Monitoring and diagnosis of potassium nutrition in Ipomoea batatas leaves based on spectral reflectivity
Two Ipomoea batatas varieties,Shangshu 19 and Xinxiang,were used as experimental materials.By setting different gradi-ent potassium treatments to determine the spectral reflectance of leaves,Ipomoea batatas leaves potassium content and potassium nutri-ent index prediction models were constructed based on the ratio vegetation index(RVI).The results showed that the linear model con-structed by RVI and potassium content in leaves showed that RVI(R1 598 nm,R1 771nm)had a high prediction accuracy for potassium con-tent in Ipomoea batatas leaves,the regression equation was y=58.601 0x-58.446(R2=0.741 4,RMSE=0.83),using validation data to test the linear model,the model showed good predictive ability for potassium content in Ipomoea batatas leaves under different potassi-um fertilizer levels(R2=0.732 4,RMSE=0.85);the linear model constructed by RVI and potassium nutrition index indicated that RVI(R700 nm,R1 385 nm)had a high prediction accuracy for the potassium nutrition index of Ipomoea batatas leaves,the regression equation was y=6.032 9x-0.833(R2=0.768 8,RMSE=0.15),using validation data to test the linear model,the model showed good predictive ability for the potassium nutrient index of Ipomoea batatas leaves under different potassium fertilizer levels(R2=0.639 5,RMSE=0.20);the use of RVI could effectively monitor and diagnose potassium nutrition in Ipomoea batatas.
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