| Juglans regia ‘Wen185’ has become the leading cultivar in the southern Xinjiang basin as the Xinjiang local choice to cultivate a good early-fruiting walnut varieties. However, In recent years, lacking in providing a approach for developing effective, timely and nondestructive nutrition diagnosis for the development of J. regia ‘Wen185’ caused the walnut orchard fertilization and soil nutrient management is not to be found, as a result, the southern basin walnut orchard tree body nutrition deficiency and nutrition imbalance has become a common phenomenon, and seriously affect the yield and quality of nuts. What kind of technology to monitor foliar nutrient content was effective and timely monitoring is one of the major technical problems demanding prompt solution in the southern basin of walnut orchard fertilization and soil nutrient management. In view of this, J. regia ‘Wen185’ in flourishing period, Wushi, was taken as the object during the flourishing time, In response to the fertilizer effect test and foliar spectral reflectance to fertilization level based on the portable spectrum analyzer as leaf spectral data acquisition means, combined field foliar samples and fruit samples with nutrient concentration and fruit quality, the correlation between foliar nutrient concentration and spectral characteristic parameters as the main line,combining Pearson correlation analysis, regression analysis and regression diagnosis to select screen the most effective or effective spectral characteristic parameters of leaf nutrient concentration at various phenological periods of fruit development as well as the mathematics relationship between them and foliar nutrient concentratin and nut quality, and the measurement error method to construct spectral inversion models of the nutrient elements concentration in the leaves at various phenological periods of fruit development were established. The main research results as follows:In the fruit setting period, fast growth period, fat change period and near mature period,characterization of leaf N element concentration the most effective spectral characteristic parameters were green peak reflectivity(Rg), yellow edge reflectance(λy), red ratio index(RNIR/Red) and yellow edge amplitude( ly). Characterization of leaf P elements concentration the effective spectral characteristic parameters were green ratio index(RNIR/Green), red blue edge edge area normalized value(SDr-SDb)/(SDr+SDb), yellow edge position(ly) and valley position(lo). Characterization of leaf K elements concentration in the most effective spectral characteristic parameters respectively for green normalized difference vegetation index NIR-Green/NIR+Green), red edge and yellow edge area ratio SDr/SDy,RNIR/Green and blue edge area(SDb). The mathematical relationships between the N, P, K concentration and the most effective spectral characteristic parameters of the leaves are cubic functions.The mathematical relation between nut single fruit weight and nut crude fat content, and nut crude protein content respectively and characterization of foliar N, P, K concentration of effective spectral characteristic parameters(Rg, RNIR/Red, red normalized difference vegetation index(NIR-Red)/(NIR+Red), λy, red valley reflectivity(Ro), RNIR/Green,RNIR/Red,(NIR-Green)/(NIR+Green),(NIR-Red)/(NIR+Red), Rg, RNIR/Red, Dy, Rg, SDr),(RNIR/Green, RNIR/Red, SDr/SDb,(SDr-SDb)/(SDr +SDb), SDb, λy, λo, blue ratio index(RNIR/Blue), blue normalized difference index(NIR-Blue)/(NIR+Blue),(Dy,(NIRGreen)/(NIR+Green), λy, Dy, yellow edge area(SDy), the ratio of green and Red Valley(Rg/Ro), the normalized value of the green peak red valley(Rg-Ro) /(Rg+Ro), SDr/SDy, red edge and yellow edge area normalized value(SDr-SDy)/(SDr+SDy) is a linear function.In the period of fruit setting period, the fast growth period, the fat change and near mature period, characterization of the blade of calcium(Ca) elements in effective spectral characteristic parameters were(R′311,R′965,R′966,R′967,R′984,R′1 047,R′1084,R′1093,R′1 094),(R′384,R′968,R′972,R′973,R′1014,R′1016,R′1025,R′1026),(R′531,R′532,R′563,R′569,R′576,R′577,R′580,R′762,R′994)and(R′337, R′338, R′356, R′357, R′1089), characterization of the foliar magnesium(Mg) elements concentration in effective spectral characteristic parameters were(R′312, R′313, R′314, R′331, R′418,R′1001, R′1002, R′1003, R′1028, R′1029, R′1030),(R′317, R′318, R′335, R′336, R′337, R′351, R′399, R′400, R′401, R′489,R′507, R′508, R′514, R′515, R′647, R′648, R′881, R′906, R′907, R′911, R′922, R′923, R′1099),(R′467, R′468) and(R′312,R′313,R′314,R′356,R′357,R′829,R′835,R′872,R′1001), characterization of the blade of iron(Fe) elements concentration in effective spectral characteristic parameters were(R′341,R′910,R′911,R′976,R′979,R′980, R′1011, R′1012, R′1015, R′1016, R′1031, R′1032, R′1033),(R′427, R′428, R′987),(R′1067, R′1068, R′1069) and(R′405, R′509, R′754, R′995, R′996, R′1007, R′1017, R′1018, R′1019), The effective spectral characteristic parameters characterizing the concentration of Mn(Mn) elements in leaves are(R′1004, R′1043),(R′786, R′787, R′788, R′789, R′842, R′856, R′857, R′858, R′882, R′883, R′884, R′886, R′887, R′964, R′965, R′1040. R′1044.R′1045. R′1046).(R′869. R′870. R′871) and(R′406. R′407. R′408. R′647. R′648. 673). The effective spectral characteristic parameters characterizing the concentration of copper(Cu) elements in leaves are(R′519.R′527.R′528.R′529.R′533.R′536.R′537.R′538.R′613.R′614.R′615.R′654.R′656.R′657.R′658).(R′331,R′510, R′511, R′512, R′536),(R′390, R′391, R′392, R′399, R′401, R′409, R′410, R′411, R′412, R′423, R′424, R′425, R′489,R′513, R′514, R′515, R′516, R′527, R′528, R′529, R′537, R′538, R′539, R′587, R′588, R′599, R′680, R′681, R′682, R′683, R′686,R′687, R′689, R′1001, R′1129) and(R′974, R′1056). The effective spectral characteristic parameters characterizing the concentration of zinc(Zn) elements in leaves are(R′988, R′989, R′992, R′993)(R′362,R′410,R′411,R′564,R′565,R′566,R′707,R′708,R′709,R′710,R′711,R′712,R′713,R′714,R′715,R′770,R′771,R′772,R′773,R′774,R′775,R′776,R′792,R′859,R′957,R′958,R′959,R′960,R′1008,R′1009,R′1010),(R′38,R′553,R′554,R′555, R′556, R′853, R′854, R′857)and(R′396, R′397, R′398, R′971, R′974, R′978, R′1094, R′1095). The mathematical relationships between the concentration of Ca, Mg, Fe, Mn, Cu, Zn and the effective spectral characteristic parameters of the leaves are linear functions.Respectively in the period of fruit setting period, fast growth period, fat change period,near mature period of the most effective spectral characteristic parameters as the independent variable, foliar N, P and K concentration as the dependent variable, with cubic function as mathematical relationship, the macromutrient concentration spectral inversion model constructed by measurement error method than regression model has higher estimation accuracy at various phenological periods of fruit development. With effective spectral characteristic parameters as independent variables, with nuts fruit weight and kernel fat,protein content is dependent variable, to linear function mathematical relationship between the measurement error method to construct the fruit quality of leaf spectral inversion model than regression model has higher estimation accuracy. Respectively with effective spectral characteristic parameters as independent variables, with foliar Ca, Mg, Fe, Mn, Cu and Zn concentration as the dependent variable, to linear function mathematical relationship between the measurement error method to construct the leaves micronutrient concentration of spectral inversion model than regression model has higher estimation accuracy at various phenological periods of fruit development. J. regia ‘Wen185’ foliar mineral concentration and nut quality spectral inversion model can be applicable only in at the age of 7 years of production. |
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