Study On Characteristic Factor And Assignment Methods Of Rice Geographical Origin

Food geographical origin traceability system was a powerful method to protectgeographical indication. The effective method for food geographical origin traceabilitywas to select the characteristic factors which was characterized by geographical origininformation, then to analyze the "fingerprint" characteristics by chemometric methodsto identify the origin of the food. The objective of this paper was to search effectivemethod to select characteristic factors, and investigate the feasibility of tracing ricegeographical origin by fingerprint techniques. In this study, inductively coupled plasmamass spectrometry (ICP-MS), near infrared spectroscopy (NIR), high performanceliquid chromatography (HPLC) and ion chromatography technology were used todetect the contents of mineral elements, organic components and anion content indifferent origin rice. Multivariate statistical methods were used to analysis the ricecharacteristics and to establish the methods of origin traceability.1. The contents of Mg, K, Ca, Na, Be, Mn, Ni, Cu, Cd, Fe, Al, Cr, Zn, Sb, and Pb inrice, exchange state Mg, K, Ca, Na, and Mn, and effective state Mn, Co, Ni, Cu, Zn, Cd,Pb, and Fe, as well as full state Be, Al, Sb, and Pb in soil were detected by ICP-MS andthe atomic absorption spectrometry. The results showed that the Mg, K, Ca, Na, Be, Mn,Ni, Cu, and Cd in rice had significant differences between different producing areas.The pH and17kind mineral elements in the soil had significant differences betweendifferent producing areas. The Mg, K, Ca, Na, Be, Mn, Ni, Cu, Cd, and Pb hadsignificant correlation between rice and soil. The discrimination correct rate basised on9elements was higher than that of all elements. In linear discriminant analysis (LDA),the discrimination correct rate and cross discriminant correct rate of rice origin were100%and93.8%, respectively. The result of R-type system clustering analysis basedon15elements showed that: Mg, Cu, K, Ni, Be, Mn, and Ca clustered to a class. Itindicated that they are appropriate origin identify elements with the commoncharacteristics related with soil elements.2. A rapid method was developed for discrimination of the geographical origins of ricewith pattern recognition technique by near infrared spectrocopy (NIRS). After first derivativeand smooth processing, principal component analysis (PCA) was used to reduct thedimensionality of the spectral datas. Through the loading graph of the first three principal components, characteristic wave band (7700-6700cm-1,5700-4300cm-1) with max-relativitywas determined. In whole wave, using agglomerative hierarchical cluster analysis andFisher’s linear discriminant, the discrimination of Xiangshui rice and Non-Xiangshui rice wasall100%. The correct rate of specific geographical origins of Non-Xiangshui rice was91.9%by cluster analysis and96.7%by discriminant anlysis. In characteristic wave band, thecorrect rate of specific geographical origins of Non-Xiangshui rice was95.7%by clusteranalysis and91.6%by discriminant anlysis. The results indicate that it is feasible todiscriminate the geographical origins of rice with pattern recognition technique by NIRS, andselecting characteristicwave band is one of the validated methods to improve the precision ofthe discrimination mode.3. HPLC fingerprint of the ethyl acetate extracts was established by Similarity EvaluationSystem for Chromatographic Fingerprint of Traditional Chinese Medicine (Version2004A)with18common peaks. The common peaks of7,10,11, and14were gallic acid, oxophenicacid, p-hydroxybenzoic acid and ferulic acid, respectively. It found that this method wasreliable to identify the Xiangshui rice with the criterion of similarity larger than0.9. Thepeaks at40.66min,5.39min,22.06min, and39.66min were deemed as characteristic peakswhich closely related to the origin information by principal component analysis (PCA). Totalof23characteristic peaks which closely related to the origin information were determined bystepwise LDA, and the peaks at22.06min,38.00min,40.66min,35.93min,17.87min, and5.39min were deemed as important peaks as same as PCA. The discrimination accuracies andcross-validation obtained by LDA achieved100.0%and97.7%, respectively. Total of22characteristic peaks which closely related to the origin information were determined bystepwise multiple linear regression (MLR). The discrimination accuracies and standarddeviation are100%and0.699, respectively. Compared with the results of LDA, thecharacteristic peaks were identical except44.97min peaks. The discrimination accuracies ofK-nearest neighbor method (KNN) were96.9%with K=2which based on22characteristicpeaks selected by MLR. The results indicated that the characteristic peaks could be efficientlyused to classification of the geographic origin of rice.4. The contents of F-, Cl-, NO2-, NO3-, and SO42-in rice samples and soil samplesfrom four provinces of China were analyzed by ion chromatography. The result ofvariance analysis and correlation analysis demonstrated that there was significantdifference in the contents for F-, Cl-, NO2-, and NO3-in the rice samples from4 provinces, and the anions in rice were closely connected with the anions in soil. Thepredictions of geographic origin made by linear discriminant analysis (LDA) based onanions gave an overall correct classification rate of100%and cross-validation rate of96.9%. The correct rate of Q-type hierarchical cluster analysis (Q-type CA) was81.3%.The above results showed that the characteristic factors of mineral element, organiccomponents and anion content which was characterized by geographical origincombined with multivariate statistical methods are effective in rice geographicaltraceability.