摘要
为探讨矿质元素和稳定同位素在马铃薯产地鉴别上的可行性,分别对内蒙古、黑龙江、新疆、四川和广东5个马铃薯主产区进行代表性样品采集,测定其矿质元素含量和稳定同位素比值,主成分分析、聚类分析和判别分析表明:采用步进式方法筛选出钠、铝、磷、锰、钴、镍、铜、镉8种矿质指纹指标,8种元素的交叉验证的正确判别率为89.3%;δ^13C比值和δ^15N比值基本可以成功区分内蒙古样品与黑龙江、新疆、广东样品,采用δ^13C和δ^15N建立的产地判别模型的判别正确率为82.0%;在钠、铝、磷、锰、钴、镍、铜、镉、δ^13C和δ^15N的综合指标下,不同产地的初始判别正确率达94.7%,交叉验证正确率达93.2%,均高于矿质元素含量和同位素比值单独判别正确率,判别结果良好。结果证明利用矿物元素和稳定同位素相结合的技术可以对马铃薯进行有效的产地判别,判别正确率较高,是产地溯源的有效方法。
In order to investigate the feasibility of identifying the geographical origin of potato based on mineral elements and stable isotopes,we determined the mineral element contents and stable isotope ratios of representative potato samples collected from five main potato-producing areas of China,Inner Mongolia,Heilongjiang,Xinjiang,Sichuan and Guangdong provinces.The results of principal component analysis(PCA),cluster analysis(CA)and discriminant analysis(DA)indicated that 8 fingerprint minerals,including sodium,aluminum,phosphorus,manganese,cobalt,nickel,copper and cadmium,were selected by stepwise method,and in the cross-validation,the correct discrimination rate was 89.3%for these minerals.δ^13C andδ^15N values could basically distinguish between samples from Inner Mongolia and those from Heilongjiang,Xinjiang and Guangdong.The discriminative accuracy of the model established based onδ^13C andδ^15N was 82.0%.Based on the fingerprint minerals combined with the stable isotopes,the initial correctness rate for the different geographical origins was 94.7%,and the correctness rate in cross-validation was 93.2%,both of which were higher than those obtained based on either of them alone,indicating good discrimination results.The results obtained in this study show that the combination of mineral elements and stable isotopes allows effective and accurate discrimination of the geographical origin of potato and therefore provides an effective method for geographical origin traceability.
作者
张欣昕
张福金
刘广华
张尧
王雪娇
莎娜
连海飞
ZHANG Xinxin;ZHANG Fujin;LIU Guanghua;ZHANG Yao;WANG Xuejiao;SHA Na;LIAN Haifei(Inner Mongolia Academy of Agricultural and Animal Husbandry Sciences,Hohhot 010030,China;Erdos Environmental Protection Center Monitoring Station,Erdos 017000,China)
出处
《食品科学》
EI
CAS
CSCD
北大核心
2020年第18期296-302,共7页
Food Science
基金
内蒙古自治区农牧业科学院创新基金项目(2017CXJJN015)
2019年自治区财政支持农牧业科技推广示范项目(2019TG03-4)。