CN109187441B - Method for constructing summer corn nitrogen content monitoring model based on canopy spectral information - Google Patents
Method for constructing summer corn nitrogen content monitoring model based on canopy spectral information Download PDFInfo
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Abstract
The invention discloses a method for constructing a summer corn nitrogen content monitoring model based on canopy spectral information, which comprises the steps of analyzing the change characteristics of the spectral reflectivity of a summer corn plant canopy under different fertilization levels through a small lysimeter test, researching the response relation between the spectral reflectivity of the summer corn plant canopy and a first derivative thereof and the nitrogen content, screening sensitive wave bands for monitoring the nitrogen content of the corn canopy, determining an optimal wave band combination, screening an optimal spectral index, constructing four summer corn nitrogen content monitoring models on the basis of the most sensitive wave bands of an original spectral reflectivity and a first differential spectrum, the optimal wave band combination and the optimal spectral index, carrying out rate determination on the four summer corn nitrogen content monitoring models through model evaluation indexes, and verifying by using field plot test data to determine the optimal monitoring model. The monitoring model can be used for monitoring the nitrogen content of summer corns in the whole growth period, and has important theoretical and practical significance for realizing the nondestructive monitoring of the nitrogen content of large-scale crops and the accurate management of water and fertilizer.
Description
Technical Field
The invention belongs to the technical field of agriculture, and particularly relates to a construction method of a summer corn whole growth period nitrogen content monitoring model based on canopy spectrum information.
Background
Corn is a widely planted grain crop, and nitrogen fertilizer is one of main limiting factors influencing corn growth, and plays an important role in growth vigor, yield and quality formation of the corn, but adverse effects brought by problems of blind application increase and low utilization rate of fertilizer are increasingly obvious, so that the nitrogen fertilizer condition of the crop is quickly and effectively tracked and monitored, the nitrogen fertilizer is reasonably applied, and the method has important significance in improving corn quality and sustainable utilization of land. The spectral characteristic difference of crops caused by different nitrogen contents is proved by a plurality of researches, and compared with the traditional method for monitoring the nitrogen content of plant canopies by destructive sampling, the method for nondestructively acquiring the hyperspectral information of the crops in a large area range is more convenient and direct, and can provide scientific and technological support for the precise management of modern large-scale agricultural water and fertilizer.
The spectral technology can be used for rapidly and nondestructively monitoring the crop nutrition state and other related parameter information, and the method is widely applied to aspects of crop growth diagnosis, accurate fertilization management, crop classification and the like at present. Scholars at home and abroad respectively select field crops such as wheat, rice, cotton, corn and the like to carry out related research, analyze the correlation between the nitrogen content of plants and the spectral reflectivity, and initially establish a spectral model for estimating the nitrogen content of the plants. Liu Bing Feng et al point out that it is better to adopt red light and green glow wave band monitoring maize plant nitrogen content effect, but each growing time interval monitoring sensitive wave band is different. In studies using a spectral index model to monitor plant nitrogen content, Clevers et al indicate that green chlorophyll index (CI green) and red-edge chlorophyll index (CI red-edge) can be used to monitor nitrogen content in plants of a particular growth period; hansen et al indicate that wheat canopy nitrogen content can be better monitored using normalized vegetation index (NDVI) and bimodal canopy nitrogen nutrition index (DCNI). In summary, at present, relevant researches on quantitative relations between crop spectral reflectivity and plant nitrogen content at home and abroad have been carried out, and the problem of universality still exists when the plant nitrogen content is monitored by adopting sensitive bands or spectral indexes and the like, namely the sensitive bands for monitoring the plant nitrogen content are different from a spectral index model due to differences of crops, growth periods, research areas and the like in different researches. In order to realize the large-scale nondestructive monitoring of the nitrogen content of main crop plants, a typical crop nitrogen content spectrum monitoring test needs to be further developed, and the most sensitive waveband and the appropriate spectrum index model suitable for monitoring the nitrogen content of plants in the whole growth period are screened out, so that the universal technological problem existing in the spectrum characteristic variable application is solved.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a method for constructing a summer corn nitrogen content monitoring model based on canopy spectrum information, wherein the monitoring model can be used for monitoring the nitrogen content of summer corn in the whole growth period, and has important theoretical and practical significance for realizing large-scale crop nitrogen content nondestructive monitoring and water and fertilizer precise management.
In order to achieve the purpose, the technical scheme adopted by the invention for solving the technical problems is as follows:
a construction method of a summer corn nitrogen content monitoring model based on canopy spectrum information comprises the following steps:
s1, measuring the original spectral reflectivity and the nitrogen content of the summer corn canopy at different growth periods under different nitrogen nutrition;
s2, resampling and deriving the reflectivity of the original spectrum, and determining a first-order differential spectrum of the original spectrum;
s3, calculating correlation coefficients of the nitrogen content of the summer corn canopy, the original spectral reflectivity and the first-order differential spectrum, and determining the most sensitive wave band corresponding to the original spectral reflectivity and the first-order differential spectrum which have the maximum correlation with the nitrogen content of the summer corn;
s4, analyzing the most sensitive wave band of the summer corn canopy through a multiple stepwise regression analysis method to obtain the optimal wave band combination;
S5, determining the optimal spectral index of spectral monitoring of nitrogen content of the canopy of summer corn;
s6, constructing four summer corn nitrogen content monitoring models on the basis of the most sensitive wave band corresponding to the original spectrum reflectivity and the first-order differential spectrum, the optimal wave band combination and the optimal spectrum index;
s7, testing the four summer corn nitrogen content monitoring models through model evaluation indexes, and determining the optimal summer corn nitrogen content monitoring model in the whole growth period.
Further, the method for measuring the original spectral reflectance of the canopy of the summer corn in the step S1 specifically comprises the following steps:
monitoring the original spectral reflectivity of the canopy layer in the growth period of the summer corn through a spectrometer, performing standard white board correction in the monitoring process, monitoring the spectral reflectivity of a plurality of summer corns in each small lysimeter, and taking the arithmetic average value of the spectral reflectivities as the original spectral reflectivity of the canopy layer of the summer corn of the small lysimeter;
the monitoring parameters of the original spectral reflectivity of the summer corn canopy are set as follows: the spectrum wave band is 325 nm-1075 nm, the monitoring sampling interval is 1nm, the spectrum resolution is 3nm, the monitoring time is 10: 00-14: 00, a probe of a spectrometer sensor is vertically downward, the field angle of the spectrometer is 25 degrees, and the vertical height from the top of a canopy of summer corn is 10-20 cm.
Further, the method for measuring the nitrogen content of the canopy of the summer corn in the step S1 specifically comprises the following steps:
cutting the plant, deactivating enzyme, oven drying, grinding the oven dried sample into powder, and pulverizing with H2SO4-H2O2Digestion, and finally measuring by using a Kjeldahl apparatus.
Further, the calculation formula of the correlation coefficient r in step S3 is:
in the formula, n is the actual measurement times;
xithe spectral reflectance or first order differential spectrum of the ith summer corn canopy;
yithe nitrogen content of the ith summer corn canopy;
Further, step S4 is specifically:
and performing regression analysis on the spectral reflectivity and the nitrogen content value of the summer corn canopy within the range of 325-1075 nm by adopting a multivariate stepwise regression analysis method to obtain the optimal waveband combination of the summer corn plant canopy.
Further, step S5 is specifically:
based on the nitrogen spectrum monitoring index, the correlation analysis is carried out on each nitrogen monitoring index and the summer corn plant canopy nitrogen content monitoring value, and the optimal spectrum index for monitoring the canopy nitrogen content in the whole growth period is determined according to the correlation coefficient.
Further, the model evaluation indexes in step S7 are a decision coefficient, a root mean square error, and an average absolute error.
The construction method of the summer corn nitrogen content monitoring model based on canopy spectral information, provided by the invention, has the following beneficial effects:
according to the method, the spectral reflectivity and the response relation of the nitrogen content of the canopy of the summer corn plant are researched by analyzing the change characteristics of the spectral reflectivity of the canopy of the summer corn plant under different fertilization levels, a sensitive wave band for monitoring the nitrogen content of the canopy of the summer corn plant and a proper spectral index model are screened out, a field plot experiment is used for verification, and finally an optimal monitoring model is confirmed.
The method comprises a small lysimeter test and a field plot test, and compared with the field plot test, the small lysimeter test is less interfered by various factors, and the obtained data is more reliable, so that the small lysimeter test is used for performing spectral characteristic rule analysis and model construction under different fertilization conditions in the research. And the field and plot experiment is basically consistent with the field and corn production practice of the research area, can completely represent the actual growth conditions of the field and corn under different fertilization conditions, and further verifies the screened model by adopting the field and plot experiment monitoring result so as to ensure the large-range regional application performance of the optimized model.
The method is researched aiming at the canopy of the summer maize plant in the whole growth period, compared with the modeling of single key growth period data, the sample data in the whole growth period is rich, the reliability of the estimation model is improved, and compared with the research of the leaf size of the summer maize, the conclusion obtained by the canopy size research has important significance for regional research.
Drawings
Fig. 1 is a flow chart of a construction method of a summer corn nitrogen content monitoring model based on canopy spectrum information.
FIG. 2 is a graph of summer maize plant canopy nitrogen content results at different fertilization levels.
FIG. 3 is a graph of the results of summer corn yield at different fertilization levels.
FIG. 4 is a graph of spectral reflectance of canopy of summer maize plants at different fertilization levels and different growth periods; wherein, (a) is the jointing stage, (b) is the emasculation stage, (c) is the grouting area, and (d) is the mature stage.
FIG. 5 is a graph of the correlation coefficient of spectral reflectance and nitrogen content of canopy of summer maize plants at different growth periods.
FIG. 6 is a graph of correlation coefficient of first order differential spectra of canopy of summer maize plants at different growth periods with nitrogen content.
FIG. 7 is a graph of spectral parameter model verification of nitrogen content in canopy of summer corn during the whole growth period.
Detailed Description
As shown in fig. 1, a method for constructing a summer corn nitrogen content monitoring model based on canopy spectrum information includes the following steps:
S1, measuring the original spectral reflectivity and the nitrogen content of the summer corn canopies in different growth periods under different nitrogen nutrition;
the method for measuring the original spectral reflectivity of the summer corn canopy specifically comprises the following steps:
monitoring the original spectral reflectivity of the canopy layer in the growth period of the summer corn through a spectrometer, performing standard white board correction in the monitoring process, monitoring the spectral reflectivity of a plurality of summer corns in each small lysimeter, and taking the arithmetic average value of the spectral reflectivities as the original spectral reflectivity of the canopy layer of the summer corn of the small lysimeter;
the monitoring parameters of the original spectral reflectivity of the summer corn canopy are set as follows: the spectrum wave band is 325 nm-1075 nm, the monitoring sampling interval is 1nm, the spectrum resolution is 3nm, the monitoring time is 10: 00-14: 00, a probe of a spectrometer sensor is vertically downward, the field angle of the spectrometer is 25 degrees, and the vertical height from the top of a canopy of summer corn is 10-20 cm.
The method for measuring the nitrogen content of the canopy of the summer corn specifically comprises the following steps:
cutting the plant, deactivating enzyme, oven drying, grinding the oven dried sample into powder, and pulverizing with H2SO4-H2O2Digestion, and finally measuring by using a Kjeldahl apparatus.
S2, resampling and deriving the reflectivity of the original spectrum, and determining a first-order differential spectrum of the original spectrum;
The specific process is as follows: before data processing and analysis, resampling and exporting the monitored original spectral reflectivity data by using processing software of a spectrometer, wherein the sampling interval is 1 nm; in order to provide the influence of soil background and atmospheric scattering and improve the contrast of different absorption characteristics, first-order differentiation is carried out on the original spectral reflectivity data, namely, the first-order derivative of the original spectral reflectivity is calculated;
s3, calculating correlation coefficients of the nitrogen content of the summer corn canopy, the original spectral reflectivity and the first-order differential spectrum, and determining the most sensitive wave band responded by the original spectral reflectivity and the first-order differential spectrum which have the maximum correlation with the nitrogen content of the summer corn;
wherein, the calculation formula of the correlation coefficient is as follows:
in the formula, n is the actual measurement times;
xithe spectral reflectance or first order differential spectrum of the ith summer corn canopy;
yithe nitrogen content of the ith summer corn canopy;
S4, analyzing the most sensitive wave band of the summer corn canopy through a multiple stepwise regression analysis method to obtain the optimal wave band combination;
the specific process is as follows: and performing regression analysis on the spectral reflectivity and the nitrogen content value of the summer corn canopy within the range of 325-1075 nm by adopting a stepwise regression method to obtain the optimal waveband combination of the summer corn plant canopy.
S5, determining the optimal spectral index of spectral monitoring of nitrogen content of the canopy of summer corn;
the specific process is as follows: based on the 44 nitrogen spectrum monitoring indexes, the optimal spectrum index is determined according to the correlation coefficient by carrying out correlation analysis on each nitrogen spectrum monitoring index and the nitrogen content monitoring value of the canopy of the summer corn plant.
S6, constructing four summer corn nitrogen content monitoring models on the basis of the most sensitive wave band responded by the original spectrum reflectivity and the first-order differential spectrum, the optimal wave band combination and the optimal spectrum index;
s7, determining the coefficient (R)2) And the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE) are used as model evaluation indexes, the four summer corn nitrogen content monitoring models are tested, and the optimal summer corn nitrogen content monitoring model is determined.
In one embodiment of the present invention, a method for constructing a nitrogen content monitoring model using summer corn in north China as an example is provided, which specifically comprises the following steps:
(one) data acquisition
1. Sample collection
The experimental place of the invention selects a water-saving irrigation experiment research base of China institute of Water conservancy and hydropower science, and the selected summer corn variety is epoch 168.
The test is divided into two parts, namely a small lysimeter test and a field plot test. Wherein the specification of the box body of the small lysimeter is 1m multiplied by 0.75m multiplied by 1m, and the box bodies are 12 in total; the area of the test cell of the field cell is 7 multiplied by 8m 2And 12 cells in total.
Sowing summer corn in 2017 in 6 months and 15 days, setting the plant and row spacing to be 25cm, and planting density to be 75000 plants/hm2Harvested at 25 days 9 months. The test has 4 fertilization treatments, and the fertilization amount is respectively 0, 225, 450 and 675kg/hm2I.e., N0, N1, N2, N3 treatments, where N2 treatment was at normal fertilization level, each treatment was repeated 3 times. Fertilizing for 2 times in the whole growth period, wherein the tested fertilizer is a compound fertilizer (containing 15% of N and P)2O5Amount of 15% and K215% of O content) and urea (46% of N content), wherein the compound fertilizer is applied as a base fertilizer, the urea is applied in the jointing-emasculation period as an additional fertilizer, and other management is consistent with that of a high-yield field.
The sample collection is to collect the leaf of the canopy of the summer corn plant as a sample at intervals of 7-10 days in the growth period.
2. Measurement of plant canopy spectra
In the summer maize growing period, under the selected sunny, breeze or no wind condition, a HandHeld ground object spectrograph of American Analytical Spectral Devices (ASD) company Field-spectrum hand-held 2 is adopted to monitor the Spectral reflectivity of the plant canopy, the Spectral band is set to 325 nm-1075 nm, the monitoring sampling interval is 1nm, the Spectral resolution is 3nm, and the monitoring time is 10: 00-14: 00. in the measurement process, the standard white board is corrected in time (the reflectivity of the standard white board is 1, so that the obtained target spectrum is the relative reflectivity) so as to accurately measure the next treatment. During measurement, the probe of the sensor is vertically downward, the field angle of the spectrometer is 25 degrees, and the vertical height from the top of the canopy is about 10-20 cm. And 3 corns are selected for each small lysimeter to be measured, and then the arithmetic mean value is taken as the canopy spectral reflectivity of the summer corn of the small lysimeter.
3. Determination of plant canopy nitrogen content
Cutting the plant, deactivating enzyme, oven drying, grinding the oven dried sample into powder, and pulverizing with H2SO4-H2O2Digestion, and finally determination by using a Kjeldahl apparatus, wherein the specific method is referred to soil agrochemical analysis.
Measuring the spectral reflectivity of the plant canopy and the nitrogen content of the plant once at intervals of 7-10 days in the growth period, and synchronously carrying out the two steps.
(II) data processing
Before data analysis, the original spectrum data measured by the spectrometer is resampled and exported by using a processing software ViewSpec Pro6.2 of the spectrometer, and the sampling interval is 1 nm. In order to eliminate the influence of soil background and atmospheric scattering and improve the contrast of different absorption characteristics, the first derivative of the reflectivity of the original spectrum is calculated by solving the first derivative of the original spectrum, and the relation between the first derivative, the reflectivity of the original spectrum and the nitrogen content is analyzed.
(III) the nitrogen content and yield of the canopy of summer maize plants under different fertilization levels
Fig. 2 shows the result of the nitrogen content in the canopy of summer maize plants at different fertilization levels, and it can be seen from fig. 2 that the nitrogen content in the canopy of summer maize plants decreases with the advancing of the growth period, the nitrogen content in the canopy is higher in the jointing stage and the androgenesis stage, and the nitrogen content in the canopy is lower in the grouting stage and the maturation stage. As the fertilization amount is increased, the nitrogen content of the canopy of the summer corn plants is increased, the nitrogen content of the canopy of the plants among different fertilization levels is different to a very significant level (p <0.01), but the nitrogen content of the canopy of the plants among the N2 treatment and the N3 treatment is different to a significant level (p < 0.05).
FIG. 3 shows the content of summer corn at different fertilization levels, and it can be seen from FIG. 3 that the yield of summer corn increases with the amount of fertilizer applied until the maximum yield reaches 10.435 t/hm/h when the fertilization level reaches N22(ii) a When the fertilizing amount is further increased, the yield does not increase and inversely decreases like the treatment N3. Therefore, the reasonable fertilization can promote the growth of the corn, ensure the high yield of the corn, control the non-point source pollution caused by excessive fertilization and be beneficial to the continuous and efficient utilization of agricultural production.
(IV) spectral characteristics of canopy of summer maize plants at different fertilization levels
Spectral characteristics of canopy of summer maize plants at different fertilization levels are shown in fig. 4, where (a) is spectral reflectance during the jointing stage, (b) is spectral reflectance during the tasseling stage, (c) is spectral reflectance during the filling zone, and (d) is spectral reflectance during the maturation stage.
As can be seen from fig. 4, in the visible light band (380-760 nm), chlorophyll is green because it absorbs most of red and purple light but reflects green light, and the chlorophyll plays a core role in light absorption of photosynthesis, so that the spectral reflectance of the plant canopy is low; wherein the reflection peak value of a green light wave band (500-580 nm) is near 550nm, and a large amount of red light is absorbed by the photosynthesis of chlorophyll to form an absorption band in a red light wave band (620-760 nm). In a near infrared region (760-1075 nm), the spectral reflectance of the plant canopy is expressed as a high reflection region under the control of the internal structure of the summer corn canopy, namely, the reflectance of the plant canopy rapidly rises near a 760nm wave band to form a red edge phenomenon. The spectral reflectance of the canopy of summer maize plants is highest at the maturity stage compared to other growing periods; in other growth periods, the spectral reflectivity of the plant canopy at the visible light band shows that the filling period is more than the emasculation period and more than the jointing period, and the near-infrared band shows that the jointing period is more than the emasculation period and more than the filling period. Within the range of visible light wave bands, the spectral reflectivity of the canopy of summer corn plants under different fertilization levels shows a certain difference, namely the spectral reflectivity is reduced along with the increase of the fertilization amount, wherein the spectral reflectivity is most obvious in a green light wave band; within the range of near-infrared wave bands, the change rule of the spectral reflectivity of the canopy of the summer corn plant under different fertilization levels in the treatment process is in an opposite trend, namely the spectral reflectivity of the canopy of the plant is increased along with the increase of the fertilization amount, and the difference between the treatment processes is more obvious than that of the visible light wave bands.
(V) screening of spectral monitoring sensitive wave band for nitrogen content of canopy of summer corn plant
The correlation coefficient of the spectral reflectivity of the canopy of the summer maize plant and the nitrogen content is shown in figure 5, and as can be seen from figure 5, the correlation between the canopy and the jointing stage is negative, the androgenesis stage is positive, the filling stage and the maturation stage are mainly positive, and the negative correlation is near the wave band of 500-720 nm. In blue light and green light wave bands, the correlation between the spectral reflectivity of the plant canopy and the nitrogen content of the plant canopy is the largest in the jointing stage, and the absolute value of the correlation coefficient is more than 0.55; in the androgenesis period, the correlation coefficient is between 0.40 and 0.52; and the correlation between the grouting period and the maturation period is low, and the absolute values of the correlation coefficients are less than 0.4. The fluctuation of the correlation coefficient is large in the red light wave band, wherein the correlation coefficients of the jointing stage, the tasseling stage, the grouting stage and the mature stage fluctuate within the ranges of-0.41-0.76, 0.36-0.61, -0.48-0.87 and-0.18-0.56 respectively, the most relevant wave band in the jointing stage is 685nm, and the most relevant wave bands in other growth stages are 760 nm. In the near infrared band, the correlation coefficient is relatively stable, wherein the correlation coefficients in the jointing stage, the emasculation stage, the grouting stage and the maturation stage are respectively stable at-0.39, 0.65, 0.88 and 0.50. From the whole growth period of summer corn, the correlation coefficient of the two is stabilized at about-0.48 in the blue light and green light wave bands; a wave trough is formed in the red wave band and located at 678nm, a wave peak is formed in the near infrared wave band and located at 760nm, and correlation coefficients are-0.56 and 0.38 respectively.
The correlation coefficient between the first derivative of the spectral rate of the canopy of the summer maize plant and the nitrogen content of the canopy of the plant is shown in fig. 6, and as can be seen from fig. 6, the correlation coefficient between the two is higher but unstable in blue light and green light bands; in a red light wave band, the two show obvious negative correlation in a 690-698nm wave band, show obvious positive correlation in a 732-753nm wave band, and are both stable; the correlation coefficient is stabilized between-0.50 and-0.59; the other growth periods have higher positive correlation, and the correlation coefficient is between 0.54 and 0.82.
Comprehensively comparing the correlation between the spectral reflectivity of the canopy of the summer maize plant and the nitrogen content, the more sensitive wave band of the nitrogen content of the canopy of the summer maize plant is positioned between the wave bands of 550nm wave peak, 678nm wave trough and 760nm wave peak and the wave bands of 690-698nm and 732-753 nm.
According to the analysis results, the blue edge (470nm), the green edge (550nm), the yellow edge (620nm) and the red edge (720nm) of the summer maize visible light region, the spectral reflectivities of the canopy layers of the 690nm, 749nm and 753nm bands selected according to the step-by-step discriminant analysis method, the first derivative of the spectral reflectivities and the correlation coefficient of the nitrogen content of the canopy layers of the summer maize plants are listed in the table 1.
TABLE 1 correlation coefficient of nitrogen content of canopy of summer maize plants with spectral reflectance and first derivative thereof
Note: p < 0.01, P < 0.05, no correlation
As can be seen from Table 1, the spectral reflectivities of characteristic wave bands of 470nm, 550nm and 620nm are very obviously related to the nitrogen content of the plant canopy in the jointing stage and the whole growth stage, and the correlations of other growth stages are lower; and the first derivative of the spectral reflectivity at 470nm, 550nm and 620nm of characteristic wave bands in different growth periods has low or no correlation with the nitrogen content of plant canopies. The spectral reflectivity and the first derivative thereof at the jointing stage and the full-growth characteristic waveband of 690nm are obviously related to the nitrogen content of the plant canopy. In the 720nm, 749nm and 753nm wave bands, the correlation between the spectral reflectivity and the plant canopy nitrogen content in the whole growth period does not reach a significant level, and the plant canopy nitrogen content in other growth periods is significantly or extremely significantly correlated with the spectral reflectivity and the first derivative.
In conclusion, the most sensitive wave bands for monitoring the nitrogen content of the plant canopy in the whole growth period by adopting the spectral reflectivity and the first derivative thereof are 690nm and 749nm respectively by respectively taking the spectral reflectivity of the characteristic wave band and the highest correlation between the first derivative thereof and the nitrogen content of the plant canopy as the selection standard.
And obtaining optimal band combinations of 690nm, 749nm and 753nm by a multivariate stepwise regression analysis method for the most sensitive band.
(VI) screening of spectral monitoring index of nitrogen content in canopy of summer maize plant
Based on the 44 reported nitrogen spectrum monitoring indexes, 5 spectrum indexes with higher correlation coefficients are preferably selected by carrying out correlation analysis on each nitrogen spectrum monitoring index and a summer corn plant canopy nitrogen content monitoring value, wherein the 5 spectrum indexes are respectively mNDVI, MSR sum value, MSR mean value, ND (FD730, FD525) and R780/R740, and the specific correlation coefficients are shown in Table 2.
TABLE 2 correlation coefficient of nitrogen content in canopy of summer maize plants and spectral index
Note: p < 0.01, — P < 0.05, — no correlation
As can be seen from Table 2, in the jointing stage, except that the correlation between the mNDVI spectral index and the nitrogen content of the plant canopy is not significant, other spectral index models all reach a very significant level. In the androgenesis period, the selected 5 spectral indexes reach a very significant level, wherein the mNDVI spectral indexes have the highest correlation, and the correlation coefficient reaches 0.821. In the grouting period, except that 2 spectral indexes such as the MSR mean value, the MSR sum value and the like reach significant correlation, other spectral index models all reach very significant correlation; wherein the correlation of the mNDVI spectral index model is the highest, and the correlation coefficient reaches 0.744. In the mature period, the spectral index model R780/R740 showed significant correlation, and other spectral index models even showed very significant correlation, except that the spectral index ND (FD730, FD525) correlation did not reach a significant level. In the whole growth period, 5 spectral index models reach a very significant level, wherein the correlation coefficient of the spectral index models mNDVI, the MSR sum value and the MSR mean value is as high as 0.849. Comprehensively considering the correlation between the spectral indexes of all growth periods and the nitrogen content of plant canopies, and combining the difference between different fertilization treatments of the nitrogen content of the plant canopies of all growth periods, the difference between the nitrogen contents of the plants in the emasculation period, the grouting period and the maturity period is obvious, the nitrogen content of the plants is increased along with the increase of the fertilization amount, and the spectral indexes mNDVI and the nitrogen content of the plant canopies in the three growth periods all reach extremely obvious levels, wherein the correlation between the calculated value of mNDVI and the nitrogen content of the plant canopies is also the highest in the emasculation period and the grouting period which have the most practical guiding significance for fertilization in the monitoring of the nitrogen content of the plants, so the mNDVI is selected as the most suitable spectral index of the nitrogen content of the maize canopies.
Construction of spectral monitoring model for nitrogen content of canopy of summer corn plant
Based on the most sensitive bands (690nm and 749nm), the optimal band combinations (690nm, 749nm and 753nm) and the optimal spectral index (mNDVI) responded by the original spectral reflectivity and the first-order differential spectrum, four summer corn nitrogen content monitoring models, namely a sensitive band reflectivity model, a sensitive band reflectivity first-order derivative model, a band optimal combination model and a proper spectral index model, are constructed by adopting a stepwise discriminant analysis method, and the determining coefficients (R) are used2) The Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE) are used as model evaluation indexes to carry out the nitrogen content monitoring on the four summer corn modelsAnd (5) checking and determining an optimal summer corn nitrogen content monitoring model. The fitting result of the spectral parameter model of the nitrogen content of the canopy of the summer corn in the whole growth period is shown in the table 3.
TABLE 3 spectral parameter model fitting of nitrogen content in canopy of summer maize in whole growth period
As can be seen from Table 3, a monitoring model of the nitrogen content of the canopy of the summer corn plant based on the original spectrum reflectivity of the sensitive waveband is established by using the natural logarithm function of the spectrum reflectivity of the sensitive waveband 690nm, and the R between the model analog value and the measured value2RMSE, MAE 0.525, 0.447g.g respectively -1、0.360g.g-1. A monitoring model of the nitrogen content of the canopy of the summer corn plant based on the sensitive waveband is established by utilizing a quadratic parabolic function of the first-order derivative of the spectral reflectivity at the sensitive waveband of 749nm, and the R between the simulation value and the measured value of the model2RMSE, MAE were 0.794 and 0.294g.g, respectively-1、0.246g.g-1. Establishing a summer maize plant canopy nitrogen content monitoring model based on the suitable spectral index model by utilizing a quadratic parabolic function of the recommended calculated value of the suitable spectral index model mNDVI, and establishing R between the model simulation value and the measured value2RMSE and MAE were 0.780 and 0.304g.g, respectively-1、0.247g.g-1. The linear regression function of the wave band combination is obtained by adopting a stepwise discriminant analysis method, and the R between the model analog value and the measured value of a summer corn plant canopy nitrogen content monitoring model based on the wave band optimal combination is established2RMSE and MAE were 0.783 and 0.302g.g, respectively-1、0.255g.g-1. Therefore, the 4 models are adopted to monitor the determination coefficient R between the model simulation value and the measured value in the nitrogen content of the canopy of the summer corn plant2>0.49 shows that the monitoring effect of monitoring the nitrogen content of the canopy of the summer corn plants by adopting the 4 models is better.
Synthesizing a sensitive waveband reflectivity model, a sensitive waveband reflectivity first-order derivative model, a waveband optimal combination model and a suitable spectral index model which are created by a small lysimeter test, and utilizing a field community The experimental data were used to validate the model, the results of which are shown in FIG. 7. As can be seen from FIG. 7, R between the simulated value and the measured value of nitrogen content in canopy of summer corn2Both are greater than 0.471, and the RMSE and MAE are respectively less than 0.520g.g-1、0.445g.g-1And the 4 models are proved to have higher precision for simulating the nitrogen content of the canopy. The 4 model simulation effects are ranked by comprehensively considering factors such as model rating and model evaluation index stability in verification and taking the principle that the decision coefficient is high and the error is small as follows: the device comprises a wave band optimal combination model, a suitable spectral index model, a sensitive wave band reflectivity first derivative model and a sensitive wave band reflectivity model.
(eighth) conclusion
In the embodiment, on the basis of monitoring data such as the nitrogen content of the canopy of the summer corn plant, the spectral reflectance of the canopy of the plant and the like under different fertilization treatments obtained by a small lysimeter test, the spectral monitoring sensitive wave band of the nitrogen content of the canopy of the summer corn plant and a proper wave band combination thereof are screened out by analyzing the response relation between the nitrogen content of the canopy of the plant and the spectral reflectance of the canopy of the plant; the most suitable spectral index model for spectral monitoring of the nitrogen content of the canopy of the maize plant in North China is provided on the basis of the principle that the correlation between the calculated value of the spectral index model of the nitrogen content of the plant and the monitoring value of the nitrogen content of the canopy of the plant is the highest and the factors such as the practical guiding significance of the monitoring of the water and fertilizer in the key growth period on the accurate distribution of nutrient elements are supplemented; based on the research results, the corresponding spectrum monitoring models of the sensitive waveband reflectivity, the first derivative of the sensitive waveband reflectivity, the recommended proper spectrum index model, the optimal waveband combination of the recommended proper spectrum index model and the like are established by adopting various methods of the sensitive waveband reflectivity, the first derivative of the sensitive waveband reflectivity, the proper spectrum index, the optimal waveband combination of the band and the like, and the monitoring effects of the 4 models are verified by using field plot test data.
The following conclusions can be drawn from the above examples:
(1) in a visible light wave band, the reflectance of a plant canopy is low due to the absorption effect of chlorophyll, and the reflectance of the wave band is high due to the multiple scattering effect of a plant canopy cell structure in a near infrared region; the spectral reflectance of the canopy of summer maize plants is highest during the maturity period compared to different growing periods; in different fertilization treatment rooms, the spectral reflectivity of the plant canopy is reduced along with the increase of the fertilization amount in a visible light wave band, and the spectral reflectivity of the plant canopy is increased along with the increase of the fertilization amount in a near infrared wave band.
(2) Screening the sensitive wave band for monitoring the nitrogen content of the plant canopy, reducing the redundancy of spectral information and being beneficial to improving the monitoring accuracy of a spectral model. On the basis of researching the correlation between the spectral reflectivity of the canopy of the summer corn plant and the first derivative thereof and the nitrogen content of the canopy of the plant, the optimal band combination is obtained by adopting a step-by-step discriminant analysis method, and the like, and the sensitive bands for monitoring the nitrogen content of the canopy of the corn plant by adopting the original spectrum and the first derivative of the spectrum are respectively positioned at 690nm and 749 nm.
(3) Based on the reported 44 nitrogen spectrum monitoring index models, the correlation analysis is carried out on the calculated value of each nitrogen spectrum monitoring index model and the nitrogen content monitoring value of the canopy of the summer corn plant, 5 spectrum index models with higher correlation coefficient are preferably selected to be mNDVI, MSR sum value, MSR mean value, ND (FD730, FD525) and R780/R740, and the principle of highest correlation of the key growth period is considered, and the mNDVI is recommended to be the most suitable spectrum index model for monitoring the nitrogen content of the summer corn plant.
(4) On the basis of selecting and determining a plant canopy nitrogen content monitoring sensitive band, recommending a proper spectral index model and an optimal band combination thereof, a sensitive band reflectivity model, a sensitive band reflectivity first-order derivative model, a proper spectral index model and a band optimal combination model are respectively constructed, the monitoring effect of monitoring the summer maize plant canopy nitrogen content by adopting the 4 models is better, and the band optimal combination model, the proper spectral index model, the sensitive band reflectivity first-order derivative model and the sensitive band reflectivity model are sequentially arranged from high to low according to the model simulation precision.
Claims (4)
1. A construction method of a summer corn nitrogen content monitoring model based on canopy spectral information is characterized by comprising the following steps:
s1, measuring the original spectral reflectivity and the nitrogen content of the summer corn canopies in different growth periods under different nitrogen nutrition; wherein, the method comprises the steps of collecting the canopy leaves of summer corn plants as samples at intervals of 7-10 days in a growth period;
s2, resampling and deriving the reflectivity of the original spectrum, and determining a first-order differential spectrum of the original spectrum;
s3, calculating correlation coefficients of the nitrogen content of the summer corn canopy, the original spectrum reflectivity and the first-order differential spectrum, and determining the most sensitive wave band corresponding to the original spectrum reflectivity and the first-order differential spectrum which have the maximum correlation with the nitrogen content of the summer corn;
The calculation formula of the correlation coefficient r in step S3 is:
in the formula, n is the actual measurement times;
x i is a firstiSpectral reflectance or first order differential spectrum of individual summer corn canopy;
y i is as followsiThe nitrogen content of the canopy of the summer corn;
s4, analyzing the most sensitive wave band of the summer corn canopy through a multiple stepwise regression analysis method to obtain the optimal wave band combination;
s5, determining the optimal spectral index of spectral monitoring of nitrogen content of the canopy of summer corn; the step S5 specifically includes:
on the basis of the nitrogen spectral monitoring index, performing correlation analysis on each nitrogen monitoring index and the summer corn plant canopy nitrogen content monitoring value, and determining the optimal spectral index for monitoring the canopy nitrogen content in the whole growth period according to the correlation coefficient;
s6, constructing four summer corn nitrogen content monitoring models on the basis of the most sensitive wave band corresponding to the original spectrum reflectivity and the first-order differential spectrum, the optimal wave band combination and the optimal spectrum index;
s7, testing the four summer corn nitrogen content monitoring models through model evaluation indexes to determine the optimal summer corn nitrogen content monitoring model in the whole growth period, wherein the model evaluation indexes in the step S7 are a decision coefficient, a root mean square error and an average absolute error;
Wherein, the most sensitive wave bands corresponding to the original spectral reflectivity and the first-order differential spectrum with the maximum correlation of the nitrogen content of the summer corn in the S3 are 690nm and 749nm respectively; the optimal waveband combination in the S4 is 690nm, 749nm and 753 nm; the optimal spectral index in the S5 is mNDVI; the four summer corn nitrogen content monitoring models in the S6 are respectively y = -0.594ln (R)690)+ 0.1227、y = -43043(R749')2 + 613.46(R749') + 0.3379、y = 13.818x2-14.885x + 4.8433 and y =0.593-2.107R690+77.031R753-75.761R749；y = 13.818x2-14.885x + 4.8433 is a model built from the optimal spectral index mNDVI.
2. The method for constructing the summer corn nitrogen content monitoring model based on the canopy spectral information as claimed in claim 1, wherein the method for measuring the original spectral reflectance of the summer corn canopy in the step S1 is specifically as follows:
monitoring the original spectral reflectivity of the canopy layer in the growth period of the summer corn through a spectrometer, performing standard white board correction in the monitoring process, monitoring the spectral reflectivity of a plurality of summer corns in each small lysimeter, and taking the arithmetic average value of the spectral reflectivities as the original spectral reflectivity of the canopy layer of the summer corn of the small lysimeter;
the monitoring parameters of the original spectral reflectivity of the summer corn canopy are set as follows: the spectrum band is 325nm ~1075nm, and monitoring sampling interval is 1nm, and spectral resolution is 3nm, and monitoring time is 10: 00-14: 00, a probe of a spectrometer sensor is vertically downward, the field angle of the spectrometer is 25 degrees, and the vertical height from the top of a canopy of summer corn is 10-20 cm.
3. The method for constructing the summer corn nitrogen content monitoring model based on the canopy spectral information as claimed in claim 1, wherein the method for measuring the nitrogen content of the summer corn canopy in the step S1 specifically comprises:
cutting the plant, deactivating enzyme and oven drying, grinding the oven dried sample into powder, and pulverizing with H2SO4-H2O2Digestion, and finally measuring by using a Kjeldahl apparatus.
4. The method for constructing the summer corn nitrogen content monitoring model based on the canopy spectral information as claimed in claim 1, wherein the step S4 is specifically as follows:
and performing regression analysis on the spectral reflectivity and the nitrogen content value of the summer corn canopy within the range of 325 nm-1075 nm by adopting a multivariate stepwise regression analysis method to obtain the optimal band combination of the summer corn plant canopy.
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