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以采集于缙云山不同海拔高度的12份青蒿为材料,研究青蒿素含量与环境、5个生理性状以及土壤营养元素的线性最优回归模型,结果表明:遮阴度对青蒿素含量的偏回归系数显著,建立根据遮阴度(X4)影响青蒿素含量(Y)的最优线性回归方程为Y=0.8986-0.0897X4(P<0.01,R2=0.8619);叶片类胡箩卜素(X2)和PAL(X3)对青蒿素含量的偏回归系数显著,建立根据类胡箩卜素(X2)和PAL(X3)影响青蒿素含量(Y)的最优线性回归方程为Y=-0.3688+0.1024X2+0.1078X3(P<0.05,R2=0.9391);速效K(X1)和碱解N(X3)对青蒿素含量的偏回归系数显著,建立根据速效K(X1)和碱解N(X3)影响青蒿素含量(Y)的最优线性回归方程为Y=0.0633+0.002081X1+0.0355X3(P<0.05,R2=0.9719),说明环境遮阴度、生理指标类胡箩卜素和PAL以及土壤中速效K和碱解N是影响青蒿素含量的重要因素。
The linear regression model of artemisinin content and environment, five physiological traits and nutrient elements in the soil was collected from 12 artemisia annua collected at different altitudes in Jinyun Mountain. The results showed that the effect of shading on the content of artemisinin The regression linear regression coefficients were significant (Y = 0.8986-0.0897X4 (P <0.01, R2 = 0.8619)). The optimal values of leaf carotenoids (X2) and PAL (X3), the optimal regression equation for artemisinin content (Y) according to class of carotenoids (X2) and PAL (X3) = -0.3688 + 0.1024X2 + 0.1078X3 (P <0.05, R2 = 0.9391). The partial regression coefficients of available K (X1) and alkaline hydrolysis N The optimal linear regression equation of alkali solution N (X3) affecting the content of artemisinin (Y) was Y = 0.0633 + 0.002081X1 + 0.0355X3 (P <0.05, R2 = 0.9719), indicating that the environmental shading and physiological indicators箩 and PAL as well as soil available K and alkaline solution N is an important factor affecting artemisinin content.