CN117195609A - Quantitative diagnosis method for nitrogen nutrient deficiency of regional corn plants - Google Patents
Quantitative diagnosis method for nitrogen nutrient deficiency of regional corn plants Download PDFInfo
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- CN117195609A CN117195609A CN202311479392.XA CN202311479392A CN117195609A CN 117195609 A CN117195609 A CN 117195609A CN 202311479392 A CN202311479392 A CN 202311479392A CN 117195609 A CN117195609 A CN 117195609A
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- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 title claims abstract description 104
- 229910052757 nitrogen Inorganic materials 0.000 title claims abstract description 52
- 238000003745 diagnosis Methods 0.000 title claims abstract description 26
- 241001057636 Dracaena deremensis Species 0.000 title claims abstract description 23
- 235000018343 nutrient deficiency Nutrition 0.000 title claims abstract description 19
- 238000000034 method Methods 0.000 title claims abstract description 18
- 240000008042 Zea mays Species 0.000 claims abstract description 43
- 239000002028 Biomass Substances 0.000 claims abstract description 34
- 235000002017 Zea mays subsp mays Nutrition 0.000 claims abstract description 28
- 235000005824 Zea mays ssp. parviglumis Nutrition 0.000 claims abstract description 26
- 235000005822 corn Nutrition 0.000 claims abstract description 26
- 241000196324 Embryophyta Species 0.000 claims abstract description 20
- 235000016709 nutrition Nutrition 0.000 claims abstract description 20
- 230000035764 nutrition Effects 0.000 claims abstract description 20
- 230000007812 deficiency Effects 0.000 claims abstract description 9
- 238000010276 construction Methods 0.000 claims abstract description 4
- 230000003595 spectral effect Effects 0.000 claims abstract description 4
- 238000004364 calculation method Methods 0.000 claims description 8
- 238000009825 accumulation Methods 0.000 claims description 3
- 125000004122 cyclic group Chemical group 0.000 claims description 2
- 238000002405 diagnostic procedure Methods 0.000 claims 5
- 238000001514 detection method Methods 0.000 abstract description 3
- 235000016383 Zea mays subsp huehuetenangensis Nutrition 0.000 abstract description 2
- 235000009973 maize Nutrition 0.000 abstract description 2
- 239000000618 nitrogen fertilizer Substances 0.000 abstract description 2
- 230000004720 fertilization Effects 0.000 description 3
- 244000038559 crop plants Species 0.000 description 2
- 235000013305 food Nutrition 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 239000000243 solution Substances 0.000 description 2
- 208000002720 Malnutrition Diseases 0.000 description 1
- 230000032683 aging Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000009360 aquaculture Methods 0.000 description 1
- 244000144974 aquaculture Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000012895 dilution Substances 0.000 description 1
- 238000010790 dilution Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 239000003041 laboratory chemical Substances 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000003900 soil pollution Methods 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
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Abstract
The invention relates to the technical field of crop performance detection, in particular to a quantitative diagnosis method for nitrogen nutrition deficiency of regional corn plants, which comprises the following steps: s1: acquiring spectral data of a maize plant and calculatingMSRAn index; s2: based onMSRExponential constructionNNIInverting the model; s3: obtaining cornLAIData and calculate plant biomass of maizeBiomassThe method comprises the steps of carrying out a first treatment on the surface of the S4: according toNNI、NNI target And plant biomassBiomassCalculating the nitrogen content to be absorbed of the corn plantsN abs When the optimal yield of corn is taken asAccording to the quantitative diagnosis of the nitrogen nutrition deficiency of the regional corn plants,NNI target =1, when quantitatively diagnosing nitrogen nutrient deficiency of regional maize plants based on the optimal protein content of maize,NNI target =0.8. The diagnosis method can quantitatively judge the nutrition deficiency condition of the corn plants, and clearly calculate the nitrogenous fertilizer requirement of the corn.
Description
Technical Field
The invention relates to the technical field of crop performance detection, in particular to a quantitative diagnosis method for nitrogen nutrition deficiency of regional corn plants.
Background
Corn is an important food crop, has strong drought resistance, cold resistance, barren resistance and excellent environmental adaptability, is an important feed source for animal husbandry, aquaculture industry and the like, and is also one of indispensable raw materials for food, medical health, light industry, chemical industry and the like, so that the diagnosis of the performance of the corn is very important. In the diagnosis of corn performance, real-time monitoring and accurate assessment of the nitrogen nutrition status are of great significance to improving the nitrogen fertilizer utilization efficiency and reducing the environmental pollution.
The modern spectrum remote sensing technology has the advantages of timeliness, accuracy and nondestructive monitoring, overcomes the defects of long period, poor aging and the like of the traditional crop nitrogen nutrition diagnosis method based on laboratory chemical analysis means, and is widely applied to crop nutrition diagnosis, thus becoming a hot spot and key of modern accurate agricultural research. The existing crop remote sensing diagnosis method is mainly contact detection, but the difficulty of guiding fertilization and exploring soil pollution by acquiring the nutrition status of a large-area crop is high, and remote sensing can acquire some information on the surface of a crop plant as a novel mode so as to reflect the nitrogen nutrition deficiency status of the crop plant, but at present, only the nitrogen nutrition level of the plant can be judged qualitatively in a multi-dimensional manner, and quantitative judgment still cannot be achieved to finish the work such as fertilization guidance.
Therefore, how to propose a remote sensing diagnosis method for quantitatively judging the nutritional deficiency of corn plants is a problem to be solved currently and urgently.
Disclosure of Invention
The invention provides a quantitative diagnosis method for nitrogen nutrition deficiency of regional corn plants, which can quantitatively judge the nutrition deficiency condition of the corn plants.
In order to achieve the above purpose, the present invention proposes the following technical scheme: a quantitative diagnosis method for nitrogen nutrient deficiency of regional corn plants, comprising the following steps:
s1: acquiring spectral data of a maize plant and calculatingMSRAn index;
s2: based onMSRExponential constructionNNIInverting the model;
s3: obtaining cornLAIData and calculate plant biomass of maizeBiomass；
S4: according toNNI、NNI target And plant biomassBiomassCalculating the nitrogen content to be absorbed of the corn plantsN abs 。
Further, the nitrogen content to be absorbed in S4N abs The calculation formula of (2) is as follows:
wherein,NNI target the corn nitrogen nutrition index is the target,NNIas the actual nitrogen nutrition index of the corn,N st standard nitrogen accumulation for maize plants.
Further, when the quantitative diagnosis of nitrogen nutrient deficiency of regional corn plants is carried out based on the optimal yield of corn,NNI target =1。
further, when the quantitative diagnosis of nitrogen nutrient deficiency of regional corn plants is carried out based on the optimal protein content of corn,NNI target = 0.8。
further, constructed in S2NNIThe inversion model is:
wherein,NNIdetermining coefficient R of inversion model 2 0.75.
Further, plant biomass in S3BiomassThe calculation formula of (2) is as follows:
Biomass=0.6852e 0.4979LAI
wherein,eis a natural constant, is an infinite non-cyclic fraction, and can be approximated here by a value of 2.71828.
Further, the method comprises the steps of,N st the calculation formula of (2) is as follows:
wherein,N c is the critical nitrogen concentration value of the corn plants,，arepresents the nitrogen concentration of plants when the biomass of the overground parts of the plants is 1 ton/hectare,bto control the statistical parameters of the slope of this curve.
Further, the method comprises the steps of,N c the values of (2) are specifically:
i.e.N st The values of (2) are specifically:
i.e.N abs The values of (2) are specifically:
。
further, in S3LAIThe data is obtained directly by terrestrial instrumentation or satellite data.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention can obtain quantitative parameters through experiments, combines the advantages of remote sensing data, and realizes large-area corn nutrition diagnosis.
2. The invention can realize the nutrition diagnosis of the whole growth period of the corn according to the corn biomass change and the corn optimal yield and the corn optimal protein content, and can realize the quantitative judgment and complete the work such as fertilization guidance.
Drawings
Fig. 1 is a remote sensing data inversion model diagram of NNI constructed in the first embodiment of the invention.
Detailed Description
Hereinafter, an embodiment of the present invention will be described with reference to fig. 1. In the following description, like modules are denoted by like reference numerals. In the case of the same reference numerals, their names and functions are also the same. Therefore, a detailed description thereof will not be repeated.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to fig. 1 and the specific embodiment. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not to be construed as limiting the invention.
Embodiment one:
a quantitative diagnosis method for nitrogen nutrient deficiency of regional corn plants, comprising the following steps:
s1: acquiring spectral data of a maize plant and calculatingMSRAn index.
Modified Simple Ratio (MSR), where NIR and R represent the near-red and red bands of telemetry data, respectively, calculated from the following formulas:
（NIR/R-1）/[sqrt（NIR/R）+1]。
s2: based onMSRExponential constructionNNIAnd (5) inverting the model.
NNIThe inversion model is specifically:
i.e.NNIMultiplied by a factor of 0.237MSRTo the power of 1.073, wherein,NNIinversion modelThe coefficient R of determination of (2) 2 0.75.
S3: obtaining cornLAIData and calculate plant biomass of maizeBiomass。LAIThe data is measured by a ground instrument or directly acquired by satellite data, and the data is acquiredLAIAfter the data, plant biomass was calculated by the following formulaBiomass：
Biomass=0.6852e 0.4979LAI
Wherein,eis a natural constant, a constant in mathematics, an infinite non-circulating decimal, which can be approximately 2.71828, plant biomassBiomassIn units of (A)t/hm 2 。
S4: according toNNI、NNI target And plant biomassBiomassCalculating the nitrogen content to be absorbed of the corn plantsN abs 。
Nitrogen content to be absorbedN abs The calculation formula of (2) is as follows:
wherein,NNI target the corn nitrogen nutrition index is the target,NNIas the actual nitrogen nutrition index of the corn,N st standard nitrogen accumulation for maize plants. When the quantitative diagnosis of the nitrogen nutrient deficiency of the regional corn plants is carried out based on the optimal yield of corn,NNI target = 1。
wherein,Nactthe actual nitrogen concentration of the biomass of the maize plants on the ground, nc is the critical nitrogen concentration value of the maize plants, and the unit iskg/tCan be converted from plant biomassBiomassThe NNI is obtained as the ratio of the two.
N st The calculation formula of (2) is as follows:
wherein,arepresents the nitrogen concentration of plants when the biomass of the overground parts of the plants is 1 ton/hectare,bto control the statistical parameters of the slope of this curve.
The embodiment is a related conclusion obtained by taking a nitrogen concentration dilution curve formula explored by spring corn in northeast as a precondition.N c The values of (2) are specifically:
i.e.N st The values of (2) are specifically:
i.e.N abs The values of (2) are specifically:
。
embodiment two:
the difference between this example and example one is that, when the quantitative diagnosis of nitrogen nutrient deficiency in regional maize plants is based on the optimal protein content of maize,NNI target =0.8。
it should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the technical solutions of the present disclosure are achieved, and are not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (9)
1. A quantitative diagnosis method for nitrogen nutrient deficiency of regional corn plants, which is characterized by comprising the following steps:
s1: acquiring spectral data of a maize plant and calculatingMSRAn index;
s2: based onMSRExponential constructionNNIInverting the model;
s3: obtaining cornLAIData and calculate plant biomass of maizeBiomass；
S4: according toNNI、NNI target And plant biomassBiomassCalculating the nitrogen content to be absorbed of the corn plantsN abs 。
2. The quantitative diagnostic method for nitrogen nutrient deficiency of regional maize plants according to claim 1, characterized in that the nitrogen content to be absorbed in S4N abs The calculation formula of (2) is as follows:
wherein,NNI target the corn nitrogen nutrition index is the target,NNIas the actual nitrogen nutrition index of the corn,N st standard nitrogen accumulation for maize plants.
3. The method for quantitative diagnosis of nitrogen deficiency in regional corn plants according to claim 2, wherein when quantitative diagnosis of nitrogen deficiency in regional corn plants is performed based on optimal yield of corn,NNI target =1。
4. the regional corn plant nitrogen nutrient deficiency of claim 2Is characterized in that when the quantitative diagnosis of nitrogen nutrient deficiency of regional corn plants is carried out based on the optimal protein content of corn,NNI target =0.8。
5. the quantitative diagnostic method for nitrogen nutrient deficiency of regional maize plants according to any of claims 1 to 4, characterized in that the method constructed in S2NNIThe inversion model is:
wherein,NNIdetermining coefficient R of inversion model 2 0.75.
6. The quantitative diagnostic method for nitrogen nutrient deficiency of regional maize plants of claim 5, wherein plant biomass in S3BiomassThe calculation formula of (2) is as follows:
Biomass=0.6852e 0.4979LAI
wherein,eis a natural constant, is an infinite non-cyclic fraction, and can be approximated here by a value of 2.71828.
7. The quantitative diagnosis method for nitrogen nutrient deficiency of regional corn plants according to claim 6, wherein,N st the calculation formula of (2) is as follows:
wherein,N c is the critical nitrogen concentration value of the corn plants,，arepresents the nitrogen concentration of plants when the biomass of the overground parts of the plants is 1 ton/hectare,bto control the statistical parameters of the slope of this curve.
8. The quantitative diagnostic method for nitrogen nutrient deficiency of regional corn plants according to claim 7, wherein,N c the values of (2) are specifically:
i.e.N st The values of (2) are specifically:
i.e.N abs The values of (2) are specifically:
。
9. the quantitative diagnostic method for nitrogen nutrient deficiency of regional maize plants of claim 8, wherein in S3LAIThe data is obtained directly by terrestrial instrumentation or satellite data.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117910280A (en) * | 2024-03-18 | 2024-04-19 | 吉林大学 | Method for quantitatively estimating potassium demand of regional corn plants in key growth period |
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