period except SSC,and each parameter had a different degree of correlation with the three color parameters(L*,a*,b*).Through the analysis of the two dimensional visible and near-infrared correlation spectra,the change of color and the change of the flesh parameters were mutually influenced,and the color changed faster than other chemical and physical parameters of flesh.Through the primary data fusion technology,the flesh color compensation PLS model was established.According to the model results,except SSC,the flesh color compensation PLS model of other parameters had a certain degree to improve the accuracy of the model.