Response Characteristics Of Fluorescence Kinetic Parameters Of Grape Leaves To Potassium Nutrition

Potassium is the activator of various enzymes in plant photosynthesis,which is closely related to the photosynthetic characteristics of plants.Based on BiXiang seedless grape as the research object,the key research under different potassium nutrition level of grape leaf chlorophyll fluorescence kinetics parameters of response mechanism.This study provide a reference for grape of potassium nutrition lack of diagnosis based on the research and development to provide technical support and related testing instrument.Research shows:1.With potassium fertilizer applied in 0²10kg/hm²,the chlorophyll fluorescence kinetic parameters of F_v/F_m,F_v/F_O,Y（II）and qP increased significantly,and qN decreased significantly with the increase of potassium application rate.After applying potassium fertilizer to 210kg/hm²,the F_v/F_m,F_v/F₀,Y（II）,qP decreased and qN increased with the increase of potassium fertilizer.The fluorescence parameters Y（II）and qP were sensitive to potassium nutrition.2.The grapes in the expanding period,the grape branches and leaf nutrient F_v/F_m,F_v/F₀,Y（II）,qP was first increased and then decreased,but the leaf F_v/F_m,F_v/F₀increased as leaf nutrient F_v/F_m,F_v/F₀ increased significantly,The decrease of Y（II）and qP in the leaves of the branches was significantly lower than that of Y（II）and qP in the leaves of the vegetative branches.3.The difference analysis of fluorescence parameters of different leaf positions（the branches above ear,including the ear leaf,from the bottom of first,second and third leaves sequentially labeled as L1,L2,L3,vegetative branches take the same leaf position,marking the same）showed that the F_v/F_m,F_v/F₀,Y（II）and qP of L1 leaves were higher than those of the final shoots L2 and L3,and qN value below the fruit L2,L3 leaf fluorescence parameter values;F_v/F_m,F_v/F₀,Y（II）,and qP were lower than those of vegetative branches L2 and L3,and qN was higher than the fluorescence parameter values of L2 and L3.And the fluorescence parameters of the leaves of the leaves were more sensitive to the potassium nutrition than the fluorescence parameters of the L1leaves.4.Fluorescence parameters of fruit L1 leaves a relevant analysis to the potassium contained in leafs,analysis found F_v/F_m,F_v/F₀,Y（II）,qP,qN associated with potassium content,and the correlation of Y（II）,qP was highest,0.664 and 0.596 respectively.5.With three kinds of model construction method based on chlorophyll fluorescence kinetics parameters of grape leaves（F_v/F₀,F_v/F_m,Y（II）,qP,qN）grape leaf potassium content regression prediction model,they are BP neural network,ELM network,SVR（support vector machine）,and the corresponding model of the precision test and evaluation.The results showed that the SVR algorithm was the best way to predict potassium content in leaves,and the average value of R² reached 0.839.The kernel function of the model is RBF,the optimum parameters c and g are selected and applied cross validation.