KR20130136670A - Method for measuring ph, water content and lactic acid content of italian ryegrass silage using near infrared spectroscopy - Google Patents
Method for measuring ph, water content and lactic acid content of italian ryegrass silage using near infrared spectroscopy Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 59
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 55
- JVTAAEKCZFNVCJ-UHFFFAOYSA-N lactic acid Chemical compound CC(O)C(O)=O JVTAAEKCZFNVCJ-UHFFFAOYSA-N 0.000 title claims abstract description 48
- 235000014655 lactic acid Nutrition 0.000 title claims abstract description 24
- 239000004310 lactic acid Substances 0.000 title claims abstract description 24
- 239000004460 silage Substances 0.000 title claims description 40
- 238000004497 NIR spectroscopy Methods 0.000 title abstract description 18
- 240000004296 Lolium perenne Species 0.000 title abstract description 5
- 238000001228 spectrum Methods 0.000 claims abstract description 15
- 238000002329 infrared spectrum Methods 0.000 claims description 42
- 238000000611 regression analysis Methods 0.000 claims description 12
- 238000005259 measurement Methods 0.000 claims description 11
- 230000005540 biological transmission Effects 0.000 claims description 3
- JVTAAEKCZFNVCJ-UHFFFAOYSA-M Lactate Chemical compound CC(O)C([O-])=O JVTAAEKCZFNVCJ-UHFFFAOYSA-M 0.000 claims description 2
- 230000001939 inductive effect Effects 0.000 claims description 2
- 238000000691 measurement method Methods 0.000 claims 1
- 238000004458 analytical method Methods 0.000 abstract description 31
- 238000007781 pre-processing Methods 0.000 abstract description 2
- 239000004461 grass silage Substances 0.000 abstract 2
- 239000000523 sample Substances 0.000 description 21
- 230000001066 destructive effect Effects 0.000 description 9
- 238000010200 validation analysis Methods 0.000 description 8
- 238000002790 cross-validation Methods 0.000 description 3
- 238000001035 drying Methods 0.000 description 3
- 238000000227 grinding Methods 0.000 description 3
- 230000005855 radiation Effects 0.000 description 3
- 239000000126 substance Substances 0.000 description 3
- 239000012491 analyte Substances 0.000 description 2
- 238000011088 calibration curve Methods 0.000 description 2
- 238000012512 characterization method Methods 0.000 description 2
- 238000011002 quantification Methods 0.000 description 2
- 238000011084 recovery Methods 0.000 description 2
- 240000007594 Oryza sativa Species 0.000 description 1
- 235000007164 Oryza sativa Nutrition 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- 239000000538 analytical sample Substances 0.000 description 1
- 235000021329 brown rice Nutrition 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 239000003153 chemical reaction reagent Substances 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 239000004459 forage Substances 0.000 description 1
- 125000000524 functional group Chemical group 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 230000031700 light absorption Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000004476 mid-IR spectroscopy Methods 0.000 description 1
- 238000002156 mixing Methods 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000002203 pretreatment Methods 0.000 description 1
- 238000010298 pulverizing process Methods 0.000 description 1
- 238000001303 quality assessment method Methods 0.000 description 1
- 239000010453 quartz Substances 0.000 description 1
- 235000009566 rice Nutrition 0.000 description 1
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N silicon dioxide Inorganic materials O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 description 1
- 239000002904 solvent Substances 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/28—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q
- G01N1/286—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q involving mechanical work, e.g. chopping, disintegrating, compacting, homogenising
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/02—Food
- G01N33/025—Fruits or vegetables
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
- G01N2021/3572—Preparation of samples, e.g. salt matrices
Abstract
Description
본 발명은 근적외선 분광기를 이용하여 이탈리안 라이그라스 사일리지의 pH, 수분함량 및 젖산함량을 분석하는 방법에 관한 것으로, 시료의 전처리 없이 비파괴분석이 가능하여 빠르고 용이하게 측정할 수 있는 이점이 있다.The present invention relates to a method for analyzing the pH, water content, and lactic acid content of Italian lygras silage using a near infrared spectrometer, and has the advantage of being able to quickly and easily measure nondestructive analysis without pretreatment of a sample.
일반적으로 근적외선은 가시광 영역의 장파장 영역에서 중적외선(Mid-IR) 영역의 단파장까지를 의미한다. 근적외선 분광분석법은 근적외선 영역에서의 빛 흡수에 입각한 분석법으로 어떤 분자결합에 근적외선이 조사되면 그 분자 결합이 가지고 있는 고유한 진동에너지에 해당하는 복사선이 흡수된다. 결국 근적외선이 가지고 있는 고유한 진동에너지에 해당하는 복사선이 흡수된다. 따라서, 근적외선은 2500 nm 이상의 중적외선 영역에서 흡수되는 O-H, C-H, N-H, C=O, N-H 등과 같은 각 관능기가 갖는 기본 진동의 1, 2, 3차 배음(overtone)과 결합음(combination)에 해당하는 진동음이 나타나는 영역이다.In general, near-infrared means from the long wavelength region of the visible light region to the short wavelength of the mid-IR region. Near-infrared spectroscopy is based on light absorption in the near-infrared region. When near-infrared radiation is irradiated on a molecular bond, radiation corresponding to the unique vibration energy of the molecular bond is absorbed. As a result, radiation corresponding to the intrinsic vibration energy of near infrared rays is absorbed. Therefore, near infrared rays are combined with the primary, secondary, and tertiary overtones and combinations of fundamental vibrations of each functional group such as OH, CH, NH, C═O, NH, etc. absorbed in the mid-infrared region of 2500 nm or more. This is the area where the corresponding vibration sound appears.
근적외선 분광분석법(NIR)의 최대 특징은 시료의 전처리가 필요 없거나, 최소한의 시료 전처리(예; 분쇄)만으로도 분석이 가능하며, 더 나아가 분쇄하지 않은 비파괴 상태로도 분석이 가능하다. 또한, 근적외선 분광분석법(NIR)은 수분이 흡수되지 않은 석영 재질을 이용한 시료장치를 쓸 수 있는 장점도 있다.Near-infrared spectroscopy (NIR) is characterized by no sample pretreatment, minimal sample pretreatment (eg grinding), and even non-destructive analysis. In addition, near-infrared spectroscopy (NIR) has the advantage of using a sample device using a quartz material that is not absorbed moisture.
통상적으로, 시료의 성분 및 특성 분석은 크게 구분하여 분석 대상물의 형태나 특성을 변화시켜 분석하는 파괴적인 방법과 형태나 특성을 변화시키지 않고 분석하는 비파괴적 방법으로 구분할 수 있다. 파괴적 방법에 의한 성분 및 특성 분석은 습식분석 혹은 화학분석으로 표현되며, 시료의 분쇄, 평량, 함수율 측정, 용액이나 용매를 이용한 화학반응, 성분검출, 정량 등 수차례의 단계적 과정이 요구된다. 또한, 짧게는 몇 분에서 길게는 며칠 동안의 복잡한 작업과정이 요구되고, 경우에 따라서는 고가의 분석장비와 많은 노동력이 요구되며, 최근에는 분석 폐기물에 의한 환경오염이 대두되고 있다. 그러나, 비파괴적 성분 및 특성 분석은 기기의 측정 센서를 분석 대상물의 표면에 접촉시키거나 비접촉시켜 측정하는 방법으로 기존 화학분석 혹은 파괴적 방법을 대신할 수 있는 안전한 분석 기술이다. 경우에 따라 파괴적 방법 및 화학 분석에 비해 정확도나 정밀도가 감소되는 경우도 있지만, 분석에 소요되는 시간, 경비 및 노력을 절감하고, 분석시료의 재사용 및 유지를 위해 다양한 방법의 비파괴적 분석 기술들이 개발되고 있다.In general, the component and characteristic analysis of a sample can be classified into two types: a destructive method of changing the shape or characteristics of the analyte and analyzing the non-destructive method without changing the shape or characteristics. Component and characterization by destructive methods is expressed by wet analysis or chemical analysis, and requires several stepwise processes such as crushing sample, measuring basis weight, measuring moisture content, chemical reaction using solution or solvent, component detection and quantification. In addition, it requires a complicated work process for a few minutes to a few days, expensive analysis equipment and a lot of labor in some cases, and environmental pollution caused by analytical waste has recently emerged. However, non-destructive component and characterization is a safe analysis technique that can replace the existing chemical analysis or destructive method by measuring the measuring sensor of the device in contact or non-contact with the surface of the analyte. In some cases, accuracy and precision may be reduced compared to destructive methods and chemical analysis, but a variety of non-destructive analysis techniques have been developed to reduce the time, cost, and effort required for analysis, and to reuse and maintain analytical samples. It is becoming.
한국공개특허 제2006-0019961호에는 근적외선 분광법을 이용한 현미 내 찹쌀함량의 측정방법이 개시되어 있으나, 본 발명의 근적외선 분광기를 이용한 이탈리안 라이그라스 사일리지의 pH, 수분함량 및 젖산함량 측정 방법과는 상이하다.Korean Laid-Open Patent Publication No. 2006-0019961 discloses a method for measuring glutinous rice content in brown rice using near infrared spectroscopy, but differs from the method for measuring pH, water content and lactic acid content of Italian lygras silage using the near infrared spectrometer of the present invention. .
본 발명은 상기와 같은 요구에 의해 도출된 것으로서, 기존에는 생시료를 1~2일 동안 건조 후 분쇄하여 NIR 스펙트럼을 수집함으로 인해 많은 시간이 소요되는 단점이 있었는데, 본 발명에서는 이러한 단점을 해결하고자 건조 및 분쇄 과정을 생략하고 단지 2~3 cm 입자도로 절단하여 시료를 전처리하였다. 따라서, 본 발명은 근적외선 분광기를 이용하여 비파괴적으로 신속 용이하게 이탈리안 라이그라스 사일리지의 pH, 수분함량 및 젖산함량을 측정하는 방법을 제공하는 데 있다.The present invention was derived by the above requirements, conventionally had a disadvantage that takes a lot of time due to collecting the NIR spectrum by drying and grinding the raw sample for 1-2 days, in the present invention to solve this disadvantage Samples were pretreated by omitting the drying and grinding process and cutting to just 2-3 cm particles. Accordingly, the present invention is to provide a method for measuring the pH, water content and lactic acid content of Italian Ligras silage quickly and nondestructively using a near infrared spectroscopy.
상기 과제를 해결하기 위해, 본 발명은 근적외선 분광기를 이용하여 이탈리안 라이그라스 사일리지의 pH, 수분함량 및 젖산함량을 분석하는 방법을 제공한다.In order to solve the above problems, the present invention provides a method for analyzing the pH, water content and lactic acid content of Italian lygras silage using a near infrared spectroscopy.
본 발명은 근적외선 분광기를 사용하여 이탈리안 라이그라스 사일리지의 pH, 수분함량 및 젖산함량을 건조 또는 분쇄하는 전처리 없이 생시료 자체로 비파괴분석이 가능하여, 빠르고 용이하게 측정할 수 있는 이점이 있다. 또한, 신속한 조사료 품질평가로 국내산 조사료의 투명한 유통체계를 확립하고, 유통활성화를 촉진시킬 수 있다.The present invention has the advantage that non-destructive analysis is possible with the raw sample itself without pretreatment of drying or pulverizing the pH, water content and lactic acid content of Italian lygras silage using a near infrared spectrometer, it is advantageous in that it can be measured quickly and easily. In addition, rapid survey quality assessment can establish a transparent distribution system of domestic forages and promote distribution.
도 1은 이탈리안 라이그라스 사일리지의 근적외선 스펙트럼 측정을 위한 시료 전처리 방법을 나타낸 것이다.
도 2는 이탈리안 라이그라스 사일리지의 근적외선 스펙트럼을 나타낸 그래프와 이탈리안 라이그라스 사일리지의 근적외선 스펙트럼을 미분 처리한 후의 그래프를 나타낸 것이다.
도 3은 근적외선 분광기를 이용하여 얻어진 수분 함량을 기준값(reference value)과 비교한 그래프이다.
도 4는 근적외선 분광기를 이용하여 얻어진 pH를 기준값(reference value)과 비교한 그래프이다.
도 5는 근적외선 분광기를 이용하여 얻어진 젖산함량을 기준값(reference value)과 비교한 그래프이다.Figure 1 shows a sample pretreatment method for measuring the near infrared spectrum of Italian laigrass silage.
FIG. 2 shows a graph showing the near infrared spectrum of Italian liegrass silage and a graph after differentiating the near infrared spectrum of Italian liegrass silage.
3 is a graph comparing the moisture content obtained using a near infrared spectroscopy with a reference value.
4 is a graph comparing a pH obtained using a near infrared spectrometer with a reference value.
5 is a graph comparing lactic acid content obtained using a near infrared spectrometer with a reference value.
본 발명의 목적을 달성하기 위하여, 본 발명은In order to achieve the object of the present invention,
(a) 이탈리안 라이그라스 사일리지 시료의 근적외선 스펙트럼을 획득하는 단계;(a) acquiring a near infrared spectrum of an Italian liegrass silage sample;
(b) 상기 근적외선 스펙트럼의 측정 파장별 갭을 4 nm 또는 8 nm로 하여 수학적으로 전처리하고, 상기 전처리된 근적외선 스펙트럼에 1차 미분법을 적용하여 수처리하며, 상기 수처리된 근적외선 스펙트럼을 부분최소자승법(Partial Least Square: PLS)으로 회귀분석하여 검량식을 유도하는 단계;(b) mathematically pretreatment by measuring the wavelength of the near-infrared spectrum at a wavelength of 4 nm or 8 nm, apply water to the pre-processed near-infrared spectrum by applying a first-order differential method, and partially process the water-treated near-infrared spectrum Inducing a calibration equation by regression analysis using Least Square: PLS);
(c) 상기 검량식을 확인하는 단계; 및(c) checking the calibration formula; And
(d) 상기 검량식을 이용하여 상기 이탈리안 라이그라스 사일리지의 pH, 수분함량 또는 젖산함량을 정량분석하는 단계를 포함하는 근적외선 분광법을 이용한 이탈리안 라이그라스 사일리지의 분석방법을 제공한다.(d) it provides a method for analyzing Italian Ligras silage using near-infrared spectroscopy comprising the step of quantitatively analyzing the pH, water content or lactic acid content of the Italian Ligras silage using the calibration equation.
본 발명의 분석방법에서, 상기 (a)단계의 근적외선 스펙트럼 획득은 근적외선 분광기를 이용하여 획득할 수 있는데, 본 발명에서 사용하는 근적외선 분광기는 파장대역이 680~2500 nm으로, 다른 파장대역보다 시료의 전처리 없이 있는 그대로 측정하기가 용이하며, 시약 등을 사용하지 않을 뿐만 아니라 시료의 정량, 혼합, 가열, 추출 등의 과정의 전처리 과정이 필요 없어 신속하고, 측정시료의 손상없이 회수하여 이용 및 기타분석에 사용할 수 있는 장점이 있다.In the analysis method of the present invention, the near-infrared spectrum acquisition of step (a) can be obtained by using a near infrared spectrometer, the near-infrared spectrometer used in the present invention has a wavelength band of 680 ~ 2500 nm, than the other wavelength band of the sample It is easy to measure as it is without pretreatment. It does not use reagents, and it does not need pretreatment process such as sample quantification, mixing, heating, extraction, etc. There are advantages to using it.
본 발명의 근적외선 스펙트럼은 본 분야에서 통상적으로 사용하는 모든 방식으로 스캐닝하여 얻을 수 있으며, 바람직하게는 반사투과 방식으로 얻을 수 있다.The near-infrared spectrum of the present invention can be obtained by scanning in any manner conventionally used in the art, and preferably by reflection transmission.
또한, 본 발명의 분석방법에서, 얻어진 스펙트럼은 복잡하고 흡광 봉우리들의 겹침과 물리적인 성질에 변화를 주는 확인되지 않은 변화요인들이 존재하게 된다. 이러한 문제점을 해결하기 위해 상기 스펙트럼을 수학적 전처리하는 과정 후 회귀분석을 통하여 검량식을 유도하는 것이 바람직하다. 따라서, 본 발명에서는 얻어진 스펙트럼을 오버-피팅(over-fitting) 등 스펙트럼이 잘못 해석되는 것을 방지하기 위하여 측정 파장별 갭(gap)을 조절하는데, 본 방법에서는 수분함량 또는 pH를 분석하는 경우 4 nm로 갭을 조절하는 것이 바람직하고, 젖산함량을 분석하는 경우 8 nm로 갭을 조절하는 것이 바람직하다.In addition, in the analytical method of the present invention, the obtained spectrum is complicated and there are unidentified change factors that change the overlapping and physical properties of the absorbing peaks. In order to solve this problem, it is preferable to derive a calibration equation through regression analysis after the process of mathematical preprocessing. Therefore, in the present invention, to prevent the misinterpretation of the spectrum, such as over-fitting the obtained spectrum, by adjusting the gap (gap) for each measurement wavelength, in this
또한, 본 발명의 분석방법에서, 상기 (b)단계의 수처리는 W-X-Y(W는 미분 회수이며, X는 스펙트럼의 nm 측정 파장 갭(gap)이며, Y는 파장 갭 수처리에서 스펙트럼의 연결을 부드럽게 하기 위한 수처리를 의미함)로 표시되고, 수분함량 또는 pH의 경우 1-4-4을 적용하고, 젖산함량의 경우 1-8-8을 적용하는 것이 바람직하다.In addition, in the analysis method of the present invention, the water treatment in step (b) is WXY (W is the differential recovery, X is the wavelength of the wavelength of the nm measurement of the spectrum, Y is to smooth the connection of the spectrum in the wavelength gap water treatment) It is preferable to apply 1-4-4 for water content or pH, and 1-8-8 for lactic acid content.
또한, 본 발명의 분석방법에서, 수처리 후 회귀분석을 수행하여 검량식을 유도하게 되는데, 상기 회귀분석은 부분최소자승법(Partial least square: PLS)을 통해 적정 검량식을 유도할 수 있다.In addition, in the analysis method of the present invention, a calibration equation is derived by performing a regression analysis after water treatment. The regression analysis may derive an appropriate calibration equation through a partial least square method (PLS).
또한, 본 발명의 분석방법에서, 상기 (c)단계의 검량식 확인은 교차검증(cross validation)을 통해 확인할 수 있다.In addition, in the analysis method of the present invention, the calibration formula check in step (c) can be confirmed through cross validation.
본 발명은 또한,The present invention also relates to
(a) 이탈리안 라이그라스 사일리지 시료의 근적외선 스펙트럼을 획득하는 단계;(a) acquiring a near infrared spectrum of an Italian liegrass silage sample;
(b) 상기 근적외선 스펙트럼의 측정 파장별 갭을 4 nm로 하여 수학적으로 전처리하고, 상기 전처리된 근적외선 스펙트럼에 1차 미분법을 적용하여 수처리하며, 상기 수처리된 근적외선 스펙트럼을 부분최소자승법(Partial Least Square: PLS)으로 회귀분석하여 검량식을 유도하는 단계;(b) mathematically pretreatment with a measurement wavelength gap of the near-infrared spectrum as 4 nm, apply water to the pre-treated near-infrared spectrum by applying a first-order differential method, and apply the partial-least square method to the water-treated near-infrared spectrum (Partial Least Square: Regression analysis using PLS) to derive a calibration equation;
(c) 상기 검량식을 확인하는 단계; 및(c) checking the calibration formula; And
(d) 상기 검량식을 이용하여 시료를 정량분석하는 단계를 포함하는 이탈리안 라이그라스 사일리지의 pH 측정 방법을 제공한다.(d) it provides a method for measuring the pH of Italian Ligras silage comprising the step of quantitatively analyzing the sample using the calibration equation.
본 발명은 또한,The present invention also relates to
(a) 이탈리안 라이그라스 사일리지 시료의 근적외선 스펙트럼을 획득하는 단계;(a) acquiring a near infrared spectrum of an Italian liegrass silage sample;
(b) 상기 근적외선 스펙트럼의 측정 파장별 갭을 4 nm로 하여 수학적으로 전처리하고, 상기 전처리된 근적외선 스펙트럼에 1차 미분법을 적용하여 수처리하며, 상기 수처리된 근적외선 스펙트럼을 부분최소자승법(Partial Least Square: PLS)으로 회귀분석하여 검량식을 유도하는 단계;(b) mathematically pretreatment with a measurement wavelength gap of the near-infrared spectrum as 4 nm, apply water to the pre-treated near-infrared spectrum by applying a first-order differential method, and apply the partial-least square method to the water-treated near-infrared spectrum (Partial Least Square: Regression analysis using PLS) to derive a calibration equation;
(c) 상기 검량식을 확인하는 단계; 및(c) checking the calibration formula; And
(d) 상기 검량식을 이용하여 시료를 정량분석하는 단계를 포함하는 이탈리안 라이그라스 사일리지에 포함된 수분함량의 측정 방법을 제공한다.(d) provides a method for measuring the water content contained in Italian lygras silage comprising the step of quantitatively analyzing the sample using the calibration equation.
본 발명은 또한,The present invention also relates to
(a) 이탈리안 라이그라스 사일리지 시료의 근적외선 스펙트럼을 획득하는 단계;(a) acquiring a near infrared spectrum of an Italian liegrass silage sample;
(b) 상기 근적외선 스펙트럼의 측정 파장별 갭을 8 nm로 하여 수학적으로 전처리하고, 상기 전처리된 근적외선 스펙트럼에 1차 미분법을 적용하여 수처리하며, 상기 수처리된 근적외선 스펙트럼을 부분최소자승법(Partial Least Square: PLS)으로 회귀분석하여 검량식을 유도하는 단계;(b) mathematically pretreatment with a measurement wavelength gap of the near-infrared spectrum as 8 nm, apply water to the pre-treated near-infrared spectrum by applying a first-order differential method, and apply the partial-least square method to the water-treated near-infrared spectrum (Partial Least Square: Regression analysis using PLS) to derive a calibration equation;
(c) 상기 검량식을 확인하는 단계; 및(c) checking the calibration formula; And
(d) 상기 검량식을 이용하여 시료를 정량분석하는 단계를 포함하는 이탈리안 라이그라스 사일리지에 포함된 젖산함량의 측정 방법을 제공한다.
(d) it provides a method for measuring the lactic acid content contained in Italian lygras silage comprising the step of quantitatively analyzing the sample using the calibration equation.
이하, 본 발명을 실시예에 의해 상세히 설명한다. 그러나, 하기 실시예는 본 발명을 예시하는 것일 뿐, 본 발명의 내용이 하기 실시예에 한정되는 것이 아니다.
Hereinafter, the present invention will be described in detail by way of examples. However, the following examples are merely illustrative of the present invention, and the content of the present invention is not limited to the following examples.
실시예Example 1: One: 근적외선을Near-infrared 이용한 Used 이탈리안Italian 라이그라스Ryegrass 사일리지의Silage 성분 분석 Component analysis
1. 시료준비 및 근적외선 스펙트럼 획득1. Sample Preparation and NIR Spectrum Acquisition
시료는 2010~2011년까지 전국 이탈리안 라이그라스 사일리지 조제 농가로부터 240점을 수집하였다. 수집한 이탈리안 라이그라스 사일리지를 가위로 2~3 cm로 절단한 후 100~150 g 정도를 시료컵에 충진한 후 근적외선 분광분석기에 장착하여 스캐닝하였으며, 측정방식은 반사투과법을 사용하였고, 1 nm 간격으로 스캐닝을 실시하였다(도 1). 그리고 근적외선 파장대역은 680~2500 nm에서 실시하였다.Samples were collected from 240 Italian Ryegrass silage farms from 2010 to 2011. The collected Italian lygras silage was cut into 2 ~ 3 cm with scissors, and then filled with 100 ~ 150 g into the sample cup and mounted on a near infrared spectrometer. Scanning was performed using a reflection transmission method. Scanning was performed at intervals (FIG. 1). The near infrared wavelength band was performed at 680 ~ 2500 nm.
이와 같은 방법으로 계산된 이탈리안 라이그라스 사일리지의 pH, 수분함량 및 젖산함량은 하기 표 1에 나타내었고, 도 2의 왼쪽 그래프와 같은 스펙트럼을 얻을 수 있었다.The pH, water content, and lactic acid content of Italian lygras silage calculated in this manner are shown in Table 1 below, and a spectrum as shown in the left graph of FIG. 2 was obtained.
2. 수처리 및 회귀분석2. Water Treatment and Regression Analysis
수처리는 미분법을 나타내는 것으로 가장 많이 사용되는 스펙트럼 전처리 기법으로 스펙트럼을 미분하여 흡수대의 변화를 강조함으로써 스펙트럼의 변화는 증폭되고, 동시에 변화만 보기 때문에 바탕선이 움직여도 관계가 없다. 즉, 미분으로 도 2의 오른쪽 그래프와 같이 바탕선 변화가 제거된다. 상기 스캐닝한 근적외선 스펙트럼에 1차 또는 2차 미분법을 적용하여 수처리하였다. 수처리의 W-X-Y에서 W는 미분 회수이며, X는 스펙트럼의 nm 측정 파장 갭(gap), Y는 파장 갭 수처리에서 스펙트럼의 연결을 부드럽게 하기 위한 수처리를 의미한다. 상기 수처리된 근적외선 스펙트럼을 계량분석화학(Chemometrics)을 이용하여 부분최소자승법(Partial Least Square: PLS)으로 회귀분석하여 검량식을 유도하였다.Water treatment is a spectral pretreatment technique that is the most widely used technique, and it is irrelevant whether the baseline moves because the change in the spectrum is amplified by simultaneously differentiating the spectrum to emphasize the change of the absorption band. That is, the derivative changes the baseline as shown in the graph on the right side of FIG. 2. The scanned near infrared spectrum was subjected to water treatment by applying a first-order or second-order differential method. In W-X-Y of water treatment, W is differential recovery, X is wavelength measurement of the wavelength of the wavelength (gap), Y means water treatment to smooth the connection of the spectrum in the wavelength gap water treatment. The water-treated near-infrared spectrum was regressively analyzed by Partial Least Square (PLS) using quantitative chemistry (Chemometrics) to derive a calibration equation.
하기 표 2는 이탈리안 라이그라스 사일리지의 수분함량 분석을 위한 검량식 작성의 결과이다. 하기 표 2와 같이 1-4-4를 통한 검량식이 결정계수(R2 )가 높으면서 오차가 낮게 나타나, 가장 우수한 것으로 판단되었다. 도 3은 실험실 내에서 표준분석하여 얻어진 수분 함량(기준값: Ref values)과 근적외선 분광기를 통해 도출된 검량식에서 얻어진 수분 분석치와의 상관관계를 나타낸 것으로, 거의 일치하여 검량식의 정확성을 확인할 수 있었다.Table 2 below shows the results of a calibration formula for moisture content analysis of Italian lygras silage. As shown in Table 2, the calibration coefficient of the calibration formula through 1-4-4 (R 2 ), The error was low, and was judged to be the best. Figure 3 shows the correlation between the moisture content (reference value: Ref values) obtained by the standard analysis in the laboratory and the moisture analysis value obtained from the calibration formula derived through the near infrared spectroscopy, almost consistent with the accuracy of the calibration formula could be confirmed.
PLS
Pls
SEC: 검량식 작성 표준오차SEC: Calibration Standard Error
SECV: 작성된 검량식의 상호검증 오차
SECV: Mutual Validation Error in Written Calibration
하기 표 3은 수처리에 따른 이탈리안 라이그라스 사일리지의 pH 분석을 위한 검량식 작성의 결과이다. 하기 표 3과 같이 1-4-4를 통한 검량식이 결정계수(R2 )가 높게 나타나, 가장 우수한 것으로 판단되었다. 도 4는 실험실 내에서 표준분석하여 얻어진 pH(Ref values)와 근적외선 분광기를 통해 도출된 검량식에서 얻어진 pH 분석치와의 상관관계를 나타낸 것으로, 거의 일치하여 검량식의 정확성을 확인할 수 있었다.Table 3 below shows the results of a calibration formula for pH analysis of Italian lygras silage according to water treatment. As shown in Table 3, the calibration coefficient of the calibration formula through 1-4-4 (R 2 )end It appeared high and was judged to be the best. Figure 4 shows the correlation between the pH (Ref values) obtained by the standard analysis in the laboratory and the pH analysis value obtained from the calibration formula derived through the near infrared spectroscopy, it was confirmed that the accuracy of the calibration formula was almost identical.
PLS
Pls
SEC: 검량식 작성 표준오차SEC: Calibration Standard Error
SECV: 작성된 검량식의 상호검증 오차
SECV: Mutual Validation Error in Written Calibration
하기 표 4는 수처리에 따른 이탈리안 라이그라스 사일리지의 젖산 성분분석을 위한 검량식 작성의 결과이다. 하기 표 4와 같이 1-8-8를 통한 검량식이 결정계수(R2 )가 가장 높게 나타나, 가장 우수한 것으로 판단되었다. 도 5는 실험실 내에서 표준분석하여 얻어진 젖산함량(Ref values)과 근적외선 분광기를 통해 도출된 검량식에서 얻어진 젖산 분석치와의 상관관계를 나타낸 것으로, 거의 일치하여 검량식의 정확성을 확인할 수 있었다.Table 4 below shows the results of a calibration formula for lactic acid component analysis of Italian lygras silage according to water treatment. As shown in Table 4, the calibration coefficient of the calibration formula through 1-8-8 (R 2 )end It appeared the highest and was judged the best. Figure 5 shows the correlation between the lactic acid content (Ref values) obtained by the standard analysis in the laboratory and the lactic acid analysis values obtained from the calibration formula derived through the near infrared spectroscopy, almost identical to confirm the accuracy of the calibration formula.
PLS
Pls
SEC: 검량식 작성 표준오차SEC: Calibration Standard Error
SECV: 작성된 검량식의 상호검증 오차
SECV: Mutual Validation Error in Written Calibration
3. 검증3. Verification
검량식이 얻어지면 이 검량식의 적용이 합당한지를 검증하여야 한다. 따라서 검량식을 만들 때 교차검증(cross validation: CV)을 사용하여 검량세트 내부 검증을 하였다. 이 방법은 검량세트 내 시료 중 일부는 검량식을 만드는데 이용되고, 검량식 작성에 제외된 시료들을 대상으로 별도의 예측세트(Prediction set)를 만들어 검량식을 검증하는 것이다.
Once a calibration equation has been obtained, it should be verified that the application of this calibration is reasonable. Therefore, the internal validation of the calibration set was performed using cross validation (CV) when creating the calibration formula. In this method, some of the samples in the calibration set are used to make a calibration formula, and a validation set is verified by creating a separate prediction set for the samples excluded from the calibration formula.
이와 같은 근적외선 분광분석기를 이용한 이탈리안 라이그라스 사일리지의 pH, 수분함량 또는 젖산함량 측정 방법에 따르면, 수처리는, 수분함량 또는 pH의 경우 1-4-4를 통한 검량식이 바람직하며, 젖산함량의 경우 1-8-8을 통한 검량식이 바람직하였다. 또한, 적정 검량식을 도출하기 위한 회귀식 작성은 부분최소자승법(Partial Least Square: PLS)이 가장 적합하였다.According to the method for measuring pH, water content or lactic acid content of Italian lygras silage using such a near-infrared spectrometer, the water treatment is preferably a calibration formula through 1-4-4 for water content or pH, and for
Claims (11)
(b) 상기 근적외선 스펙트럼의 측정 파장별 갭을 4 nm 또는 8 nm로 하여 수학적으로 전처리하고, 상기 전처리된 근적외선 스펙트럼에 1차 미분법을 적용하여 수처리하며, 상기 수처리된 근적외선 스펙트럼을 부분최소자승법(Partial Least Square: PLS)으로 회귀분석하여 검량식을 유도하는 단계;
(c) 상기 검량식을 확인하는 단계; 및
(d) 상기 검량식을 이용하여 상기 이탈리안 라이그라스 사일리지의 pH, 수분함량 또는 젖산함량을 정량분석하는 단계를 포함하는 근적외선 분광법을 이용한 이탈리안 라이그라스 사일리지의 분석방법.(a) acquiring a near infrared spectrum of an Italian liegrass silage sample;
(b) mathematically pretreatment by measuring the wavelength of the near-infrared spectrum at a wavelength of 4 nm or 8 nm, apply water to the pre-processed near-infrared spectrum by applying a first-order differential method, and partially process the water-treated near-infrared spectrum Inducing a calibration equation by regression analysis using Least Square: PLS);
(c) checking the calibration formula; And
(d) quantitatively analyzing the pH, water content or lactic acid content of the Italian lygras silage using the calibration equation.
(b) 상기 근적외선 스펙트럼의 측정 파장별 갭을 4 nm로 하여 수학적으로 전처리하고, 상기 전처리된 근적외선 스펙트럼에 1차 미분법을 적용하여 수처리하며, 상기 수처리된 근적외선 스펙트럼을 부분최소자승법(Partial Least Square: PLS)으로 회귀분석하여 검량식을 유도하는 단계;
(c) 상기 검량식을 확인하는 단계; 및
(d) 상기 검량식을 이용하여 시료를 정량분석하는 단계를 포함하는 이탈리안 라이그라스 사일리지의 pH 측정 방법.(a) acquiring a near infrared spectrum of an Italian liegrass silage sample;
(b) mathematically pretreatment with a measurement wavelength gap of the near-infrared spectrum as 4 nm, apply water to the pre-treated near-infrared spectrum by applying a first-order differential method, and apply the partial-least square method to the water-treated near-infrared spectrum (Partial Least Square: Regression analysis using PLS) to derive a calibration equation;
(c) checking the calibration formula; And
(D) method for measuring the pH of Italian lygras silage comprising the step of quantitatively analyzing the sample using the calibration equation.
(b) 상기 근적외선 스펙트럼의 측정 파장별 갭을 4 nm로 하여 수학적으로 전처리하고, 상기 전처리된 근적외선 스펙트럼에 1차 미분법을 적용하여 수처리하며, 상기 수처리된 근적외선 스펙트럼을 부분최소자승법(Partial Least Square: PLS)으로 회귀분석하여 검량식을 유도하는 단계;
(c) 상기 검량식을 확인하는 단계; 및
(d) 상기 검량식을 이용하여 시료를 정량분석하는 단계를 포함하는 이탈리안 라이그라스 사일리지에 포함된 수분함량의 측정 방법.(a) acquiring a near infrared spectrum of an Italian liegrass silage sample;
(b) mathematically pretreatment with a measurement wavelength gap of the near-infrared spectrum as 4 nm, apply water to the pre-treated near-infrared spectrum by applying a first-order differential method, and apply the partial-least square method to the water-treated near-infrared spectrum (Partial Least Square: Regression analysis using PLS) to derive a calibration equation;
(c) checking the calibration formula; And
(d) Method of measuring the water content contained in Italian lygras silage comprising the step of quantitatively analyzing the sample using the calibration equation.
(b) 상기 근적외선 스펙트럼의 측정 파장별 갭을 8 nm로 하여 수학적으로 전처리하고, 상기 전처리된 근적외선 스펙트럼에 1차 미분법을 적용하여 수처리하며, 상기 수처리된 근적외선 스펙트럼을 부분최소자승법(Partial Least Square: PLS)으로 회귀분석하여 검량식을 유도하는 단계;
(c) 상기 검량식을 확인하는 단계; 및
(d) 상기 검량식을 이용하여 시료를 정량분석하는 단계를 포함하는 이탈리안 라이그라스 사일리지에 포함된 젖산함량의 측정 방법.(a) acquiring a near infrared spectrum of an Italian liegrass silage sample;
(b) mathematically pretreatment with a measurement wavelength gap of the near-infrared spectrum as 8 nm, apply water to the pre-treated near-infrared spectrum by applying a first-order differential method, and apply the partial-least square method to the water-treated near-infrared spectrum (Partial Least Square: Regression analysis using PLS) to derive a calibration equation;
(c) checking the calibration formula; And
(d) measuring the amount of lactic acid contained in Italian lygras silage comprising the step of quantitatively analyzing the sample using the calibration equation.
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| CN117388209B (en) * | 2023-11-23 | 2024-03-15 | 蓝星智云(山东)智能科技有限公司 | On-line near infrared spectrometer measuring method based on instant reference feedback |
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