基于稳定同位素的上海地产蔬菜种植模式及产地判别

Determination of Planting Patterns and Geographical Origin of Local Vegetables in Shanghai Based on Stable Isotopes

为保护蔬菜的优质优价及质量安全,以上海9个农业产区(宝山区、崇明区、奉贤区、嘉定区、金山区、闵行区、浦东新区、青浦区和松江区)蔬菜为研究对象,分析不同产区蔬菜的δ^(15)N值差异及其对种植模式(常规、绿色或有机种植)的指示;对δ^(13)C、δ^(15)N、δ^(2)H和δ^(18)O值进行单因素方差分析,并应用主成分分析(PCA)、偏最小二乘判别分析(PLS-DA)及支持向量机(SVM)方法,建立上海地产蔬菜产地判别模型。结果表明,宝山区、松江区和嘉定区蔬菜的δ^(15)N值占前三,且分别与δ^(15)N值最低的浦东新区蔬菜(4.44‰)存在显著差异,且仅有浦东新区蔬菜可能为绿色或有机种植的比例低于50%;δ^(13)C、δ^(2)H和δ^(18)O值只在部分产区间差异显著,PCA可初步实现浦东新区蔬菜与其他8个产区的鉴别;PLS-DA最优模型可以很好地实现浦东新区蔬菜产地判别(预测准确率为98.80%),SVM最优模型可以很好地实现宝山区(预测正确率96.38%)、嘉定区(预测正确率92.77%)和青浦区(预测正确率91.57%)蔬菜的产地判别,SVM最优模型可以较好地实现金山区、松江区、崇明区和奉贤区蔬菜的产地判别。本研究结果为上海地产蔬菜种植模式及产地判别提供了参考方法,并为其溯源和质量安全保护提供了基础数据。

To protect the high quality,high price and the quality and safety of vegetables,nine agricultural production areas(Baoshan District,Chongming District,Fengxian District,Jiading District,Jinshan District,Minhang District,Pudong New District,Qingpu District and Songjiang District)in Shanghai were taken as the research objects.The difference ofδ^(15)N values among vegetables grown in different regions and the indication of planting patterns(conventional,green or organic farming)were analyzed.One-way ANOVA was used to analyze the value ofδ^(13)C,δ^(15)N,δ^(2)H andδ^(18)O,and principal component analysis(PCA),partial least squares discriminant analysis(PLS-DA)and support vector machine(SVM)were applied to establish discriminant models of vegetable producing regions in Shanghai.The results showed that theδ^(15)N values of vegetables in Baoshan District,Songjiang District and Jiading District accounted for the top three,and there was a significant difference fromδ^(15)N value of vegetables in Pudong New District with the lowest value(4.44‰),respectively.Only vegetables from Pudong New District grown green or organically were less than 50%.The value ofδ^(13)C,δ^(2)H andδ^(18)O were only significantly different in some producing areas,and PCA could preliminarily realize the identification of vegetables from the other 8 producing areas with Pudong New District.The optimal PLS-DA model could well realize the geographical origin discriminant of Pudong New District vegetables(prediction accuracy of 98.80%).The optimal SVM models could well realize the geographical origin discriminant of Baoshan District vegetables(prediction accuracy of 96.38%),Jiading District vegetables(prediction accuracy of 92.77%),and Qingpu District vegetables(prediction accuracy of 91.57%).The gegraphical origin discriminant of Jinshan District vegetables,Songjiang District vegetables and Chongming District vegetables could also be achieved by the optimal SVM models to some extent.These results could provide reference methods for planting patern and geographical origin discriminant of Shanghai local vegetables,as well as basic data for their traceability,quality and safety protection.