| Corylus’Xinzhen 1’is an excellent(C.heterophylla×C.avellana)which has been popularized and planted in northern and southern Xinjiang in recent years due to its high yield,full kernel,high kernel yield,cold resistance and strong adaptability.Some studies have established a spectral inversion model of leaf mineral nutrient content,which can provide a technical way for efficient and timely tree nutrient monitoring based on leaf nutrient content.Therefore,based on the field experiment of fertilizer effect and taking Corylus’Xinzhen 1’in the full fruit stage as the research object,this paper used a portable spectrometric analyzer(Uni Spec-SC)as the instrument to measure the spectral reflectance of leaves.Using the method of combining spectral reflectance measurement of living leaves in field,leaf sample collection and chemical determination of mineral nutrient content in laboratory,we screened the effective spectral characteristic parameters and the effective spectral sensitive bands for the content of mineral nutrients in fruit leaves at four growth periods In addition,based on the analysis of different growth periods of fruits(fruit setting period(FSP),fruit rappid growth period(FRGP),fruit fat change period(FFCP)and fruit near mature period(FNMP),this paper establishes the mathematics function relations that can be used in the spectral inversion statistical model of leaf mineral nutrient content(N,P,K,Ca,Mg,Fe,Mn,Cu,Zn).Furthermore,the least square estimation method of parameters was used to establish the spectral inversion statistical model of leaf mineral nutrient content of Corylus’Xinzhen 1’fruits in four growth periods.The main findings were as follows:(1)There were effective spectral characteristic parameters for the contents of N,P and K nutrient elements in leaves of fruit at four growth periods.The most effective spectral characteristic parameters of N were(NIR-Green)/(NIR+Green),(NIR-Red)/(NIR+Red),SD_rand SD_r;The most effective spectral characteristic parameters of P were(SD_r/SD_b),SD_b,R_oand R_g;The most effective spectral characteristic parameters of K were(SDr-SDb)/(SDr+SDb),(RNIR/Green),R_o and R_o.(2)There were effective spectral sensitive bands of Ca,Mg,Fe,Mn,Cu and Zn in leaves of fruit at four growth periods.Leaf Ca elements at FSP were 327,334,339,354,372,395,447,456,496,563,809,814,823,831,986,1 046 and 1 059 nm;351,359,378,409,471,774,775,845,866,894,923,979,990,1 014,1 031 and 1 091 nm in FRGP;388,440 and993 nm in FFCP;365,485,508,536,538,571,603,607,795,835,885,978,991,1 040,1072,1 078 and 1 097 nm in FNMP.Leaf Mg elements at FSP were 321,384,425,469,669,785,795,853,894,922,970,980,1 013,1 038 and 1 073 nm;317,335,360,379,485,846,902,948,974,981,984,1 015,1 036,1 062,1 075 and 1 092 nm in FRGP;467,517 and 1095 nm in FFCP;332,346,366,449,470,546,589,643,701,882,902,903,918,994,1 041,1 045 and 1064 nm in FNMP.Leaf Fe elements at FSP were 315,341,398,429,557,581,815,830,832,941,955,974,978,1 045,1 073,1 086 and 1 112 nm;347,352,395,456,469,474,574,773,784,850,853,928,959,969,1 110 and 1 124 nm in FRGP;820,845,1 085and 1 102 nm in FFCP;391,439,456,509,522,545,653,678,767,826,834,856,1 035,1050,1 070,1 098 and 1 109 nm in FNMP.Leaf Mn elements at FSP were 341,358,440,484,525,534,633,754,802,827,840,891,965,975,1 016 and 1 045 nm;341,358,440,484,525,534,633,754,802,827,840,891,965,975,1 016 and 1 045 nm in FRGP;350,778,851,868 and 1 048 nm in FFCP;369,387,393,494,522,581,599,609,629,653,859,922,974,1 016 and 1 085 in FNMP.Leaf Cu elements at FSP were 351,353,366,402,420,675,779,836,870,948,1 027,1 072,1 120 and 1 129 nm;331,340,396,441,468,769,837,878,919,1 004,1 016,1 033,1 045 and 1 077 nm in FRGP;378,933 and 992 nm in FFCP;314,505,506,569,623,640,674,775,836,1 033,1 037,1 053,1 060 and 1 116 nm in FNMP.Leaf Zn elements at FSP were 342,364,422,552,560,585,596,601,623,641,862,880,1076,1 098,1 099 and 1 112 nm;339,362,365,382,576,639,821,876,942,1 010,1 032,1049,1 056,1 092,1 099 and 1 112 nm in FRGP;450 and 1 061nm in FFCP;316,378,396,452,491,555,591,609,774,805,876,908,923,1 040,1 089 and 1 095 in FNMP.(3)The spectral inversion statistical model of N,P,K mineral nutrient contents in leaves was established,which could use cubic function and effective spectral characteristic parameters as independent variables.(4)We established a spectral inversion statistical model for the contents of Ca,Mg,Fe,Mn,Cu and Zn mineral nutrients in leaves,which can adopt a linear function relationship and take the first-order differential of the spectral reflectance of the effective spectral sensitive bands as the independent variable. |
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