CN102879340A - Method for quickly detecting nutritional quality of root/stem crops on basis of near-infrared spectrum - Google Patents
Method for quickly detecting nutritional quality of root/stem crops on basis of near-infrared spectrum Download PDFInfo
- Publication number
- CN102879340A CN102879340A CN2012103655294A CN201210365529A CN102879340A CN 102879340 A CN102879340 A CN 102879340A CN 2012103655294 A CN2012103655294 A CN 2012103655294A CN 201210365529 A CN201210365529 A CN 201210365529A CN 102879340 A CN102879340 A CN 102879340A
- Authority
- CN
- China
- Prior art keywords
- infrared spectrum
- model
- sample
- nutritional quality
- root
- 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
Landscapes
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The invention discloses a method for quickly detecting nutritional quality of root/stem crops on the basis of near-infrared spectrum, and belongs to the field of nutritional quality detection. The method includes steps of 1), screening a representative test sample bank with high gradient of component content and according with modeling; 2), acquiring near-infrared spectrum data of test samples by a near-infrared spectrometer; 3), precisely analyzing component content of nutritional quality of the test samples in the test sample bank by referring to international or national standard methods; 4), processing the near-infrared spectrum data; 5), selecting a chemical metering process for building a mathematical model and establishing a model by a program QUANT-2 in OPUS quantitative analysis software; 6), evaluating the model by means of correction and internal cross validation; and 7), collecting the near-infrared spectrum data of to-be-tested samples, preprocessing the spectrum data, and then predicting the nutritional quality of the samples by the aid of the established model. The method has the advantages of high analysis speed, no pollution, no sample preprocessing, high detection precision, good repeatability, and capability of analyzing various nutritional quality components of underground root/stem crops simultaneously.
Description
Technical field
The present invention relates to a kind of method based on underground root of near-infrared spectrum technique fast detecting/stem class crop alimentary quality, the detection technique field of piece root under the possession/stem class crop alimentary quality component.Can quick, pollution-free detection sweet potato, nutritional quality component in the underground root/stem class crop such as cassava, potato, Chinese yam, taro.
Background technology
Sweet potato, cassava, potato, Chinese yam, taro etc. are as typical underground root/stem kind of starch crop, all are China and even important grain, feed and the raw material of industry in the world.In every year, underground root of this class of China/stem kind of starch crop has a large amount of sample estovers matter identifications at breeding, cultivation, resource screening and the aspects such as preservation and processing and utilization.Laboratory conventional chemical detecting instrument is analyzed lixiviate or a plurality of steps such as reaction, detection that nutritional labeling needs chemical reagent, the shortcoming such as that the preparation of sample, pre-service and analytic process exist is consuming time, effort, determination step are loaded down with trivial details, different indexs however with passage test, easily cause environmental error and personal error, impact analysis result's reliability and comparability, consume a large amount of chemical reagent, the pollutants such as the waste liquid of generation, waste gas do not meet the low-carbon (LC) social desirability of present promotion yet.At present, in China, underground root of this class/stem kind of starch crop field does not still have fast, the analytical approach of low consumption, no-pollution nutrient quality.
Summary of the invention
Quick in order to realize, efficient, pollution-free, the content of underground root of many index determinings/stem class crop alimentary quality component simultaneously the invention provides a kind of method based on underground root of near-infrared spectrum technique fast detecting/stem class crop alimentary quality.Utilize this method not need underground root/stem class is carried out complicated Chemical Pretreatment as matter sample, realize the quick pollution-free detection to underground root of this class/stem class crop Multiple components, and save detection time, reduce cost, increase efficient, protection of the environment.The present invention adopts following technical scheme to realize: a kind of method based near infrared spectrum fast detecting piece root/stem class crop alimentary quality, use near-infrared spectral analysis technology underground root/stem class crop alimentary quality component concentration is carried out analyzing and testing, concrete steps are as follows:
1) selection of sample: each crop screening meets large, the representational test specimen of the component concentration gradient storehouse of modeling;
2) collection of spectrum: state per sample, use near infrared spectrometer acquisition test sample near infrared spectrum data;
3) analysis of test specimen chemical score: with reference to nutritional quality component concentration in international or the national standard method Accurate Analysis test specimen storehouse;
4) pre-service of spectrum: the near infrared spectrum data that collects is carried out pre-service;
5) optimization of calibration model: select to set up the stoechiometric process of mathematical model, the QUANT-2 program is carried out model construction in the employing OPUS quantitative analysis software;
6) checking of model: have fine representativeness for guaranteeing the modeling sample collection, institute's established model is adopted proofread and correct and the cross-validation evaluation;
7) application of model: the acquisition condition that adopts during with acquisition standard correction sample spectrum is consistent, gathers underground root to be measured/stem class and makes the near infrared spectrum data of matter sample, predict its nutritional quality with constructed calibration model after the spectroscopic data pre-service.
The selection of the described sample of step 1) is large, the representational Calibration of component concentration gradient and the testing sample collection that meets modeling from the screening of National Resources storehouse.
The optimization of the described calibration model of step 5): comprise the stoechiometric process of selecting to set up mathematical model, the chemical measurement value of Calibration is input among the modeling program QUANT-2 with corresponding spectral value, recycling OPTIMIZE program Automatic Optimal is processed, select the best modeled condition, comprise optimal spectrum preprocess method, best Spectral range and best major component dimension etc.; Set up the calibration model of near infrared spectrum and underground root/stem class crop nutrient composition content.
The nutritional quality component comprises the nutritional quality component concentrations such as starch, protein, soluble sugar, reducing sugar, glucose, fructose, sucrose and part mineral matter element of underground root/stem class crop in the step 3).
Above-mentioned NIR technology has the incomparable characteristics of conventional method such as amount of samples is few, sample nondestructive loses, analysis speed is fast, many index determinings of while, no waste is polluted and cost is low, utilization factor is high, also meets " low-carbon (LC) scientific research " requirement that present country proposes simultaneously.Can be advantageously applied to underground root/stem class crop quality index analysis, it predicts the outcome all in conventional method permissible error scope, and the result that checking detects can reach the requirement of practical application fully.Therefore, can be used as a kind of fast method is applied in underground root/stem class crop research and production.
The invention has the beneficial effects as follows, analysis speed of the present invention is fast, pollution-free, need not sample pretreatment, accuracy of detection is high, good reproducibility, can analyze simultaneously the multiple nutrients quality component in underground root/stem class crop, for the screening of underground root/stem class crop breeding and resource provides convenient, fast, efficient analytical approach.
Description of drawings
Fig. 1 is process flow diagram of the present invention.
Embodiment
Process flow diagram route is as shown in Figure 1 tested.
The screening of sample: screening meets large, the representational Calibration of component concentration gradient and the testing sample collection of modeling from resources bank in all parts of the country.This enforcement is that each crop is screened 120 parts of materials with essential informations such as separate sources, different yellowish pink, different dry rate and different biological characteristics as Calibration and 50 parts of sample sets to be predicted from resources bank in all parts of the country;
The pre-service of sample: select healthy and strong, well-balanced material, clean, allowance for bark, cut into slices, put-50 ℃ of frozen drying 72h, grind, cross 60 orders, sealing is preserved, and is for subsequent use;
The mensuration of sample chemical value: with reference to the nutritional quality component concentrations such as starch, protein, soluble sugar, reducing sugar, glucose, fructose, sucrose and part mineral matter element in international or such underground root of the national standard method Accurate Analysis/stem class crop sample sets;
The collection of spectrum: VECTOR22/N type Fourier transform near-infrared reflection spectrometer (German BRUKER spectral instrument company system) is adopted in test, and sample is contained in the rotary sample container of diameter 50mm, and the about 5mm of thickness is at 4000-10000cm
-1Spectral range interscan 64 times, resolution are 4cm
-1To instrument preheating 30min, after instrument test (such as peak and expansion signal etc.) passes through, background is scanned before measuring; Sample is scanned, and each sample repeats 3 times;
The pre-service of spectrum: with order in the software kit near infrared spectrum data is carried out pre-service (level and smooth, differential, averaged spectrum, baseline correction etc.), disturb to eliminate background and context, improve spectral quality and signal to noise ratio (S/N ratio), be stored in the computing machine;
The optimization of calibration model: chemical measurement value and the corresponding spectral value of Calibration are input among the modeling program QUANT-2, adopt the Multielement statistical analysis methods such as least square method (MPLS), partial least square method (PLS) and principal component regression (PCR), utilize OPTIMIZE program Automatic Optimal to process, select the best modeled condition, comprise optimal spectrum preprocess method, best Spectral range and best major component dimension etc.; Set up the near infrared spectrum of sweet potato and the calibration model of underground root/stem class crop nutrient composition content; For guaranteeing measurement environment and manually-operated consistance, carry out a background scans to eliminate drift every 30 samples in the measuring process.
The checking of model and application: have fine representativeness for guaranteeing the modeling sample collection, adopt correction and cross-validation to estimate the coefficient of determination (R relevant with chemical score such as predicted value to institute's established model
2) and mean square deviation (RMSEE and RMECV); The acquisition condition that adopts during with acquisition standard correction sample spectrum is consistent, gathering 50 parts of underground root/stems to be measured) class makes the near infrared spectrum data of matter sample, with constructed calibration model, underground root of fast prediction/stem class is made the result of the index of quality such as starch in the matter sample, protein, soluble sugar, reducing sugar, glucose, fructose, sucrose and part trace element after the spectroscopic data pre-service.
Claims (4)
1. the method based near infrared spectrum fast detecting piece root/stem class crop alimentary quality is characterized in that using near-infrared spectral analysis technology underground root/stem class crop alimentary quality component concentration is carried out analyzing and testing, and concrete steps are as follows:
1) selection of sample: each crop screening meets large, the representational test specimen of the component concentration gradient storehouse of modeling;
2) collection of spectrum: state per sample, adopt appropriate method to use near infrared spectrometer acquisition test sample near infrared spectrum data;
3) analysis of test specimen chemical score: with reference to nutritional quality component concentration in international or the national standard method Accurate Analysis test specimen storehouse;
4) pre-service of spectrum: the near infrared spectrum data that collects is carried out pre-service;
5) optimization of calibration model: select to set up the stoechiometric process of mathematical model, the QUANT-2 program is carried out model construction in the employing OPUS quantitative analysis software;
6) checking of model: have fine representativeness for guaranteeing the modeling sample collection, institute's established model is adopted proofread and correct and the cross-validation evaluation;
7) application of model: the acquisition condition that adopts during with acquisition standard correction sample spectrum is consistent, gathers underground root to be measured/stem class and makes the near infrared spectrum data of matter sample, predict its nutritional quality with constructed calibration model after the spectroscopic data pre-service.
2. the method based near infrared spectrum fast detecting piece root/stem class crop alimentary quality according to claim 1, the selection that it is characterized in that the described sample of step 1) is that each crop is screened large, the representational Calibration of the component concentration gradient that meets modeling and testing sample collection from the National Resources storehouse.
3. the method based near infrared spectrum fast detecting piece root/stem class crop alimentary quality according to claim 1, the optimization that it is characterized in that the described calibration model of step 5): comprise the stoechiometric process of selecting to set up mathematical model, the chemical measurement value of Calibration is input among the modeling program QUANT-2 with corresponding spectral value, recycling OPTIMIZE program Automatic Optimal is processed, select the best modeled condition, comprise optimal spectrum preprocess method, best Spectral range and best major component dimension etc.; Set up underground root/near infrared spectrum of stem class crop and the calibration model of its nutrient composition content.
4. the method based near infrared spectrum fast detecting piece root/stem class crop alimentary quality according to claim 1 is characterized in that nutritional quality component in the step 3) comprises the nutritional quality component concentrations such as starch, protein, soluble sugar, reducing sugar, glucose, fructose, sucrose and part mineral matter element of underground root/stem class crop.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2012103655294A CN102879340A (en) | 2012-09-27 | 2012-09-27 | Method for quickly detecting nutritional quality of root/stem crops on basis of near-infrared spectrum |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2012103655294A CN102879340A (en) | 2012-09-27 | 2012-09-27 | Method for quickly detecting nutritional quality of root/stem crops on basis of near-infrared spectrum |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN102879340A true CN102879340A (en) | 2013-01-16 |
Family
ID=47480748
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2012103655294A Pending CN102879340A (en) | 2012-09-27 | 2012-09-27 | Method for quickly detecting nutritional quality of root/stem crops on basis of near-infrared spectrum |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102879340A (en) |
Cited By (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103278460A (en) * | 2013-05-30 | 2013-09-04 | 华南农业大学 | Test and analysis method of red spider insect pest coercion conditions of orange trees |
| CN103389370A (en) * | 2013-06-09 | 2013-11-13 | 新疆农业科学院园艺作物研究所 | Establishment and application of mineral element nutrient diagnosis system for leaves of Xinjiang almond |
| CN103487384A (en) * | 2013-10-15 | 2014-01-01 | 无锡艾科瑞思产品设计与研究有限公司 | Near-infrared-spectrum-based method for rapidly detecting components of bagged rice |
| CN103575689A (en) * | 2013-10-11 | 2014-02-12 | 西北农林科技大学 | Method for rapidly detecting amylose content in rice by near infrared spectrum and visible light analyzer |
| CN103712924A (en) * | 2013-12-26 | 2014-04-09 | 河南中医学院 | Quality control method for preparing semen euphorbiae pulveratum decoction piece |
| CN104237138A (en) * | 2013-06-21 | 2014-12-24 | 中国农业机械化科学研究院 | Near infrared determination method for potato reducing sugar |
| CN104897607A (en) * | 2015-06-18 | 2015-09-09 | 北京工商大学 | Food modeling and rapid detecting integration method and system adopting portable NIRS (near infrared spectroscopy) |
| CN105486650A (en) * | 2015-12-31 | 2016-04-13 | 深圳市芭田生态工程股份有限公司 | Method for measuring main nutritional components of potatoes through spectrometry |
| CN105512430A (en) * | 2015-12-31 | 2016-04-20 | 深圳市芭田生态工程股份有限公司 | Shared input and output system of spectroscopic data and chemical detection data |
| CN105527236A (en) * | 2015-12-31 | 2016-04-27 | 深圳市芭田生态工程股份有限公司 | Method for determination of main nutritional components of agricultural product by use of spectroscopy method |
| CN105628647A (en) * | 2015-12-31 | 2016-06-01 | 深圳市芭田生态工程股份有限公司 | Method for measuring soluble sugar in agricultural product by utilization of spectroscopic method |
| CN105699302A (en) * | 2015-12-31 | 2016-06-22 | 深圳市芭田生态工程股份有限公司 | Method for determining main nutritional ingredients of apples by means of spectral method |
| CN106770019A (en) * | 2017-03-01 | 2017-05-31 | 四川农业大学 | A kind of assay method of Itanlian rye soluble sugar content |
| CN107314986A (en) * | 2017-06-12 | 2017-11-03 | 华中农业大学 | A kind of method that utilization near infrared spectrum detects rape stem soluble sugar content |
| CN109374548A (en) * | 2018-11-14 | 2019-02-22 | 深圳职业技术学院 | A method of quickly measuring nutritional ingredient in rice using near-infrared |
| CN110596038A (en) * | 2019-09-27 | 2019-12-20 | 南京晶薯生物科技有限公司 | Method for rapidly determining starch content of sweet potatoes |
| CN110702806A (en) * | 2019-09-09 | 2020-01-17 | 米津锐 | Reverse engineering dynamic analysis method |
| CN111781161A (en) * | 2020-07-09 | 2020-10-16 | 青岛农业大学 | Method for establishing near-infrared reflection spectrum model for determining nutritional quality of corn stalks |
| CN114428061A (en) * | 2021-12-16 | 2022-05-03 | 皖西学院 | Method for predicting total polysaccharide content in fiddlehead based on ultraviolet-visible-near infrared spectrum |
| CN116297318A (en) * | 2023-03-24 | 2023-06-23 | 广东省农业科学院作物研究所 | Method for measuring total phenols in sweet potato stem tip based on near infrared spectroscopy |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6114699A (en) * | 1997-11-26 | 2000-09-05 | The United States Of America As Represented By The Secretary Of Agriculture | Prediction of total dietary fiber in cereal products using near-infrared reflectance spectroscopy |
| CN101701911A (en) * | 2009-11-30 | 2010-05-05 | 吉林燃料乙醇有限责任公司 | Method for detecting content of reducing sugar in fermentation materials |
| CN101231274B (en) * | 2008-01-28 | 2011-06-01 | 河南中医学院 | Method for rapid measuring allantoin content in yam using near infrared spectrum |
| CN202216900U (en) * | 2011-07-25 | 2012-05-09 | 中机美诺科技股份有限公司 | Potato internal quality detection device based on near infrared spectrum scanning |
| CN102539566A (en) * | 2011-12-28 | 2012-07-04 | 河南中医学院 | Method for fast detecting content of dioscin in dioscorea zingiberensis by utilizing near infrared spectrum technology |
-
2012
- 2012-09-27 CN CN2012103655294A patent/CN102879340A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6114699A (en) * | 1997-11-26 | 2000-09-05 | The United States Of America As Represented By The Secretary Of Agriculture | Prediction of total dietary fiber in cereal products using near-infrared reflectance spectroscopy |
| CN101231274B (en) * | 2008-01-28 | 2011-06-01 | 河南中医学院 | Method for rapid measuring allantoin content in yam using near infrared spectrum |
| CN101701911A (en) * | 2009-11-30 | 2010-05-05 | 吉林燃料乙醇有限责任公司 | Method for detecting content of reducing sugar in fermentation materials |
| CN202216900U (en) * | 2011-07-25 | 2012-05-09 | 中机美诺科技股份有限公司 | Potato internal quality detection device based on near infrared spectrum scanning |
| CN102539566A (en) * | 2011-12-28 | 2012-07-04 | 河南中医学院 | Method for fast detecting content of dioscin in dioscorea zingiberensis by utilizing near infrared spectrum technology |
Non-Patent Citations (5)
| Title |
|---|
| 唐忠厚 等: "基于近红外光谱的甘薯抗性淀粉含量的快速测定方法", 《江苏农业学报》 * |
| 唐忠厚 等: "甘薯蛋白质含量近红外反射光谱分析模型应用研究", 《中国食品学报》 * |
| 李炎 等: "近红外反射光谱（NIRS）分析技术及其在农业上的应用", 《黑龙江农业科学》 * |
| 梁高峰 等: "近红外光谱分析技术及其在农业研究中的应用", 《安徽农业科学》 * |
| 陆国权 等: "主要根茎类作物淀粉特性研究", 《中国食品学报》 * |
Cited By (25)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103278460A (en) * | 2013-05-30 | 2013-09-04 | 华南农业大学 | Test and analysis method of red spider insect pest coercion conditions of orange trees |
| CN103278460B (en) * | 2013-05-30 | 2015-07-29 | 华南农业大学 | A kind of mandarin tree red spider herbivore stress situation method for testing and analyzing |
| CN103389370A (en) * | 2013-06-09 | 2013-11-13 | 新疆农业科学院园艺作物研究所 | Establishment and application of mineral element nutrient diagnosis system for leaves of Xinjiang almond |
| CN104237138A (en) * | 2013-06-21 | 2014-12-24 | 中国农业机械化科学研究院 | Near infrared determination method for potato reducing sugar |
| CN103575689A (en) * | 2013-10-11 | 2014-02-12 | 西北农林科技大学 | Method for rapidly detecting amylose content in rice by near infrared spectrum and visible light analyzer |
| CN103575689B (en) * | 2013-10-11 | 2015-07-15 | 西北农林科技大学 | Method for rapidly detecting amylose content in rice by near infrared spectrum and visible light analyzer |
| CN103487384A (en) * | 2013-10-15 | 2014-01-01 | 无锡艾科瑞思产品设计与研究有限公司 | Near-infrared-spectrum-based method for rapidly detecting components of bagged rice |
| CN103487384B (en) * | 2013-10-15 | 2016-01-27 | 无锡艾科瑞思产品设计与研究有限公司 | Based on the packed paddy composition method for quick of near infrared spectrum |
| CN103712924A (en) * | 2013-12-26 | 2014-04-09 | 河南中医学院 | Quality control method for preparing semen euphorbiae pulveratum decoction piece |
| CN103712924B (en) * | 2013-12-26 | 2016-08-17 | 河南中医学院 | Prepare the quality determining method of Semen Euphorbiae Pulveratum decoction pieces |
| CN104897607A (en) * | 2015-06-18 | 2015-09-09 | 北京工商大学 | Food modeling and rapid detecting integration method and system adopting portable NIRS (near infrared spectroscopy) |
| CN104897607B (en) * | 2015-06-18 | 2017-08-25 | 北京工商大学 | Portable near infrared spectrum food modeling and quick detection integral method and system |
| CN105527236A (en) * | 2015-12-31 | 2016-04-27 | 深圳市芭田生态工程股份有限公司 | Method for determination of main nutritional components of agricultural product by use of spectroscopy method |
| CN105628647A (en) * | 2015-12-31 | 2016-06-01 | 深圳市芭田生态工程股份有限公司 | Method for measuring soluble sugar in agricultural product by utilization of spectroscopic method |
| CN105699302A (en) * | 2015-12-31 | 2016-06-22 | 深圳市芭田生态工程股份有限公司 | Method for determining main nutritional ingredients of apples by means of spectral method |
| CN105512430A (en) * | 2015-12-31 | 2016-04-20 | 深圳市芭田生态工程股份有限公司 | Shared input and output system of spectroscopic data and chemical detection data |
| CN105486650A (en) * | 2015-12-31 | 2016-04-13 | 深圳市芭田生态工程股份有限公司 | Method for measuring main nutritional components of potatoes through spectrometry |
| CN106770019A (en) * | 2017-03-01 | 2017-05-31 | 四川农业大学 | A kind of assay method of Itanlian rye soluble sugar content |
| CN107314986A (en) * | 2017-06-12 | 2017-11-03 | 华中农业大学 | A kind of method that utilization near infrared spectrum detects rape stem soluble sugar content |
| CN109374548A (en) * | 2018-11-14 | 2019-02-22 | 深圳职业技术学院 | A method of quickly measuring nutritional ingredient in rice using near-infrared |
| CN110702806A (en) * | 2019-09-09 | 2020-01-17 | 米津锐 | Reverse engineering dynamic analysis method |
| CN110596038A (en) * | 2019-09-27 | 2019-12-20 | 南京晶薯生物科技有限公司 | Method for rapidly determining starch content of sweet potatoes |
| CN111781161A (en) * | 2020-07-09 | 2020-10-16 | 青岛农业大学 | Method for establishing near-infrared reflection spectrum model for determining nutritional quality of corn stalks |
| CN114428061A (en) * | 2021-12-16 | 2022-05-03 | 皖西学院 | Method for predicting total polysaccharide content in fiddlehead based on ultraviolet-visible-near infrared spectrum |
| CN116297318A (en) * | 2023-03-24 | 2023-06-23 | 广东省农业科学院作物研究所 | Method for measuring total phenols in sweet potato stem tip based on near infrared spectroscopy |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102879340A (en) | Method for quickly detecting nutritional quality of root/stem crops on basis of near-infrared spectrum | |
| CN101413885A (en) | Near-infrared spectrum method for rapidly quantifying honey quality | |
| Triolo et al. | Near Infrared Reflectance Spectroscopy (NIRS) for rapid determination of biochemical methane potential of plant biomass | |
| CN104316489B (en) | A kind of adulterated method of near infrared spectrum detection Ganoderma extract | |
| CN103543123A (en) | Infrared spectrum recognition method for adulterated milk | |
| CN101221125A (en) | Method for measuring eutrophication water body characteristic parameter by spectrum technology | |
| CN102590129B (en) | Method for detecting content of amino acid in peanuts by near infrared method | |
| CN105486662A (en) | Cottonseed gossypol content non-destructive measurement method based on near-infrared spectrum technology | |
| CN102346136A (en) | Method for measuring content of substance in process of anaerobic fermentation | |
| CN101762569A (en) | Non-destructive monitoring method of livestock excrement industrialized composting fermentation process | |
| CN102680426A (en) | Method for rapidly determining starch gelatinization degree of steam-tabletting corn | |
| CN106018335A (en) | Method for nondestructively determining content of phytic acid in whole cottonseed based on near infrared spectroscopy | |
| CN109211829A (en) | A method of moisture content in the near infrared spectroscopy measurement rice based on SiPLS | |
| CN102252972A (en) | Near infrared spectrum based detection method for rapid discrimination of oil-tea camellia seed oil real property | |
| CN107703097A (en) | Utilize the method and its application of decay total reflection probe and the model of near infrared spectrometer structure fast prediction oil property | |
| CN102937575B (en) | Watermelon sugar degree rapid modeling method based on secondary spectrum recombination | |
| CN103487398B (en) | A kind of analytical method of lysine fermentation liquor | |
| CN101349638A (en) | Spectrum rapid nondestructive testing method for vitamin C content of fruits and vegetables | |
| CN104266998A (en) | Near-infrared spectrum detection method for isocyanate group content in spandex prepolymer | |
| CN101788459B (en) | Quasi-continuous spectroscopic wavelength combination method | |
| CN101769867A (en) | Nondestructive testing method for quality of compost products | |
| CN104502307A (en) | Method for quickly detecting content of glycogen and protein of crassostrea gigas | |
| CN103308507A (en) | Analysis method for rapidly measuring free isocyanate (NCO) in polyurethane | |
| CN111521577B (en) | Infrared spectrum quantitative analysis method taking carbon dioxide peak area as reference | |
| CN105223102A (en) | A kind of method utilizing Near Infrared Spectroscopy for Rapid slurrying material basic density |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into 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: 20130116 |