CN103575694A - Quick detection method for aflatoxin B1 of rice based on near infrared spectroscopy - Google Patents
Quick detection method for aflatoxin B1 of rice based on near infrared spectroscopy Download PDFInfo
- Publication number
- CN103575694A CN103575694A CN201310555346.3A CN201310555346A CN103575694A CN 103575694 A CN103575694 A CN 103575694A CN 201310555346 A CN201310555346 A CN 201310555346A CN 103575694 A CN103575694 A CN 103575694A
- Authority
- CN
- China
- Prior art keywords
- paddy
- sample
- infrared spectrum
- near infrared
- afb
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Abstract
The invention belongs to the field of food quality detection and in particular relates to a quick detection method for aflatoxin B1 of rice based on a near infrared spectroscopy. The quick detection method comprises collection of a rice sample material, spectral acquisition, measurement of aflatoxin B1 of the rice sample, spectral pretreatment, construction of a correction model, checking of the model and measurement of the aflatoxin B1 content of an unknown rice sample. The method disclosed by invention aims at basic research and discussion on quick and nondestructive detection of harmful substances of the rice and is used for detecting the aflatoxin B1 content of the rice based on the near infrared spectroscopy. The method has the advantages of simpleness, feasibility, high analysis speed, high detection precision, low analysis cost and the like and the advantages that the sample is not required to be pretreated and the environment cannot be polluted; a reliable basis can be supplied to control of the storage quality of the rice and the quality of a rice processed product.
Description
Technical field
The invention belongs to grain quality detection field, specifically, the present invention relates to a kind of paddy AFB based on near-infrared spectrum technique
1method for quick.
Background technology
Paddy rice is one of one of most important cereal crops ,Ye Shi China Three major grain crops in the world, and paddy industry has very important meaning for agricultural industrialization.Along with socioeconomic development, rice quality quality is more and more subject to people and pays close attention to.Paddy is after long storage, and due to the impact of reserve temperature, water grading factors, rice quality declines, and even can produce noxious material, such as the very large AFB of harm
1deng, consumer's health is brought to potential hazard, grain security is produced to material impact simultaneously.Paddy aflatoxin fast, Non-Destructive Testing is subject to the attention of the units such as scientific research institutions, quality testing department, state-owned large granary and grain processing enterprise day by day, as being this field worker's problem demanding prompt solution with fast, accurately detecting aflatoxin in paddy always.
In paddy, main dependence of aflatoxin detection manually completes in conjunction with chemically treated method for a long time, high, the consuming time length of this method testing cost, consume huge man power and material, simultaneously higher to testing staff's competency profiling, Technique Popularizing is restricted, and the consistance of detection efficiency and detection effect is all poor.
Except traditional chemical analysis method, some new technologies are used to aflatoxin in paddy and detect, such as liquid chromatography, euzymelinked immunosorbent assay (ELISA), immune affine method etc., although the method for these improvement can use manpower and material resources sparingly, but these methods are mostly because sense cycle is still longer, consume in a large number chemical reagent, and instrument price comparison is expensive, the more high reason of testing cost can not meet the requirement that grain quality is quick, harmless, low cost detects.Therefore, build a set of fast, harmless, efficiently, accurately detect aflatoxin in paddy, and do not have the technical system of high requirement to seem particularly important to testing staff.
Near-infrared spectrum technique has been a Fast Detection Technique with the fastest developing speed since the eighties in 20th century, in a lot of fields especially grain quality detection field, is widely applied.The advantage of near-infrared spectrum technique is just fast, can't harm, efficient, accurately.In recent years computer technology and Chemical Measurement develop into near-infrared spectrum technique is applied in Non-Destructive Testing paddy to aflatoxin provides may.Therefore, utilize near-infrared spectrum technique to set up that paddy aflatoxin is harmless, Fast Detection Technique system has most important theories meaning and practice significance.The present invention provides theoretical foundation for developing a set of near infrared Non-Destructive Testing paddy mycotoxin device, and expectation can be extended to this device in other cereal crops such as wheat, corn on this basis.
Summary of the invention
Object of the present invention is exactly for AFB in current paddy
1quantitatively detect the problem existing, overcome the defect that prior art exists, provide a kind of method based on near-infrared spectrum technique fast, harmless, efficiently, accurately detect AFB in paddy
1.
For achieving the above object, the technical solution used in the present invention is as follows: the collection of (1) sample material and the spectra collection of sample: collect the rice sample that aspergillus flavus is infected in various degree, for foundation and the correction of model, then apply near-infrared spectrometers and under same environmental conditions, gather paddy seed spectral information; (2) sample chemistry pH-value determination pH: the paddy seed that gathered near infrared spectrum is carried out to pulverization process and obtain paddy powder, adopt GB/T 5009.22-2003 national standard method to measure the AFB in paddy
1content; (3) calibration set and the pre-service of forecast set near infrared spectrum: calibration set paddy sample and forecast set paddy sample spectrum are carried out to pre-service, eliminate the interference of Aimless factors, improve accuracy of detection; (4) calibration model is set up: by multivariable analysis, with calibration set sample paddy AFB
1content is scaled values, and using forecast set sample paddy near infrared spectrum characteristic information data as independent variable, scaled values is as dependent variable, and application partial least square method builds paddy near infrared spectrum characteristic information and paddy AFB
1between chemometric model; (5) modelling verification: adopt the near infrared spectrum data of the forecast sample collection of pretreated paddy seed in step (3) to carry out performance evaluation to the model of step (4) structure; (6) unknown rice sample AFB
1the mensuration of content: the near infrared spectrum data that gathers paddy seed samples to be measured, use and with preprocess method identical in step (3), the near infrared spectrum data of paddy seed samples to be measured is carried out after pre-service, with the calibration model that step (4) is constructed, paddy seed samples to be measured is predicted.
Described step (1), the quantity of paddy sample is at least 60, and paddy sample is divided into calibration set sample and forecast set sample at random.
Described near-infrared spectrometers spectral scan scope is 10000cm
-1~4000cm
-1, resolution: 8cm
-1, scanning times: 64 times, replication three times, is averaged spectrum.
Described step (3), the pretreated method of spectrum comprises smoothly, second order differentiate, standardization, base-line shift, standard normal variable, polynary scatter correction, go trend method or the wherein combination of two or more methods.
The present invention is without any need for pre-treatment, and can realize fast, efficient, low-cost, pollution-free detection, reduce preferably the interference of external environment near infrared spectra collection simultaneously.
The preprocessing procedures that the present invention adopts can effectively extract the characteristic information of near infrared spectrum, reduces various Noise and Interferences, improves model prediction precision and stability.
Method provided by the invention can be a set of near infrared Non-Destructive Testing paddy mycotoxin device of development foundation is provided, and can on this basis this device be extended in other cereal crops such as wheat, corn.
Accompanying drawing explanation
Fig. 1 is the original near infrared light spectrogram of paddy seed;
Fig. 2 is the paddy seed near infrared light spectrogram of processing through second order differentiate;
Fig. 3 is sample predicted value and original value correlativity collection of illustrative plates.
Embodiment
Give an actual example below and describe the present invention by reference to the accompanying drawings.
(1) get the paddy sample of 30 natural infections and 50 water percentage be the paddy sample preserved at 25 ℃ of 16%-22% totally 80 samples as the Calibration of paddy seed and the Prediction of paddy seed, before scanning, naturally dry in the shade to paddy moisture stabilization at 10%-14%.Randomly drawing 2/3 sample is calibration set sample, and 1/3 is checking collection sample; At 25 ℃, open ANTARIS II type Fourier Transformation Near-Infrared Spectroscopy Analysis instrument preheating 30min, get 45g paddy seed and be put in sealing bag, before scanning, deaeration affects to reduce as far as possible; Adopt transmission integrating sphere type collection spectrum, spectral scan scope 10000cm
-1~4000cm
-1, scanning times 64 times, resolution 8cm
-1, sample multiple scanning 3 times, the absorption spectrum of collected specimens; Average as the near infrared spectrum data of Calibration and the near infrared spectrum data of Prediction (referring to accompanying drawing 1), for building AFB
1calibration model is prepared;
(2) the paddy seed that gathered near infrared spectrum is carried out to pulverization process and obtain paddy powder, adopt GB/T 5009.22-2003 national standard method to measure the AFB in paddy
1content;
(3) near infrared spectrum that adopts second order differentiate disposal route to obtain step (1) carries out pre-service (referring to accompanying drawing 2);
(4), according to the pretreated near infrared spectrum data of step (3), the partial least squares analysis method that adopts Unscrambler 10.3 softwares to provide, sets up AFB in the near infrared spectrum of Calibration of paddy seed and paddy
1calibration model between content;
(5) use through the pretreated forecast set sample of step (3) near infrared spectrum data, constructed calibration model is carried out to performance evaluation, in Table 1 and table 2;
(6), under identical environmental baseline, adopt method as herein described to unknown AFB
1the rice sample of content detects, use the preprocess method identical with step (3) to carry out pre-service to the spectroscopic data of rice sample to be measured, use the constructed calibration model of step (4) to predict rice sample to be measured, the model predication value of rice sample and the relation between reference value are shown in Fig. 3.
Table 1: AFB
1quantitative Analysis Model external certificate result
Sequence number | Measured value | Predicted value | Residual error |
1 | 19.91 | 10.08 | 9.83 |
2 | 2.81 | 1.26 | 1.55 |
3 | 22.97 | 23.45 | -0.48 |
4 | 9.3 | 9.61 | -0.31 |
5 | 26.88 | 20.21 | 6.67 |
6 | 10.35 | 12.09 | -1.74 |
7 | 21.3 | 18.56 | 2.74 |
8 | 15.95 | 16.09 | -0.14 |
9 | 2.54 | 1.12 | 1.42 |
10 | 2.19 | 2.16 | 0.03 |
11 | 0.28 | 0.95 | -0.67 |
12 | 10.09 | 12.32 | -2.23 |
13 | 8.62 | 11.90 | -3.28 |
14 | 8.21 | 10.56 | -2.35 |
15 | 3.25 | 5.01 | -1.76 |
16 | 7.05 | 6.28 | 0.77 |
17 | 5.5 | 7.78 | -2.28 |
18 | 0.77 | 0.93 | -0.16 |
19 | 1.44 | 1.56 | -0.12 |
20 | 13.29 | 14.89 | -1.6 |
Table 2: AFB
1quantitative Analysis Model external certificate precision
Related coefficient | Prediction standard deviation | Residual error standard value |
0.922 | 3.14 | 0.30 |
Claims (5)
1. the paddy AFB based on near-infrared spectrum technique
1method for quick, the concrete steps that it is characterized in that it are as follows: the collection of (1) sample material and the spectra collection of sample: collect the rice sample that aspergillus flavus is infected in various degree, for foundation and the correction of model, then apply near-infrared spectrometers and under same environmental conditions, gather paddy seed spectral information; (2) sample chemistry pH-value determination pH: the paddy seed that gathered near infrared spectrum is carried out to pulverization process and obtain paddy powder, adopt GB/T 5009.22-2003 national standard method to measure the AFB in paddy
1content; (3) calibration set and the pre-service of forecast set near infrared spectrum: calibration set paddy sample and forecast set paddy sample spectrum are carried out to pre-service, eliminate the interference of Aimless factors, improve accuracy of detection; (4) calibration model is set up: by multivariable analysis, with calibration set sample paddy AFB
1content is scaled values, and using forecast set sample paddy near infrared spectrum characteristic information data as independent variable, scaled values is as dependent variable, and application partial least square method builds paddy near infrared spectrum characteristic information and paddy AFB
1between chemometric model; (5) modelling verification: adopt the near infrared spectrum data of the forecast sample collection of pretreated paddy seed in step (3) to carry out performance evaluation to the model of step (4) structure; (6) unknown rice sample AFB
1the mensuration of content: the near infrared spectrum data that gathers paddy seed samples to be measured, use and with preprocess method identical in step (3), the near infrared spectrum data of paddy seed samples to be measured is carried out after pre-service, with the calibration model that step (4) is constructed, paddy seed samples to be measured is predicted.
2. the paddy AFB based on near-infrared spectrum technique according to claim 1
1method for quick, is characterized in that, the quantity of the described paddy sample of step (1) is at least 60, and paddy sample is divided into calibration set sample and forecast set sample at random.
3. the paddy aspergillus flavus based on near-infrared spectrum technique according to claim 1 is malicious
Element B
1method for quick, is characterized in that, described near-infrared spectrometers spectral scan scope is 10000cm
-1~4000cm
-1, resolution: 8cm
-1, scanning times: 64 times, replication three times, is averaged spectrum.
4. the paddy AFB based on near-infrared spectrum technique according to claim 1
1method for quick, is characterized in that, the pretreated method of the described spectrum of step (3) comprises smoothly, second order differentiate, standardization, base-line shift, standard normal variable, polynary scatter correction, go trend method or the wherein combination of two or more methods.
5. the paddy AFB based on near-infrared spectrum technique according to claim 1
1method for quick, is characterized in that, described detection method can be used for developing a set of near infrared Non-Destructive Testing paddy mycotoxin device, and can on this basis this device be extended in other cereal crops such as wheat, corn.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201310555346.3A CN103575694A (en) | 2013-11-11 | 2013-11-11 | Quick detection method for aflatoxin B1 of rice based on near infrared spectroscopy |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201310555346.3A CN103575694A (en) | 2013-11-11 | 2013-11-11 | Quick detection method for aflatoxin B1 of rice based on near infrared spectroscopy |
Publications (1)
Publication Number | Publication Date |
---|---|
CN103575694A true CN103575694A (en) | 2014-02-12 |
Family
ID=50047937
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201310555346.3A Pending CN103575694A (en) | 2013-11-11 | 2013-11-11 | Quick detection method for aflatoxin B1 of rice based on near infrared spectroscopy |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN103575694A (en) |
Cited By (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104048941A (en) * | 2014-06-25 | 2014-09-17 | 常熟雷允上制药有限公司 | Method for quickly measuring content of multiple index components in radix ophiopogonis through near infrared spectroscopy |
CN104048940A (en) * | 2014-06-05 | 2014-09-17 | 中国肉类食品综合研究中心 | Near-infrared quick determination method for content of cortisol in live pig blood |
CN104048939A (en) * | 2014-06-05 | 2014-09-17 | 中国肉类食品综合研究中心 | Near infrared rapid detection method for blood sugar content in live pig blood |
CN104089926A (en) * | 2014-07-18 | 2014-10-08 | 湖南省食品测试分析中心 | NIR (Near Infrared Ray) spectral analysis model and method for identifying excessive content of cadmium in rice |
CN104964969A (en) * | 2015-05-28 | 2015-10-07 | 广东省生态环境与土壤研究所 | Label-free visualization detection method and label-free visualization detection kit of aflatoxin B1 |
CN105158201A (en) * | 2015-07-27 | 2015-12-16 | 南京财经大学 | Rapid detection method for content of aflatoxin in brown rice based on FT-NIR technology |
CN105445217A (en) * | 2015-07-27 | 2016-03-30 | 南京财经大学 | Method for rapidly detecting content of aflatoxin in brown rice based on attenuated total reflection Fourier transform infrared spectrum technique |
CN105675534A (en) * | 2016-03-25 | 2016-06-15 | 北京市农林科学院 | Method for quickly and nondestructively identifying polished grains |
EP3211400A1 (en) * | 2016-02-24 | 2017-08-30 | TOMRA Sorting NV | A method and apparatus for the detection of the presence of mycotoxins in cereals |
CN104730027B (en) * | 2015-02-03 | 2017-09-15 | 中国农业大学 | The method that puccinia striiformis uredospores germination rate is determined using near-infrared spectrum technique |
CN108107019A (en) * | 2017-12-15 | 2018-06-01 | 暨南大学 | A kind of method that versicolorin content in corn is quickly detected based near infrared spectroscopy |
CN108548786A (en) * | 2018-03-08 | 2018-09-18 | 青岛农业大学 | A kind of apparatus and method using multiple surface rotating mirror spectral detection peanut aflatoxin |
CN112730269A (en) * | 2020-12-10 | 2021-04-30 | 青岛农业大学 | Aflatoxin intelligent detection method based on deep learning |
CN112798539A (en) * | 2020-12-10 | 2021-05-14 | 青岛农业大学 | Intelligent aflatoxin detection method based on transfer learning |
CN114002166A (en) * | 2021-10-29 | 2022-02-01 | 南京财经大学 | Hyperspectral imaging technology-based quantitative detection method for mildew of three aspergillus oryzae of rice |
CN114112988A (en) * | 2021-11-26 | 2022-03-01 | 江苏省农业科学院 | Cloud platform-based corn quality and fumonisin pollution field synchronous rapid analysis system and detection method |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1673746A (en) * | 2005-04-15 | 2005-09-28 | 中国农业科学院油料作物研究所 | Fast detecting method for aftatoxin B1 |
CN101936895A (en) * | 2010-09-02 | 2011-01-05 | 中南林业科技大学 | Near infrared spectroscopy analysis rapid detection method of rice freshness |
CN103163086A (en) * | 2013-04-01 | 2013-06-19 | 河南工业大学 | Terahertz spectrum detection method for aflatoxin |
CN203148850U (en) * | 2013-03-29 | 2013-08-21 | 合肥美亚光电技术股份有限公司 | Aflatoxin toxin detecting and sorting device |
CN103278631A (en) * | 2013-04-03 | 2013-09-04 | 中国农业科学院油料作物研究所 | Aflatoxin B1 flow lag immunization time distinguishing fluorescence rapid-detection kit and application thereof |
CN103323598A (en) * | 2012-11-21 | 2013-09-25 | 北京农学院 | Rapid detecting card for simultaneous detection of aflatoxin B1, ochratoxin A, vomitoxin and zearalenone in wheat and wheat products, and detection method thereof |
-
2013
- 2013-11-11 CN CN201310555346.3A patent/CN103575694A/en active Pending
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1673746A (en) * | 2005-04-15 | 2005-09-28 | 中国农业科学院油料作物研究所 | Fast detecting method for aftatoxin B1 |
CN101936895A (en) * | 2010-09-02 | 2011-01-05 | 中南林业科技大学 | Near infrared spectroscopy analysis rapid detection method of rice freshness |
CN103323598A (en) * | 2012-11-21 | 2013-09-25 | 北京农学院 | Rapid detecting card for simultaneous detection of aflatoxin B1, ochratoxin A, vomitoxin and zearalenone in wheat and wheat products, and detection method thereof |
CN203148850U (en) * | 2013-03-29 | 2013-08-21 | 合肥美亚光电技术股份有限公司 | Aflatoxin toxin detecting and sorting device |
CN103163086A (en) * | 2013-04-01 | 2013-06-19 | 河南工业大学 | Terahertz spectrum detection method for aflatoxin |
CN103278631A (en) * | 2013-04-03 | 2013-09-04 | 中国农业科学院油料作物研究所 | Aflatoxin B1 flow lag immunization time distinguishing fluorescence rapid-detection kit and application thereof |
Cited By (26)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104048940A (en) * | 2014-06-05 | 2014-09-17 | 中国肉类食品综合研究中心 | Near-infrared quick determination method for content of cortisol in live pig blood |
CN104048939A (en) * | 2014-06-05 | 2014-09-17 | 中国肉类食品综合研究中心 | Near infrared rapid detection method for blood sugar content in live pig blood |
CN104048941A (en) * | 2014-06-25 | 2014-09-17 | 常熟雷允上制药有限公司 | Method for quickly measuring content of multiple index components in radix ophiopogonis through near infrared spectroscopy |
CN104089926A (en) * | 2014-07-18 | 2014-10-08 | 湖南省食品测试分析中心 | NIR (Near Infrared Ray) spectral analysis model and method for identifying excessive content of cadmium in rice |
CN104089926B (en) * | 2014-07-18 | 2016-07-13 | 湖南省食品测试分析中心 | For differentiating NIR spectra analytical model and the discrimination method that Cd concentration of brown rice exceeds standard |
CN104730027B (en) * | 2015-02-03 | 2017-09-15 | 中国农业大学 | The method that puccinia striiformis uredospores germination rate is determined using near-infrared spectrum technique |
CN104964969A (en) * | 2015-05-28 | 2015-10-07 | 广东省生态环境与土壤研究所 | Label-free visualization detection method and label-free visualization detection kit of aflatoxin B1 |
CN105158201A (en) * | 2015-07-27 | 2015-12-16 | 南京财经大学 | Rapid detection method for content of aflatoxin in brown rice based on FT-NIR technology |
CN105445217A (en) * | 2015-07-27 | 2016-03-30 | 南京财经大学 | Method for rapidly detecting content of aflatoxin in brown rice based on attenuated total reflection Fourier transform infrared spectrum technique |
CN105445217B (en) * | 2015-07-27 | 2018-08-21 | 南京财经大学 | The rapid detection method of aflatoxin content in brown rice based on attenuated total reflection Fourier transform infrared spectrometry technology |
RU2721896C2 (en) * | 2016-02-24 | 2020-05-25 | Томра Сортинг Н.В. | Method and apparatus for detecting presence of mycotoxins in cereals |
AU2017222946B2 (en) * | 2016-02-24 | 2022-03-17 | Tomra Sorting N.V. | A method and apparatus for the detection of the presence of mycotoxins in cereals |
EP3211400A1 (en) * | 2016-02-24 | 2017-08-30 | TOMRA Sorting NV | A method and apparatus for the detection of the presence of mycotoxins in cereals |
WO2017144608A1 (en) * | 2016-02-24 | 2017-08-31 | Tomra Sorting N.V. | A method and apparatus for the detection of the presence of mycotoxins in cereals |
CN109073546A (en) * | 2016-02-24 | 2018-12-21 | 陶朗分拣股份有限公司 | For detecting the existing method and apparatus of mycotoxin in cereal |
JP2019510968A (en) * | 2016-02-24 | 2019-04-18 | トムラ ソーティング ナムローゼ フェンノートシャップ | Method and apparatus for the detection of the presence of mycotoxins in cereals |
US10429295B2 (en) | 2016-02-24 | 2019-10-01 | Tomra Sorting N.V. | Method and apparatus for the detection of the presence of mycotoxins in cereals |
CN109073546B (en) * | 2016-02-24 | 2022-08-02 | 陶朗分拣股份有限公司 | Method and apparatus for detecting the presence of mycotoxins in cereals |
CN105675534A (en) * | 2016-03-25 | 2016-06-15 | 北京市农林科学院 | Method for quickly and nondestructively identifying polished grains |
CN108107019A (en) * | 2017-12-15 | 2018-06-01 | 暨南大学 | A kind of method that versicolorin content in corn is quickly detected based near infrared spectroscopy |
CN108548786A (en) * | 2018-03-08 | 2018-09-18 | 青岛农业大学 | A kind of apparatus and method using multiple surface rotating mirror spectral detection peanut aflatoxin |
CN108548786B (en) * | 2018-03-08 | 2023-09-05 | 青岛农业大学 | Device and method for detecting peanut aflatoxin by using polygon mirror spectrum |
CN112798539A (en) * | 2020-12-10 | 2021-05-14 | 青岛农业大学 | Intelligent aflatoxin detection method based on transfer learning |
CN112730269A (en) * | 2020-12-10 | 2021-04-30 | 青岛农业大学 | Aflatoxin intelligent detection method based on deep learning |
CN114002166A (en) * | 2021-10-29 | 2022-02-01 | 南京财经大学 | Hyperspectral imaging technology-based quantitative detection method for mildew of three aspergillus oryzae of rice |
CN114112988A (en) * | 2021-11-26 | 2022-03-01 | 江苏省农业科学院 | Cloud platform-based corn quality and fumonisin pollution field synchronous rapid analysis system and detection method |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN103575694A (en) | Quick detection method for aflatoxin B1 of rice based on near infrared spectroscopy | |
CN104596957A (en) | Estimation method for content of copper in soil on basis of visible-light near-infrared spectrum technology | |
CN104849232B (en) | A kind of method of quick detection royal jelly moisture and protein content | |
CN102636450A (en) | Method for detecting wolfberry polyose content in Chinese wolfberry in a nondestructive way based on near infrared spectrum technology | |
CN104316491A (en) | Method for detecting urea doped in milk based on synchronous-asynchronous two-dimensional near-infrared correlation spectrum | |
CN101504363A (en) | Edible fatty acid value detection method based on near-infrared spectrum analysis | |
CN105445217A (en) | Method for rapidly detecting content of aflatoxin in brown rice based on attenuated total reflection Fourier transform infrared spectrum technique | |
CN102879353A (en) | Near infrared detection method for contents of protein components in peanut | |
CN101413883A (en) | Method for identifying tea-leaf origin by infrared spectrum | |
CN103969212B (en) | The method utilizing Terahertz frequency range FTIR technology detection by quantitative Pesticide Residues In Grain | |
CN103487395A (en) | Quick multi-index detection method for Paris polyphylla medicinal materials | |
CN103645155A (en) | Quick nondestructive testing method for tenderness of fresh mutton | |
CN103175805A (en) | Method for determining indexes of COD and BOD5 in sewage through near infrared spectrometry | |
CN104596979A (en) | Method for measuring cellulose of reconstituted tobacco by virtue of near infrared reflectance spectroscopy technique | |
CN105784672A (en) | Drug detector standardization method based on dual-tree complex wavelet algorithm | |
CN105486663B (en) | A method of detecting the stable carbon isotope ratio of soil using near infrared spectrum | |
CN103411895B (en) | Pseudo-near infrared spectrum identification method mixed by pearl powder | |
CN105158201A (en) | Rapid detection method for content of aflatoxin in brown rice based on FT-NIR technology | |
CN104596975A (en) | Method for measuring lignin of reconstituted tobacco by paper-making process by virtue of near infrared reflectance spectroscopy technique | |
CN103712948A (en) | Rapid nondestructive test method for content of volatile basic nitrogen in raw and fresh mutton | |
CN106126879B (en) | A kind of soil near-infrared spectrum analysis prediction technique based on rarefaction representation technology | |
CN110376154A (en) | Fruit online test method and system based on spectrum correction | |
CN102928356A (en) | Method for measuring essence solvent content rapidly | |
Zhou et al. | Applications of near infrared spectroscopy in cotton impurity and fiber quality detection: A review | |
CN204008454U (en) | Portable near infrared spectrometer for detection of mould index in storage paddy |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
C02 | Deemed withdrawal of patent application after publication (patent law 2001) | ||
WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20140212 |