Analysis of Meteorological Disasters in the Flowering and Fruiting Period of Sugar Orange in Guilin

The yield of sugar orange is closely related to meteorological conditions in the flowering and fruiting period, and meteorological disasters at the flowering and early fruiting stage seriously affect its yield. To study influences of meteorological disasters in the flowering and early fruiting stage on sugar orange industry in Guilin, meteorological disasters in the flowering and early fruiting stage and its defense measures were analyzed and studied. The flowering and early fruiting stage of sug- ar orange in Guilin is from March to June, and sudden change of temperature, thunderstorm, hale, hail, rainstorm and other natural disasters can cause the falling of large numbers of flowers and young fruit, damage of tree body, reduction of fruit in quantity, and decrease of its yield. Timely understanding information of disastrous weather and implementing management of water and fertilizer can effectively reduce the loss caused by meteorological disasters and ensue high quality and high yield of sugar orange.

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

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 Dy(spectra slope of yellow edge),Rg(reflectance of the green peak position),λo(red valley position),SDb(blue edge area),SDr/SDb(where SDr represents red edge area),and(SDr–SDb)/(SDr+SDb)(P<0.01).There were significant correlations of leaf K concentration with Dy,Rg,SDb,Rg/Ro(where Ro is the reflectance of the red valley position),and(Rg–Ro)/(Rg+Ro)at the fruit rapid growth stage(P<0.01).Further,significant correlations of leaf K concentration with Rg,Ro,RNIR/Green,and RNIR/Blue were obtained at the fruit fat-change period(P<0.01).Finally,leaf K concentration showed significant correlations with Dr,Rg,Ro,SDy(yellow edge area),and SDr at the fruit near-maturity stage(P<0.01).Through a cubic function analysis,regression estimation model of leaf K concentration with highest fitting degree(R2)values at the four fruit growth stages was established.The findings in this study demonstrated that it is feasible to estimate leaf K concentration of Ping′ou hybrid hazelnut at the various phenological stages of fruit development by establishing regression models between leaf K concentration and spectral parameters.