Spectral parameter-based models for leaf potassium concentration estimation in Ping’ou hybrid hazelnut

• Published in: Journal of arid land 2020-11, Vol.12 (6), p.1083-1092
• Main Authors: Zhao, Shanchao, Pan, Cunde
• Format: Article
• Language: English
• Subjects: Correlation analysis; Cultivation; Earth and Environmental Science; Exponential functions; Fertilizers; Fruits; Function analysis; Geography; Growth stage; Hazelnuts; Leaves; Linear functions; Parameter estimation; Parameters; Physical Geography; Plant Ecology; Potassium; Quadratic equations; Reflectance; Regression analysis; Regression models; Research Article; Spectra; Spectral reflectance; Sustainable Development; Valleys
• ISSN: 1674-6767; 2194-7783
• DOI: 10.1007/s40333-020-0081-y

Ping’ou hybrid hazelnut is produced by cross cultivation and is widely cultivated in northern China with good development prospects. Based on a field experiment of fertilizer efficiency, the leaf spectral reflectance and leaf potassium (K) concentration were measured with different quantities of K fertilizer applied at four fruit growth stages (fruit setting stage, fruit rapid growth stage, fruit fat-change stage, and fruit near-maturity stage) of Ping’ou hybrid hazelnut in 2019. Spectral parameters that were significantly correlated with leaf K concentration were selected using Pearson correlation analysis, and spectral parameter estimation models of leaf K concentration were established by employing six different modelling methods (exponential function, power function, logarithmic function, linear function, quadratic function, and cubic function). The results indicated that at the fruit setting period, leaf K concentration was significantly correlated with D y (spectra slope of yellow edge), R g (reflectance of the green peak position), λ o (red valley position), SD b (blue edge area), SD r / SD b (where SD r represents red edge area), and ( SD r −SD b )/( SD r + SD b ) ( P