CN117740721A - Method for detecting non-protein nitrogen content in feed raw material - Google Patents
Method for detecting non-protein nitrogen content in feed raw material Download PDFInfo
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- CN117740721A CN117740721A CN202311256194.7A CN202311256194A CN117740721A CN 117740721 A CN117740721 A CN 117740721A CN 202311256194 A CN202311256194 A CN 202311256194A CN 117740721 A CN117740721 A CN 117740721A
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- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 title claims abstract description 192
- 102000004169 proteins and genes Human genes 0.000 title claims abstract description 101
- 108090000623 proteins and genes Proteins 0.000 title claims abstract description 101
- 229910052757 nitrogen Inorganic materials 0.000 title claims abstract description 96
- 238000000034 method Methods 0.000 title claims abstract description 62
- 239000002994 raw material Substances 0.000 title claims abstract description 50
- 235000019750 Crude protein Nutrition 0.000 claims abstract description 42
- 239000000126 substance Substances 0.000 claims abstract description 15
- 239000000463 material Substances 0.000 claims description 28
- 235000019764 Soybean Meal Nutrition 0.000 claims description 14
- 239000004455 soybean meal Substances 0.000 claims description 14
- 235000019733 Fish meal Nutrition 0.000 claims description 12
- 239000004467 fishmeal Substances 0.000 claims description 12
- NLXLAEXVIDQMFP-UHFFFAOYSA-N Ammonia chloride Chemical compound [NH4+].[Cl-] NLXLAEXVIDQMFP-UHFFFAOYSA-N 0.000 claims description 6
- 241000084490 Esenbeckia delta Species 0.000 claims description 4
- FGIUAXJPYTZDNR-UHFFFAOYSA-N potassium nitrate Chemical compound [K+].[O-][N+]([O-])=O FGIUAXJPYTZDNR-UHFFFAOYSA-N 0.000 claims description 4
- 235000019270 ammonium chloride Nutrition 0.000 claims description 3
- 239000005696 Diammonium phosphate Substances 0.000 claims description 2
- 229920000877 Melamine resin Polymers 0.000 claims description 2
- 229920001807 Urea-formaldehyde Polymers 0.000 claims description 2
- 150000003863 ammonium salts Chemical class 0.000 claims description 2
- -1 bioprotein Polymers 0.000 claims description 2
- MNNHAPBLZZVQHP-UHFFFAOYSA-N diammonium hydrogen phosphate Chemical compound [NH4+].[NH4+].OP([O-])([O-])=O MNNHAPBLZZVQHP-UHFFFAOYSA-N 0.000 claims description 2
- 229910000388 diammonium phosphate Inorganic materials 0.000 claims description 2
- 235000019838 diammonium phosphate Nutrition 0.000 claims description 2
- JDSHMPZPIAZGSV-UHFFFAOYSA-N melamine Chemical compound NC1=NC(N)=NC(N)=N1 JDSHMPZPIAZGSV-UHFFFAOYSA-N 0.000 claims description 2
- 229920000642 polymer Polymers 0.000 claims description 2
- ODGAOXROABLFNM-UHFFFAOYSA-N polynoxylin Chemical compound O=C.NC(N)=O ODGAOXROABLFNM-UHFFFAOYSA-N 0.000 claims description 2
- 239000004323 potassium nitrate Substances 0.000 claims description 2
- 235000010333 potassium nitrate Nutrition 0.000 claims description 2
- 241000894007 species Species 0.000 claims description 2
- 238000004519 manufacturing process Methods 0.000 abstract description 5
- 238000005259 measurement Methods 0.000 abstract description 5
- 238000001514 detection method Methods 0.000 description 6
- 238000004458 analytical method Methods 0.000 description 5
- 238000001228 spectrum Methods 0.000 description 4
- 229920002430 Fibre-reinforced plastic Polymers 0.000 description 2
- FFEARJCKVFRZRR-BYPYZUCNSA-N L-methionine Chemical compound CSCC[C@H](N)C(O)=O FFEARJCKVFRZRR-BYPYZUCNSA-N 0.000 description 2
- KDXKERNSBIXSRK-UHFFFAOYSA-N Lysine Natural products NCCCCC(N)C(O)=O KDXKERNSBIXSRK-UHFFFAOYSA-N 0.000 description 2
- 239000004472 Lysine Substances 0.000 description 2
- XSQUKJJJFZCRTK-UHFFFAOYSA-N Urea Chemical compound NC(N)=O XSQUKJJJFZCRTK-UHFFFAOYSA-N 0.000 description 2
- 239000008186 active pharmaceutical agent Substances 0.000 description 2
- 239000004202 carbamide Substances 0.000 description 2
- 239000002131 composite material Substances 0.000 description 2
- 235000019784 crude fat Nutrition 0.000 description 2
- 239000000835 fiber Substances 0.000 description 2
- 239000011151 fibre-reinforced plastic Substances 0.000 description 2
- 238000002329 infrared spectrum Methods 0.000 description 2
- 229930182817 methionine Natural products 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000001320 near-infrared absorption spectroscopy Methods 0.000 description 2
- 239000000523 sample Substances 0.000 description 2
- QJZYHAIUNVAGQP-UHFFFAOYSA-N 3-nitrobicyclo[2.2.1]hept-5-ene-2,3-dicarboxylic acid Chemical compound C1C2C=CC1C(C(=O)O)C2(C(O)=O)[N+]([O-])=O QJZYHAIUNVAGQP-UHFFFAOYSA-N 0.000 description 1
- 238000007696 Kjeldahl method Methods 0.000 description 1
- 229910019142 PO4 Inorganic materials 0.000 description 1
- DZHMRSPXDUUJER-UHFFFAOYSA-N [amino(hydroxy)methylidene]azanium;dihydrogen phosphate Chemical compound NC(N)=O.OP(O)(O)=O DZHMRSPXDUUJER-UHFFFAOYSA-N 0.000 description 1
- 238000000862 absorption spectrum Methods 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- OHJMTUPIZMNBFR-UHFFFAOYSA-N biuret Chemical compound NC(=O)NC(N)=O OHJMTUPIZMNBFR-UHFFFAOYSA-N 0.000 description 1
- 210000001124 body fluid Anatomy 0.000 description 1
- 239000010839 body fluid Substances 0.000 description 1
- 230000000052 comparative effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 239000004021 humic acid Substances 0.000 description 1
- 238000010348 incorporation Methods 0.000 description 1
- YWXYYJSYQOXTPL-SLPGGIOYSA-N isosorbide mononitrate Chemical compound [O-][N+](=O)O[C@@H]1CO[C@@H]2[C@@H](O)CO[C@@H]21 YWXYYJSYQOXTPL-SLPGGIOYSA-N 0.000 description 1
- 244000144972 livestock Species 0.000 description 1
- 235000012054 meals Nutrition 0.000 description 1
- 238000000386 microscopy Methods 0.000 description 1
- 125000000449 nitro group Chemical group [O-][N+](*)=O 0.000 description 1
- QJGQUHMNIGDVPM-UHFFFAOYSA-N nitrogen group Chemical group [N] QJGQUHMNIGDVPM-UHFFFAOYSA-N 0.000 description 1
- JDLQRNRWXLXOMN-UHFFFAOYSA-N octadecanoic acid;urea Chemical compound NC(N)=O.CCCCCCCCCCCCCCCCCC(O)=O JDLQRNRWXLXOMN-UHFFFAOYSA-N 0.000 description 1
- NBIIXXVUZAFLBC-UHFFFAOYSA-K phosphate Chemical compound [O-]P([O-])([O-])=O NBIIXXVUZAFLBC-UHFFFAOYSA-K 0.000 description 1
- 239000010452 phosphate Substances 0.000 description 1
- 235000013613 poultry product Nutrition 0.000 description 1
- 238000000513 principal component analysis Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 239000013074 reference sample Substances 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
- 239000007858 starting material Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/80—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in fisheries management
- Y02A40/81—Aquaculture, e.g. of fish
- Y02A40/818—Alternative feeds for fish, e.g. in aquacultures
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- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The invention relates to a method for detecting the content of non-protein nitrogen in feed raw materials, which comprises the steps of firstly calibrating a scanning method of a near infrared scanner, and then scanning the predicted content of crude protein in the feed raw materials to be detected by the calibrated method, wherein the predicted content is marked as a 1 Detecting the actual content of crude protein in the feed raw material to be detected by a wet chemical method, and marking as b 1 ，a 1 And b 1 The absolute value of the difference is the content delta of non-protein nitrogen 1 . Compared with the prior art, the invention creates a novel method for measuring the non-protein nitrogen content in the feed raw material, the protein content detected by the traditional method and the protein content increment predicted by the near infrared spectrometer reflect the non-protein nitrogen content doped in the feed raw material, and the method has reliable result, simple and convenient operation, strong operability, less interference and no special effect on operatorsThe method has the advantages that the problems that the traditional method cannot directly measure and the measurement content is inaccurate are solved, the method can effectively ensure the protein content of the feed and improve the quality of the product when applied to actual production.
Description
Technical Field
The invention relates to the technical field of analysis of chemical components of livestock and poultry products, in particular to a method for detecting the content of non-protein nitrogen in feed raw materials.
Background
Non-protein nitrogen refers to the total amount of nitrogen in the body fluid from which the protein remains in the various nitrogen-containing compounds. Including feed urea, urea nitro humic acid condensate, isobutylenediurea, ammonium chloride, urea phosphate, biuret, monoamine phosphate, urea stearate, etc. The detection of non-protein nitrogen is the detection of nitrogen content derived from the outside of the protein. Non-protein nitrogen has an important role in raw material adulteration, covering almost all protein raw materials. The benefit of the feed production enterprises is affected, and the feed quality is seriously affected. At present, the industry mainly uses a microscope to detect or uses a method of measuring real protein in T/NAIA 060-2021 feed by Kjeldahl method to measure real protein to reflect the content of non-protein nitrogen, the detection is complicated, and with the increase of the variety of non-protein nitrogen, the process is changed, part of non-protein nitrogen cannot be reflected by the method of measuring real protein, in addition, the microscope detection has higher experience requirements on operators, and the universality is not high.
Therefore, a method for detecting the content of non-protein nitrogen is needed, which is not limited by the variety, experience and the like of the non-protein nitrogen.
Disclosure of Invention
The invention aims to provide a method for detecting the non-protein nitrogen content in feed raw materials, which aims to solve the defect of detecting the non-protein nitrogen content in feed in the prior art.
And scanning the feed raw material by adopting a near infrared detector to obtain a model crude protein predicted value, and simultaneously measuring the crude protein content by adopting a traditional method, wherein the difference between the model crude protein and the crude protein is the non-protein nitrogen content, so that the quantification of the non-protein nitrogen in the feed raw material is achieved.
The aim of the invention can be achieved by the following technical scheme:
the technical scheme of the invention is to provide a method for detecting the non-protein nitrogen content in a feed raw material, which comprises the steps of firstly calibrating a scanning method of a near infrared scanner, and then scanning the predicted content of crude protein in the feed raw material to be detected by the calibrated method, wherein the predicted content is marked as a 1 Detecting the actual content of crude protein in the feed raw material to be detected by a wet chemical method, and marking as b 1 ，a 1 And b 1 The absolute value of the difference is the content delta of non-protein nitrogen 1 I.e. delta 1 ＝|b 1 -a 1 |。
In some embodiments, the scanning calibration method of the near infrared scanner specifically comprises the following steps: detecting a predicted content a of crude protein in a plurality of undoped non-protein nitrogen feed raw materials by using a near infrared scanner 2 And detecting the actual content b of crude protein in the feed material without doped non-protein nitrogen by wet chemical method 2 Comparison, a 2 And b 2 The absolute value of the difference is the content delta of non-protein nitrogen 2 Meets the content delta of non-protein nitrogen 2 ＝|b 2 -a 2 |＝0。
Further, the crude protein content in the feed feedstock without doped non-protein nitrogen is 45% -72%.
Still more preferably, the feed material that is not doped with non-protein nitrogen is fish meal with a crude protein content of 45% -72% and fermented soybean meal with a crude protein content of 45% -54%.
Further, the near infrared scanner scans a wavelength range of 850 to 2500nm.
In some embodiments, the method is also specific to delta 1 Error judgment is carried out, specifically: the same method is used for detecting the predicted content a of crude protein in a plurality of feed raw materials doped with quantitative non-protein nitrogen through a near infrared scanner 3 And detecting the actual content b of crude protein in the feed raw material doped with quantitative non-protein nitrogen by wet chemical method 3 ，a 3 And b 3 The absolute value of the difference is the content delta of non-protein nitrogen 3 I.e. delta 3 ＝|b 3 -a 3 I, compare delta 3 The absolute value of the difference value between the feed material doped with quantitative non-protein nitrogen and the theoretical value of the non-protein nitrogen is the error value epsilon, and the error value epsilon is reasonable within 3 percent of the feed material.
More specifically, when the crude protein content in the feed raw material is more than 25%, the error value epsilon is reasonable within 1% of the mass of the feed raw material;
when the content of crude protein in the feed raw material is 10% -25%, the error value epsilon is reasonable within 2% of the mass of the feed raw material;
when the crude protein content in the feed raw material is less than 10%, the error value epsilon is reasonable within 3% of the mass of the feed raw material.
Still further, feed materials that are doped with a quantitative amount of non-protein nitrogen include feed materials that are doped with a non-protein nitrogen content of 0.5% -1%.
Still further preferred feed materials that are doped with a quantitative amount of non-protein nitrogen are feed materials that are doped with a non-protein nitrogen content of 0.5% and feed materials that are doped with a non-protein nitrogen content of 1%.
Still further, the non-protein nitrogen species doped in the feed stock doped with the quantitative non-protein nitrogen include ammonium salts, urea-formaldehyde polymers, potassium nitrate, ammonium chloride, diammonium phosphate, bioprotein, melamine.
In some embodiments, the feed material to be tested comprises fish meal and fermented soybean meal.
The near infrared spectrum method (NIR) utilizes the general frequency vibration or rotation of organic matters containing C-H, N-H, O-H, C-C and other chemical bonds to obtain an absorption spectrum in a near infrared region in a diffuse reflection mode, and establishes a linear or nonlinear model between the substance spectrum and the content of the component to be measured by means of modern chemometry and metering means such as principal component analysis, partial least square method, artificial neural network and the like, thereby realizing the rapid measurement of the content of the component to be measured by using the information of the substance near infrared spectrum. A linear or nonlinear model between the content of crude protein of the feed raw material without added non-protein nitrogen and the corresponding spectrum is established by the nitrogen content and spectrum provided by the protein. When detecting feeds or feed materials containing non-protein nitrogen, the model cannot predict the content of the non-protein nitrogen, so that the predicted protein content is different from the protein content detected by the traditional method, and the difference between the predicted protein content and the protein content is the content of the non-protein nitrogen.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides a novel method for measuring the non-protein nitrogen content in a feed raw material, which is characterized in that the protein content detected by the traditional method and the protein content value added value predicted by a near infrared spectrometer reflect the non-protein nitrogen content doped in the feed raw material, the result is reliable, the operation is simple and convenient, the operability is strong, the interference is less, no special requirements are imposed on operators, the application is wide, the problems that the traditional method cannot directly measure and the measurement content is inaccurate are solved, the situation that whether the raw material is counterfeited is judged, the protein content of the feed can be effectively ensured in actual production, and the product quality is improved.
Detailed Description
The present invention will be described in detail with reference to specific examples. The present embodiment is implemented on the premise of the technical scheme of the present invention, and a detailed implementation manner and a specific operation process are given, but the protection scope of the present invention is not limited to the following examples.
In the following examples and comparative examples, unless otherwise specified, the starting materials or processing techniques are all those which are conventional commercially available in the art.
Near infrared feed analyzer (denmark fos DS 2500F), calibration software: winISI.
Analytical balance: the sensing amount is 0.0001g.
Example 1:
the method for detecting the content of non-protein nitrogen in the fish meal feed raw material and the fermented soybean meal feed raw material comprises the following steps:
1. establishing a calibration model for near infrared scanning:
about 50 feed raw materials which are not doped with non-protein nitrogen and need to be judged are collected, and a fish meal model and a fermented soybean meal model are respectively built according to the type of the raw materials in order to accurately judge the non-protein nitrogen content.
The model building samples are fish meal feed raw materials and fermented soybean meal feed raw materials which are free of adulteration and doped with non-protein nitrogen, and are fish meal with the crude protein content of 45% -72% and fermented soybean meal with the crude protein content of 45% -54%.
The microscopic examination and chemical drop experiment method can be adopted to ensure that the sample has no adulteration and doping phenomenon.
(1) Spectral acquisition using a near infrared feed analyzer (danish foss DS 2500F), wavelength range: model creation using scaling software 850-2500 nm: winISI. The prediction value a of the crude protein is established by calibration according to the near infrared spectrometry for rapidly determining moisture, crude protein, crude fiber, crude fat, lysine and methionine in GB/T18868-2002 feed 2 And (5) a model.
(2) Crude protein tradition test value b of the sample used for calibration 2 The feed is obtained by measurement by adopting a method of measurement of crude protein in GB/T6432-2018 feed.
(3) Ensure the difference delta 2 ＝|b 2 -a 2 The predictive value a can be used at this time, |=0 2 The parameters of the model are used for measuring the predicted value of the crude protein in the feed raw material to be measured and the predicted value of the crude protein in the feed raw material doped with quantitative non-protein nitrogen.
2. Determination of whether the difference is valid and whether the difference is authentic:
respectively preparing fermented soybean meal and fermented soybean meal doped with 0.5% and 1% of different non-protein nitrogenFish meal, obtaining predicted value a scanned by near infrared ray instrument 3 And adopts the method of GB/T6432-2018 determination of crude protein in feed to determine the traditional detection value b 3 Calculating protein increment delta 3 ＝|b 3 -a 3 | a. The invention relates to a method for producing a fibre-reinforced plastic composite. And comparing the obtained value-added data with the corresponding theoretical nitrogen content value-added data of the non-protein nitrogen doped substances to verify the feasibility and reliability of the method, wherein, table 1 is the difference error analysis in the fermented soybean meal doped with quantitative non-protein nitrogen, table 2 is the difference error analysis in the fish meal doped with quantitative non-protein nitrogen, table 3 is the allowable error between the predicted value and the wet chemical method measured value of the crude protein and the corresponding theoretical crude protein content value-added table of the common non-protein nitrogen and the doping proportion of the common non-protein nitrogen, which are specified in GB/T18868-2002 feed, and table 3 is the rapid determination near infrared spectrometry of water, crude protein, crude fiber, crude fat, lysine and methionine.
TABLE 1 error analysis in quantitative non-protein nitrogen doped fermented soybean meal
TABLE 2 error analysis in fish meal doped with quantitative non-protein nitrogen
TABLE 3 allowable error Range for whether the difference is valid
TABLE 4 common non-protein Nitrogen and the corresponding theoretical crude protein content increment for the incorporation ratio
As can be seen from Table 3, the difference value delta calculated in tables 1 and 2 3 Is not in the error range and is an effective value. Difference delta 3 The error range from the theoretical increment is within 1 percent, which can be understood as the difference delta obtained by the invention 3 Is reliable and has high accuracy.
3. Detecting the non-protein nitrogen content in fish meal and fermented soybean meal to be detected:
collecting spectra of fish meal feed raw materials and fermented soybean meal feed raw materials which are collected and tested in the market by a near infrared feed analyzer to obtain crude protein predicted content a 1 And adopts the method of GB/T6432-2018 determination of crude protein in feed to determine the traditional detection value b 1 Calculating protein increment delta 1 ＝|b 1 -a 1 | a. The invention relates to a method for producing a fibre-reinforced plastic composite. And judging whether the error is out of the error allowable range or not according to the table 3, wherein the result is shown in the table 5.
TABLE 5 determination of non-protein nitrogen content in samples to be tested
The microscopic examination judges that the non-protein nitrogen content% is determined by an operator according to the content proportion of suspicious substances found by the control of the prepared reference sample, and the method for microscopic examination of the feed raw materials is referred to GB/T14698-2017. As can be seen from Table 5, the non-protein nitrogen content detected by the present invention is relatively similar to the non-protein nitrogen content obtained by microscopy, indicating that the accuracy of the data obtained by the present invention is high.
The previous description of the embodiments is provided to facilitate a person of ordinary skill in the art in order to make and use the present invention. It will be apparent to those skilled in the art that various modifications can be readily made to these embodiments and the generic principles described herein may be applied to other embodiments without the use of the inventive faculty. Therefore, the present invention is not limited to the above-described embodiments, and those skilled in the art, based on the present disclosure, should make improvements and modifications without departing from the scope of the present invention.
Claims (10)
1. A method for detecting the content of non-protein nitrogen in feed raw material is characterized by that the scanning method of near-infrared scanner is calibrated, and the predicted content of coarse protein in feed raw material to be detected is scanned by said calibrated method, and is marked as a 1 Detecting the actual content of crude protein in the feed raw material to be detected by a wet chemical method, and marking as b 1 ，a 1 And b 1 The absolute value of the difference is the content delta of non-protein nitrogen 1 I.e. delta 1 ＝|b 1 -a 1 |。
2. The method for detecting the nitrogen content of non-protein in a feed raw material according to claim 1, wherein the scanning method calibration of the near infrared scanner is specifically as follows: detecting a predicted content a of crude protein in a plurality of undoped non-protein nitrogen feed raw materials by using a near infrared scanner 2 And detecting the actual content b of crude protein in the feed material without doped non-protein nitrogen by wet chemical method 2 Comparison, a 2 And b 2 The absolute value of the difference is the content delta of non-protein nitrogen 2 Meets the content delta of non-protein nitrogen 2 ＝|b 2 -a 2 |＝0。
3. The method for detecting the content of non-protein nitrogen in a feed material according to claim 2, wherein the crude protein content in the feed material without doped with non-protein nitrogen is 45% -72%.
4. A method for detecting the non-protein nitrogen content in a feed material according to claim 3, wherein the feed material without doped non-protein nitrogen is fish meal with a crude protein content of 45% -72% and fermented soybean meal with a crude protein content of 45% -54%.
5. The method for detecting the nitrogen content of non-protein in a feed raw material according to claim 2, wherein the wavelength range scanned by the near infrared scanner is 850-2500 nm.
6. The method for detecting the nitrogen content of a non-protein in a feed material according to claim 1, wherein the method further comprises the step of measuring delta 1 Error judgment is carried out, specifically: the same method is used for detecting the predicted content a of crude protein in a plurality of feed raw materials doped with quantitative non-protein nitrogen through a near infrared scanner 3 And detecting the actual content b of crude protein in the feed raw material doped with quantitative non-protein nitrogen by wet chemical method 3 ，a 3 And b 3 The absolute value of the difference is the content delta of non-protein nitrogen 3 I.e. delta 3 ＝|b 3 -a 3 I, compare delta 3 The absolute value of the difference value between the feed material doped with quantitative non-protein nitrogen and the theoretical value of the non-protein nitrogen is the error value epsilon, and the error value epsilon is reasonable within the range of not exceeding 3% of the feed material.
7. The method for detecting the non-protein nitrogen content in a feed material according to claim 6, wherein the feed material doped with quantitative non-protein nitrogen comprises a feed material doped with 0.5% -1% non-protein nitrogen content.
8. The method for detecting the non-protein nitrogen content in a feed material according to claim 7, wherein the feed material doped with quantitative non-protein nitrogen is a feed material doped with 0.5% non-protein nitrogen content and a feed material doped with 1% non-protein nitrogen content.
9. The method for detecting the content of non-protein nitrogen in a feed material according to claim 6, wherein the non-protein nitrogen species doped in the feed material doped with quantitative non-protein nitrogen comprises ammonium salt, urea-formaldehyde polymer, potassium nitrate, ammonium chloride, diammonium phosphate, bioprotein, melamine.
10. The method for detecting the non-protein nitrogen content in the feed raw material according to claim 1, wherein the feed raw material to be detected comprises fish meal and fermented soybean meal.
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