Physiological Properties Of Moldy Core Apple Fruits Flesh And Nondestructive Detection Using Near Infrared Spectroscopy

Moldy core (MC) and core rot (CR), pathogenic disorders associated with the coreregion of fruits, are among the most important postharvest diseases of apple (Malus domestica)and are mainly found in susceptible varieties that have open calyx tubes. Apple fruits werefirst infected in the seed locules, then gradually expanded into fruit flesh and finally resultedin fruit rot. MC and CR of apple fruits are undetectable unless the fruits are cut open or bitteninto because they occurred in the internal of apple fruits (surround seed locules), they can notonly affect fruit quality, cause lower commodity prices, but also may cause damage toconsumers' health, and if the diseased fruits were delivered into the table of consumers, it willhave a negative impact on both producers and consumers, such as loss of consumers trust andloyalty or even lost the market. However, there is no related report on the physiologicalresponses of apple fruits with MC and CR. Therefore, it is necessary to study the fruitphysiological responses caused by apple MC and CR, and to find or establish a reliable,nondestructive method to detecting apple MC and CR fruits.With the "Fuji" apple (Malus domestica cv. Fuji) as materials, this study investigated thecasual agents of apple moldy core, physiological responses of fruit flesh, and nondestructivedetection of apple moldy core and core rot using near infrared spectroscopy. The main resultswere exhibited as follows:(1) After investigation the relationship between MC and CR and apple fruits, the resultsshowed that apple MC and CR occur mainly in fruit diameter is70mm～85mm, fruitheight is60mm～70mm, fruit-shape index is0.80～0.90, and high apple MC and CRincidence rate occurs in circular or near circular apple fruits.(2) In order to clear the casual agents of apple MC and CR, the diseases through isolation,cultivation and pathogenicity experiment, found that the main pathogen caused apple MC andCR are Alternaria alternata, Trichothecium roseum, and/or the combination of Alternariaalternata and Trichothecium roseum.(3) The fruit flesh physiological responses of apple MC and CR was studied, the results indicated that different types of apple MC and CR have different effects on the physiologicalindices of apple fruits flesh. Total phenolic content and ascorbate (AsA) content increasedsignificantly when pathogen infecting apple fruits caused MC. When pathogen infecting applefruits caused dry CR (DCR), Superoxide dismutase (SOD), catalase (CAT), polyphenoloxidase (PPO), ascorbate peroxidase (APX), phenylalanine ammonia-lyase (PAL),β-1,3-glucanase and chitinase activities, and total phenolic content, superoxide radicalproduction of fruit flesh increased significantly; protein content decreased markedly. Whenpathogen infecting apple fruits caused wet CR (WCR), peroxidase (POD) activity and totalphenolic content were increased significantly in asymptomatic tissue of WCR (asympWCR)fruit flesh; in symptomatic tissue of WCR (sympWCR) fruit flesh, membrane permeability,malondialdehyde (MDA) content, β-1,3-glucanase and chitinase activities were increasedsignificantly, thus, APX activity, and the contents of total phenolic, AsA, hydrogen peroxide(H2O2), soluble solid content (SSC), protein content were decreased significantly.(4) Select effective wavenumber range, apple MC and CR discriminant efficiency ofFisher function based on several spectra preprocessing methods (non-preprocess,multiplicative scatter correction (MSC), standard normal variate transformation (SNV), vectornormalization (VN), maximum normalization (MN), area normalization (AN), smoothingwith a segment of9, first derivation with a segment of9) and principal component analysis(PCA) were investigated. In the whole wavenumber range (12000cm^-1～4000cm^-1), thehighest correct discriminant rate (89.9%) of Fisher discriminant function was based on VNpreprocessing, while the lowest correct discriminant rate (73.3) was based on MNpreprocessing, and the correct discriminant efficiency of Fisher discriminant function built byother preprocessing methods were between the upper two.(5) In whole wavenumber range (12000cm^-1～4000cm^-1), the correct discriminantefficiency of Fisher discriminant function based on VN preprocessing and extracting principalcomponents (PCs,20PCs) was stabe, correct discriminant rate for calibration set is of89.9%,for test set is of87.8%. It can basically meet the requirements of non-destructive testing ofapple MC and CR fruits. These results could indicate that near infrared diffuse reflectancespectroscopy applied to apple MC and CR detection is feasible.(6) By using automatic optimization function of OPUS-QUANT2quantitative analysissoftwarefor modeling contidions, the best partial least square (PLS) model built for relativedecay area of apple MC and CR were based on VN preprocess. The optimized parameters forPLS model were as follows: effective wavenumbers are of12000cm^-1～5446.2cm^-1and4601.5cm^-1～4246.6cm^-1; PCs rank of10. Under these conditions, root mean square error ofcross-validation (RMSECV) is the lowest (0.123), the cross-validation determination (R2 0.5172, it is better than PLS model build in whole wavenumber range.(7) The best PLS model of decay area for apple MC and CR were built with the variablesselected by genetic algorithm (GA) after smoothing with a segment of9and VNpreprocessing. TheR2CVand prediction determination (R²P) for the PLS model built by GAselected variables after the both two preprocessing methods were0.6623and0.6328,0.6597and0.6466, respectively. Their corresponding RMSECV and root mean square errors ofprediction (RMSEP) were0.1035and0.0929,0.1041and0.0944, respectively. The resultsindicated that the PLS model buid by GA selected variables were better than the parametersoptimized by OPUS.(8) Eliminating32outliers by criterion of prediction difference, theR²_CVof PLS modelbuild by GA selected wavenumbers after smoothing with a segment of9spectrapreprocessing for calibration set is0.7809, RMSECV is of0.0846; theR2Pfor prediction setis0.6902, RMSEP is of0.0860. Eliminating44outliers by criterion of prediction difference,theR²_CVof PLS model build by GA selected wavenumbers after VN spectra preprocessingfor calibration set is0.7730, RMSECV is of0.0784; theR²_Pfor prediction set is0.7105,RMSEP is of0.0817. The above results indicated that both PLS models were robust, and canbe used to predicting decay area of apple MC and CRfruits, and the PLS model build by GAselected wavenumbers with VN preprocessing has a better prediction effect on decay area ofapple MC and CR fruits than GA selected wavenumbers with smoothing (a segment of9)preprocessing.