CN109632688B - Plant seedling nutrient profit and loss state identification method and spectrum detection system - Google Patents
Plant seedling nutrient profit and loss state identification method and spectrum detection system Download PDFInfo
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- 241000196324 Embryophyta Species 0.000 title claims abstract description 97
- 235000015097 nutrients Nutrition 0.000 title claims abstract description 64
- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000001514 detection method Methods 0.000 title claims abstract description 19
- 238000001228 spectrum Methods 0.000 title claims description 61
- 239000003337 fertilizer Substances 0.000 claims abstract description 22
- 238000012545 processing Methods 0.000 claims abstract description 21
- 238000009331 sowing Methods 0.000 claims abstract description 18
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 12
- 239000013307 optical fiber Substances 0.000 claims description 18
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 9
- 239000011159 matrix material Substances 0.000 claims description 8
- 230000007812 deficiency Effects 0.000 claims description 5
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- 235000018343 nutrient deficiency Nutrition 0.000 claims description 4
- 238000002310 reflectometry Methods 0.000 claims description 4
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- 238000005507 spraying Methods 0.000 claims description 4
- 238000004659 sterilization and disinfection Methods 0.000 claims description 4
- 238000003756 stirring Methods 0.000 claims description 4
- 238000012258 culturing Methods 0.000 claims description 3
- 239000000203 mixture Substances 0.000 claims description 3
- 230000004720 fertilization Effects 0.000 abstract description 18
- 239000000126 substance Substances 0.000 abstract description 6
- 238000002474 experimental method Methods 0.000 abstract description 5
- 235000016709 nutrition Nutrition 0.000 abstract description 3
- 230000035764 nutrition Effects 0.000 abstract description 3
- 235000007688 Lycopersicon esculentum Nutrition 0.000 description 46
- 240000003768 Solanum lycopersicum Species 0.000 description 46
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 29
- 229910052757 nitrogen Inorganic materials 0.000 description 15
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 description 10
- ZLMJMSJWJFRBEC-UHFFFAOYSA-N Potassium Chemical compound [K] ZLMJMSJWJFRBEC-UHFFFAOYSA-N 0.000 description 10
- 229910052698 phosphorus Inorganic materials 0.000 description 10
- 239000011574 phosphorus Substances 0.000 description 10
- 239000011591 potassium Substances 0.000 description 10
- 229910052700 potassium Inorganic materials 0.000 description 10
- 238000000985 reflectance spectrum Methods 0.000 description 3
- 239000000758 substrate Substances 0.000 description 3
- XSQUKJJJFZCRTK-UHFFFAOYSA-N Urea Chemical compound NC(N)=O XSQUKJJJFZCRTK-UHFFFAOYSA-N 0.000 description 2
- 239000004202 carbamide Substances 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- OTYBMLCTZGSZBG-UHFFFAOYSA-L potassium sulfate Chemical compound [K+].[K+].[O-]S([O-])(=O)=O OTYBMLCTZGSZBG-UHFFFAOYSA-L 0.000 description 2
- 229910052939 potassium sulfate Inorganic materials 0.000 description 2
- 235000011151 potassium sulphates Nutrition 0.000 description 2
- WZLMXYBCAZZIRQ-UHFFFAOYSA-N [N].[P].[K] Chemical compound [N].[P].[K] WZLMXYBCAZZIRQ-UHFFFAOYSA-N 0.000 description 1
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- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 229910000402 monopotassium phosphate Inorganic materials 0.000 description 1
- 235000019796 monopotassium phosphate Nutrition 0.000 description 1
- 239000000618 nitrogen fertilizer Substances 0.000 description 1
- QJGQUHMNIGDVPM-UHFFFAOYSA-N nitrogen group Chemical group [N] QJGQUHMNIGDVPM-UHFFFAOYSA-N 0.000 description 1
- 239000003415 peat Substances 0.000 description 1
- 239000010451 perlite Substances 0.000 description 1
- 235000019362 perlite Nutrition 0.000 description 1
- 239000002686 phosphate fertilizer Substances 0.000 description 1
- GNSKLFRGEWLPPA-UHFFFAOYSA-M potassium dihydrogen phosphate Chemical compound [K+].OP(O)([O-])=O GNSKLFRGEWLPPA-UHFFFAOYSA-M 0.000 description 1
- LWIHDJKSTIGBAC-UHFFFAOYSA-K potassium phosphate Substances [K+].[K+].[K+].[O-]P([O-])([O-])=O LWIHDJKSTIGBAC-UHFFFAOYSA-K 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000010455 vermiculite Substances 0.000 description 1
- 235000019354 vermiculite Nutrition 0.000 description 1
- 229910052902 vermiculite Inorganic materials 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
- 229910052724 xenon Inorganic materials 0.000 description 1
- FHNFHKCVQCLJFQ-UHFFFAOYSA-N xenon atom Chemical compound [Xe] FHNFHKCVQCLJFQ-UHFFFAOYSA-N 0.000 description 1
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- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
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- G—PHYSICS
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
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Abstract
The invention relates to the technical field of crop nutrition condition detection, in particular to a method for identifying the nutrient profit and loss state of plant seedlings, which comprises the following steps: s1, adding fertilizers with different quantities or proportions in the process of sowing or growing the plant seedlings to ensure that the plant seedlings grow to present different nutrient profit and loss states; s2, collecting the near infrared spectrum of the plant seedling cotyledon in the seedling growing process; s3, processing the near infrared spectrum data to obtain the red edge position information of the plant seedling cotyledon; s4, obtaining the red edge position distribution of the plant seedling cotyledons under different nutrient profit and loss states according to the red edge position information of the plant seedling cotyledons; and S5, finding a boundary point for distinguishing the nutrient profit and loss state of the plant seedling in the red edge position distribution of the plant seedling cotyledon. The invention solves the problems that the prior plug seedling is applied by experience and the fertilization time point is controlled inaccurately, does not need to obtain reference values through physical and chemical experiments, and has simple and easy modeling method.
Description
Technical Field
The invention relates to the technical field of crop nutrition condition detection, in particular to a plant seedling nutrient profit and loss state identification method and a spectrum detection system.
Background
At present, in the tomato planting process, the seedling nutrient condition is directly related to the tomato planting quality and yield, and the normal growth of seedlings is influenced due to unreasonable nutrient supply ratio or quantity, so that the appearance quality is reduced, the growth is poor, and particularly, the problem that the growth of tomato seedlings is adversely influenced due to the high-concentration instant fertilizer applied in seedling culture is likely to occur. In order to avoid nutrient deficiency, some producers apply excessive nitrogen, phosphorus and potassium fertilizers, so that not only is the fertilizer waste and the environmental pollution caused, but also the tomato quality and the tomato yield are reduced.
A paper published in agricultural engineering newspaper, namely tomato nitrogen phosphorus potassium nutrition level rapid diagnosis based on hyperspectrum, utilizes a reflection spectrum technology diagnosis method to respectively establish tomato leaf nitrogen, phosphorus and potassium models based on spectrum and image characteristics, obtains better research results, can identify nutrient profit and loss states of tomato leaves, but has complex, tedious, time-consuming and labor-consuming modeling process, needs to obtain the nitrogen, phosphorus and potassium contents of experimental samples through physical, chemical and other methods, and takes the measured values of the nitrogen, phosphorus and potassium contents as reference values to be subjected to modeling.
Disclosure of Invention
Technical problem to be solved
The invention aims to solve the technical problems that the existing method for identifying the nutrient profit and loss state of plant leaves needs to obtain a measured value as a reference value to participate in modeling through physical and chemical methods, and the modeling process is complex, time-consuming and labor-consuming.
(II) technical scheme
In order to solve the technical problem, the invention provides a method for identifying the nutrient profit and loss state of plant seedlings, which comprises the following steps:
s1, adding fertilizers with different quantities or proportions in the process of sowing or growing the plant seedlings to ensure that the plant seedlings grow to present different nutrient profit and loss states;
s2, collecting the near infrared spectrum of the plant seedling cotyledon in the seedling growing process;
s3, processing the near infrared spectrum data to obtain the red edge position information of the plant seedling cotyledon;
s4, obtaining the red edge position distribution of the plant seedling cotyledons under different nutrient profit and loss states according to the red edge position information of the plant seedling cotyledons;
and S5, finding a boundary point for distinguishing the nutrient profit and loss state of the plant seedling in the red edge position distribution of the plant seedling cotyledon.
Wherein, step S1 specifically includes the following steps:
s11, dissolving the fertilizer in water, spraying the fertilizer into a quantitative mixed matrix, stirring and then putting the mixture into a plug tray;
s12, soaking plant seeds in hot water at 55-60 ℃ for disinfection, accelerating germination, finely sowing the seeds in a hole tray, and culturing the seeds in a greenhouse, wherein one seed is put in each hole.
Wherein, step S2 specifically includes the following steps:
s21, preheating the spectrum detection system for 15 minutes, and enabling the light source and the spectrometer to be in a stable working state;
s22, collecting the spectrum information of the standard reference white board by the spectrometer;
s23, cutting off the light source unit, and collecting spectral information of a dark environment by the spectrometer;
s24, communicating a light source unit, and collecting the reflection spectrum information of the plant seedling cotyledon by a spectrometer;
and S25, automatically performing white reference calibration and black reference calibration on the reflection spectrum of the plant seedling cotyledon by using the spectrometer.
In step S25, the reference formula of white reference calibration and black reference calibration of the spectrum of the reflection spectrum of the plant seedling cotyledon by the spectrometer is
Wherein R isλThe reflectivity of the plant seedling cotyledon at the standard section lambda is represented; sλThe reflected light intensity of the plant seedling cotyledon at the standard section lambda is represented; b isλRepresenting the reflected light intensity of the dark environment at the mark segment lambda; wλIndicating the reflected light intensity of the reference whiteboard at marker segment lambda.
Wherein, step S3 specifically includes the following steps:
s31, performing first order differential processing on the reflection spectrum to obtain a first order differential spectrum, wherein the approximate calculation formula of the first order differential processing is
Wherein λ isiIs the wavelength value of the band i; ρ (λ)i) Is a wavelength lambdaiSpectral reflectance values of; ρ' (λ)i) Is the first order differential value of the band i;
and S32, extracting the wavelength corresponding to the maximum value of the first-order differential spectrum in the interval of 680-750 nm from the data of the first-order differential spectrum as red edge position information.
In step S5, the red edge position of the boundary point of the plant seedling nutrient excess and deficiency state is 705-712 nm, when the red edge position of the plant seedling cotyledon is less than 705nm, the plant seedling nutrient deficiency occurs, and when the red edge position of the plant seedling cotyledon is greater than 712nm, the plant seedling nutrient excess occurs.
The invention also provides a spectrum detection system for identifying the nutrient profit and loss state of plant seedlings, which comprises a light source unit, a spectrometer, a data processing unit and a dark box, wherein the light source unit and the spectrometer are both arranged in the dark box, the spectrometer is connected with the light source unit, the data processing unit is connected with the spectrometer, and the detection wavelength range of the spectrometer comprises 680-750 nm.
The light source unit comprises a light source, an optical fiber and an attenuator, one end of the optical fiber is connected with the light source, the other end of the optical fiber is fixed in the dark box in a hanging mode through a support, the attenuator is arranged on the optical fiber, and the spectrometer is connected with the optical fiber.
(III) advantageous effects
The technical scheme of the invention has the following advantages: the plant seedling nutrient profit and loss state identification method is a method for establishing a seedling nutrient profit and loss state identification model based on the red edge characteristics of plants, firstly, fertilizers such as nitrogen, phosphorus, potassium and the like in different quantities or proportions are added in the plant seedling sowing or growing process, so that the seedlings grow to present different nutrient profit and loss states; secondly, in the seedling growth process, near infrared spectrums of seedling cotyledons are collected at different time nodes, and spectrum data collected at the different time nodes are processed to extract red edge position information; and finally, finding out a boundary point for distinguishing the nutrient profit and loss states of the tomato seedlings according to the red edge position distribution of the seedling leaves in different nutrient profit and loss states. The invention solves the problems that the prior plug seedling is applied by experience and the fertilization time point is controlled inaccurately, does not need to obtain reference values through physical and chemical experiments, and has simple and easy modeling method.
In addition to the technical problems addressed by the present invention, the technical features constituting the technical solutions and the advantages brought by the technical features of the technical solutions described above, other technical features of the present invention and the advantages brought by the technical features of the technical solutions will be further explained with reference to the accompanying drawings.
Drawings
FIG. 1 is a schematic structural diagram of a spectral detection system for identifying the nutrient profit and loss state of plant seedlings according to an embodiment of the invention;
FIG. 2 is a cotyledon reflectance spectrum curve of a tomato seedling in the fourth week after sowing according to the method for identifying the nutrient profit-and-loss state of a plant seedling in the embodiment of the present invention;
FIG. 3 is a cotyledon reflectance spectrum curve of a tomato seedling at the fifth week after sowing according to the method for identifying the nutrient profit-and-loss state of a plant seedling of the embodiment of the present invention;
FIG. 4 is a cotyledon reflectance spectrum curve of a tomato seedling at the sixth week after sowing according to the method for identifying the nutrient profit-and-loss state of a plant seedling of the embodiment of the present invention;
FIG. 5 shows the cotyledon red edge position of the tomato seedling in the fourth week according to the method for identifying the nutrient profit-and-loss state of the plant seedling in the embodiment of the invention;
FIG. 6 shows the cotyledon red edge position of a tomato seedling in the fifth week of the plant seedling nutrient profit-and-loss state identification method of the embodiment of the invention;
FIG. 7 shows the cotyledon red edge position of a tomato seedling in the sixth week of the plant seedling nutrient profit-and-loss state identification method of the embodiment of the present invention.
In the figure: 1: a light source unit; 2: a spectrometer; 3: a dark box; 4: a support; 11: a light source; 12: an optical fiber; 13: an attenuator.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In addition, in the description of the present invention, unless otherwise specified, "plurality", "plural groups" means two or more, and "several", "several groups" means one or more.
The method for identifying the nutrient profit and loss state of the plant seedlings provided by the embodiment of the invention comprises the following steps:
s1, adding fertilizers with different quantities or proportions in the process of sowing or growing the plant seedlings to ensure that the plant seedlings grow to present different nutrient profit and loss states;
s2, collecting the near infrared spectrum of the plant seedling cotyledon in the seedling growing process;
s3, processing the near infrared spectrum data to obtain the red edge position information of the plant seedling cotyledon;
s4, obtaining the red edge position distribution of the plant seedling cotyledons under different nutrient profit and loss states according to the red edge position information of the plant seedling cotyledons;
and S5, finding a boundary point for distinguishing the nutrient profit and loss state of the plant seedling in the red edge position distribution of the plant seedling cotyledon.
The plant seedling nutrient profit and loss state identification method is a method for establishing a seedling nutrient profit and loss state identification model based on the red edge characteristics of plants, firstly, fertilizers such as nitrogen, phosphorus, potassium and the like in different quantities or proportions are added in the plant seedling sowing or growing process, so that the seedlings grow to present different nutrient profit and loss states; secondly, in the seedling growth process, near infrared spectrums of seedling cotyledons are collected at different time nodes, and spectrum data collected at the different time nodes are processed to extract red edge position information; and finally, finding out a boundary point for distinguishing the nutrient profit and loss states of the tomato seedlings according to the red edge position distribution of the seedling leaves in different nutrient profit and loss states. The invention solves the problems that the prior plug seedling is applied by experience and the fertilization time point is controlled inaccurately, does not need to obtain reference values through physical and chemical experiments, and has simple and easy modeling method.
Wherein, step S1 specifically includes the following steps:
s11, dissolving the fertilizer in water, spraying the fertilizer into a quantitative mixed matrix, stirring and then putting the mixture into a plug tray;
s12, soaking plant seeds in hot water at 55-60 ℃ for disinfection, accelerating germination, finely sowing the seeds in a hole tray, and culturing the seeds in a greenhouse, wherein one seed is put in each hole.
Wherein, step S2 specifically includes the following steps:
s21, preheating the spectrum detection system for 15 minutes, and enabling the light source and the spectrometer to be in a stable working state;
s22, collecting the spectrum information of the standard reference white board by the spectrometer;
s23, cutting off the light source unit, and collecting spectral information of a dark environment by the spectrometer;
s24, communicating a light source unit, and collecting the reflection spectrum information of the plant seedling cotyledon by a spectrometer;
and S25, automatically performing white reference calibration and black reference calibration on the reflection spectrum of the plant seedling cotyledon by using the spectrometer.
In step S25, the reference formula of white reference calibration and black reference calibration of the spectrum of the reflection spectrum of the plant seedling cotyledon by the spectrometer is
Wherein R isλThe reflectivity of the plant seedling cotyledon at the standard section lambda is represented; sλThe reflected light intensity of the plant seedling cotyledon at the standard section lambda is represented; b isλRepresenting the reflected light intensity of the dark environment at the mark segment lambda; wλIndicating the reflected light intensity of the reference whiteboard at marker segment lambda.
Wherein, step S3 specifically includes the following steps:
s31, performing first order differential processing on the reflection spectrum to obtain a first order differential spectrum, wherein the approximate calculation formula of the first order differential processing is
Wherein λ isiIs the wavelength value of the band i; ρ (λ)i) Is a wavelength lambdaiSpectral reflectance values of; ρ' (λ)i) Is the first order differential value of the band i;
and S32, extracting the wavelength corresponding to the maximum value of the first-order differential spectrum in the interval of 680-750 nm from the data of the first-order differential spectrum as red edge position information.
In step S5, the red edge position of the boundary point of the plant seedling nutrient excess and deficiency state is 705-712 nm, when the red edge position of the plant seedling cotyledon is less than 705nm, the plant seedling nutrient deficiency occurs, and when the red edge position of the plant seedling cotyledon is greater than 712nm, the plant seedling nutrient excess occurs.
The implementation provides a method for identifying the nutrient excess and deficiency state of tomato seedlings, wherein experimental materials comprise 10 plug trays with 105 holes and the variety of tomato seeds of Tianma No. 54, a seedling culture substrate (peat: vermiculite: perlite: 2:1:1), urea, a quick-acting phosphate fertilizer, potassium sulfate, an electronic balance and a beaker.
Under the normal condition of tomato plug seedling, the seedling substrate is added with nitrogen (urea), phosphorus (monopotassium phosphate) and potassium (potassium sulfate) fertilizers with different contents and proportions to carry out the tomato plug seedling, and the growth vigor of the seedlings is observed. In the experiment, the fertilizing amount and the fertilizing proportion are treated by 5 groups, the treatment is repeated for 1 time, and the concentration of nitrogen, phosphorus and potassium fertilizers in the seedling culture substrate is designed as shown in the following table:
fertilizing concentration and proportion table of nitrogen, phosphorus and potassium fertilizer
Dissolving the fertilizer required by each treatment in water, spraying into a certain amount of mixed matrix, fully and uniformly stirring, filling into a hole tray, soaking tomato seeds in hot water at 55-60 ℃ for disinfection and accelerating germination, finely sowing in the hole tray, and placing one fertilizer in each hole for cultivation in a greenhouse. As the fertilizer to be tested is completely applied into the matrix at one time, only clear water is needed to be irrigated daily to keep the matrix moist, and other management measures are the same. At the fourth, fifth and sixth weeks after sowing, the visible/near infrared spectra of the seedlings were collected for a total of 506 seedlings.
Preheating a spectrum detection system for 15 minutes to enable a light source and a spectrometer to be in a stable working state, then collecting spectrum information of a standard reference white board, cutting off a light path, and collecting spectrum information of a dark environment; communicating a light path, collecting the reflection spectrum information of the tomato plug seedling cotyledon, and using a spectrometer to obtain the reflection spectrum information according to a formula
Automatically performing white reference calibration and black reference calibration on the reflection spectrum of the tomato seeds, wherein RλThe reflectivity of the plant seedling cotyledon at the standard section lambda is represented; sλThe reflected light intensity of the plant seedling cotyledon at the standard section lambda is represented; b isλRepresenting the reflected light intensity of the dark environment at the mark segment lambda; wλIndicating the reflected light intensity of the reference whiteboard at marker segment lambda. The integration time of spectrum collection is set to 8ms, the average frequency is set to 15 times, the smoothness is set to 1, and the spectrum data is stored and then is subjected to subsequent processing. The visible/near infrared reflection spectrum curves of the tomato plug seedlings collected 3 times are shown in fig. 2, fig. 3 and fig. 4, and the wavelength range is 380-970 nm.
Adopting a spectrum normalized differential analysis technology to perform one on the reflection spectrum data in Matlab softwareDifferential spectrum is obtained by order differential processing, and the approximate calculation method of first order differential processing is shown as formula
Shown in whichiIs the wavelength value of the band i; ρ (λ)i) Is a wavelength lambdaiSpectral reflectance values of; ρ' (λ)i) Is the first order differential value of the band i; further extracting a red edge position (a wavelength corresponding to the maximum value of the first derivative spectrum in the interval of 680-750 nm) from the first derivative spectrum data. In this study, the red-pass position curves of the seedling leaves of the experimental group and the parallel experimental group are shown in fig. 5, 6 and 7, where Δ is group number 1; + is group number 2; o is group number 3; x is group number 4; □ is group number 5.
It is found by fig. 5, 6 and 7 that:
(1) the red edge positions of the cotyledons of the tomato seedlings are distributed in two areas: 712-717 nm and 697-705 nm, and the boundary point is 705-712 nm.
(2) In the fourth week after sowing, the tomato seedlings under the condition of fertilizing treatment group number 1 are in a deficient state, the red edge positions of the cotyledons of the tomato seedlings of the experimental group and the repeated group are less than 705nm and are positioned in the area of 697-705 nm; the tomato seedling nitrogen nutrient under the condition of fertilization treatment group No. 5 is in surplus state, the red edge position of the cotyledon of the tomato seedling of the experimental group and the tomato seedling of the repeated group is larger than 712nm, and the red edge position is in 712-717 nm area; from fertilization treatment group No. 1 to fertilization treatment group No. 5, the red edge position of the cotyledon of the tomato seedling was shifted to the right with the increase of the nitrogen application amount. And when the nitrogen nutrients of the tomato seedlings are in surplus state, the red edge position of the seedling cotyledon is greater than 715nm and is 712-717 nm.
(3) In the fifth week after sowing, with the growth of the plug seedlings of the tomatoes, the nutrient supply in the matrix is continuously reduced, and the red edge positions of the cotyledons of the tomato seedlings of the experimental group and the repeated group under the condition of the fertilization treatment group number 1 are still less than 705nm and are positioned in the area of 697-705 nm; the red edge positions of the tomato seedling cotyledons of the experimental group and the repeated group under the condition of the fertilization treatment group number 5 mostly move from 712-717 nm to 697-705 nm, and the red edge positions of the tomato seedling cotyledons all have a left-moving phenomenon under the conditions of the fertilization treatment group number 2, the fertilization treatment group number 3, the fertilization treatment group number 4 and the fertilization treatment group number 5.
(4) In the 6 th week after sowing, with the growth of the tomato plug seedlings, the nutrients in the matrix are continuously consumed and are in a depletion state, and the red edge positions of the cotyledons of the tomato seedlings of the experimental group and the repeated group under the condition of the fertilization treatment group number 1 are still less than 705nm and are positioned in the area of 697-705 nm; under the conditions of the fertilization treatment group No. 2, the fertilization treatment group No. 3, the fertilization treatment group No. 4 and the fertilization treatment group No. 5, the red edge positions of the cotyledon of the tomato seedling of the experimental group and the tomato seedling of the repeated group are all moved from the area 712-717 nm to the area 697-705 nm. When the nitrogen nutrients of the tomato seedlings are in a deficiency state, the red edge position of the seedling cotyledon is smaller than 705nm and is positioned in a region 697-705 nm.
With the increase of the fertilizing amount of the nitrogen fertilizer, the red edge position of the leaf blade of the tomato seedling moves to the right, and with the continuous growth of the plug seedling of the tomato, the red edge position of the leaf blade of the tomato seedling moves to the left, and the red edge position of the nitrogen nutrient profit and loss boundary point of the tomato seedling is indicated to be 705-712 nm.
As shown in fig. 1, an embodiment of the present invention further provides a spectrum detection system for identifying the nutrient profit and loss state of plant seedlings, including a light source unit 1, a spectrometer 2, a data processing unit and a dark box 3, wherein the light source unit 1 and the spectrometer 2 are both disposed in the dark box 3, the spectrometer 2 is connected with the light source unit 1, the data processing unit 3 is connected with the spectrometer 3, and the detection wavelength range of the spectrometer 2 includes 680 to 750 nm.
The light source unit 1 comprises a light source 11, an optical fiber 12 and an attenuator 13, one end of the optical fiber 12 is connected with the light source 11, the other end of the optical fiber 12 is suspended and fixed in the dark box 3 through a support 4, the attenuator 13 is arranged on the optical fiber 12, and the spectrometer 2 is connected with the optical fiber 12.
The invention relates to a spectrum detection system for identifying the nutrient profit and loss state of plant seedlings, which mainly comprises a light source unit, a spectrometer, a data processing unit and a dark box. The spectrometer is used as a spectrum data acquisition unit, and in the embodiment, the spectrometer with the detection wavelength range of 380-970nm and the spectral resolution of 0.14-7.7nm can be selected; the data processing unit can be a computer; the light source unit comprises a xenon lamp light source, an optical fiber and an optical fiber attenuator, the light source is also provided with a stabilized voltage power supply and a heat dissipation device, and the wavelength range of the light source is 185-2200 nm; the function of the dark box is to isolate the interference of external light.
In summary, the plant seedling nutrient profit and loss state identification method is a method for establishing a seedling nutrient profit and loss state identification model based on the red edge characteristics of plants, and firstly, fertilizers such as nitrogen, phosphorus, potassium and the like in different quantities or proportions are added in the plant seedling sowing or growing process, so that the seedling grows to present different nutrient profit and loss states; secondly, in the seedling growth process, near infrared spectrums of seedling cotyledons are collected at different time nodes, and spectrum data collected at the different time nodes are processed to extract red edge position information; and finally, finding out a boundary point for distinguishing the nutrient profit and loss states of the tomato seedlings according to the red edge position distribution of the seedling leaves in different nutrient profit and loss states. The invention solves the problems that the prior plug seedling is applied by experience and the fertilization time point is controlled inaccurately, does not need to obtain reference values through physical and chemical experiments, and has simple and easy modeling method.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (5)
1. A method for identifying the nutrient profit and loss state of plant seedlings is characterized by comprising the following steps: the method comprises the following steps:
s1, adding fertilizers with different quantities or proportions in the process of sowing or growing the plant seedlings to ensure that the plant seedlings grow to present different nutrient profit and loss states;
s2, collecting the near infrared spectrum of the plant seedling cotyledon in the seedling growing process;
s3, processing the near infrared spectrum data to obtain the red edge position information of the plant seedling cotyledon;
s4, obtaining the red edge position distribution of the plant seedling cotyledons under different nutrient profit and loss states according to the red edge position information of the plant seedling cotyledons;
s5, finding a boundary point for distinguishing the nutrient profit and loss state of the plant seedling in the red edge position distribution of the plant seedling cotyledon;
step S2 specifically includes the following steps:
s21, preheating the spectrum detection system for 15 minutes, and enabling the light source and the spectrometer to be in a stable working state;
s22, collecting the spectrum information of the standard reference white board by the spectrometer;
s23, cutting off the light source unit, and collecting spectral information of a dark environment by the spectrometer;
s24, communicating a light source unit, and collecting the reflection spectrum information of the plant seedling cotyledon by a spectrometer;
s25, automatically performing white reference calibration and black reference calibration on the reflection spectrum of the plant seedling cotyledon by using a spectrometer;
in step S25, the reference formula of white reference calibration and black reference calibration of the reflection spectrum of the plant seedling cotyledon by the spectrometer is
Wherein R isλThe reflectivity of the plant seedling cotyledon at the standard section lambda is represented; sλThe reflected light intensity of the plant seedling cotyledon at the standard section lambda is represented; b isλRepresenting the reflected light intensity of the dark environment at the mark segment lambda; wλRepresenting the reflected light intensity of the reference whiteboard at marker segment λ;
step S3 specifically includes the following steps:
s31, performing first order differential processing on the reflection spectrum to obtain a first order differential spectrum, wherein the approximate calculation formula of the first order differential processing is
Wherein λ isiIs the wavelength value of the band i; ρ (λ)i) Is a wavelength lambdaiSpectral reflectance values of; ρ' (λ)i) Is the first order differential value of the band i;
and S32, extracting the wavelength corresponding to the maximum value of the first-order differential spectrum in the interval of 680-750 nm from the data of the first-order differential spectrum as red edge position information.
2. The method for identifying the nutrient profit-loss state of plant seedlings according to claim 1, which is characterized in that: step S1 specifically includes the following steps:
s11, dissolving the fertilizer in water, spraying the fertilizer into a quantitative mixed matrix, stirring and then putting the mixture into a plug tray;
s12, soaking plant seeds in hot water at 55-60 ℃ for disinfection, accelerating germination, finely sowing the seeds in a hole tray, and culturing the seeds in a greenhouse, wherein one seed is put in each hole.
3. The method for identifying the nutrient profit-loss state of plant seedlings according to claim 1, which is characterized in that: in step S5, the red edge of the boundary point of the plant seedling nutrient excess and deficiency state is 705-712 nm, when the red edge of the plant seedling cotyledon is less than 705nm, the plant seedling nutrient deficiency occurs, and when the red edge of the plant seedling cotyledon is greater than 712nm, the plant seedling nutrient excess occurs.
4. A spectrum detection system using the method for identifying the nutrient profit and loss state of plant seedlings according to any one of claims 1 to 3, which is characterized in that: including light source unit, spectrum appearance, data processing unit and camera bellows, the light source unit with the spectrum appearance all set up in the camera bellows, the spectrum appearance with the light source unit is connected, data processing unit with the spectrum appearance is connected, the detection wavelength range of spectrum appearance contains 680 ~ 750 nm.
5. The spectroscopic detection system of claim 4, wherein: the light source unit comprises a light source, an optical fiber and an attenuator, one end of the optical fiber is connected with the light source, the other end of the optical fiber is fixed in the dark box in a hanging mode through a support, the attenuator is arranged on the optical fiber, and the spectrometer is connected with the optical fiber.
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