• 제목/요약/키워드: Near Infrared Reflectance (NIR)

검색결과 180건 처리시간 0.029초

Nondestructive Determination of Humic Acids in Soils by Near Infrared Reflectance Spectroscopy

  • Seo, Sang-Hyun;Park, Woo-Churl;Cho, Rae-Kwang;Xiaori Han
    • Near Infrared Analysis
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    • 제1권1호
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    • pp.31-35
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    • 2000
  • Near-infrared reflectance spectroscopy(NIRS) was used to determine the humic acids in soil samples from the fields of different crops and land-use over Youngnam and Honam regions in Korea. An InfraAlyzer 500 scanning spectrophotometer was obtained near infrared relectance spectra of soil at 2-nm intervals from 1100 to 2500nm. Multiple linear regression(MLR) or partial least square regression (PLSR) was used to evaluate a NIRS method for the rapid and nondestructive determination of humic acid, fulvic acid and its total contents in soils. The raw spectral data(log 1/R) can be used for estimating humic acid, fulvic acid and its total contents in soil by MLR procedure between the content of a given constituent and the spectral response of several bands. In which the predicted results for fulvic acid is the best in the constituents. The new spectral data are converted from the raw spectra by PLSR method such as the first derivative of each spectrum can also be used to predict humic acid and fulvic acid of the soil samples. A low SEC, SEP and a high coefficient of correlation in the calibration and validation stages enable selection of the best manipulation. But a simple calibration and prediction method for determining humic acid and fulvic acid should be selected under similar accuracy and precision of prediction. NIRS technique may be an effective method for rapid and nondestructive determination for humic acid, fulvic acid and its total contents in soils.

PREDICTION OF BEEF TENDERNESS USING NEAR-INFRARED REFLECTANCE SPECTRUM ANALYSIS

  • Cho, S.I.;Yeo, W.Y.;Nam, K.C.
    • 한국농업기계학회:학술대회논문집
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    • 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.III
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    • pp.521-524
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    • 2000
  • Nearinfra-red(NIR) reflectance NIR a spectra (400 to 2,100 nm) were collected on 32 beef samples to find feasibility of predicting beef tenderness. The study to predict beef tenderness was accomplished with the stepwise second differential data of the collected NIR spectra. Beef tenderness was measured by Warner-Bratzler(WB) shear force using a Universal Testing Machine(UTM). After modeling the relation between Warner-Bratzler shear force and NIR spectrum of 19 samples among the 32 beef samples, the verification was carried out through predicting the other 13 samples. The SEC and R$^2$ values in the prediction equation were 9.07(N) and 0.6463, respectively. The SEP and R$^2$ were 14.8(N) and 0.7082 (wave length 552 nm, 1988 nm) respectively. The result implied that it was possible to predict the beef tenderness using NIR spectrum and that the tenderness could be predicted non-destructively in real time.

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Development of Nondestructive Grouping System for Soil Organic Matter Using VIS and NIR Spectral Reflectance

  • Sung J.H.
    • Agricultural and Biosystems Engineering
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    • 제6권1호
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    • pp.15-21
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    • 2005
  • This study was conducted to develop a nondestructive grouping system for soil organic matter using visible (VIS) and near infrared (NIR) spectroscopic method. The artificial light was irradiated on the cut soil surface at 15 to 20 cm depths to reduce the errors of light at open field. The reflectance energy from the cut soil surface was measured to group the soil organic matter using VIS/NIR light sensor with narrow band pass filter. From reflectance spectra of soil samples, the sensitive wavelengths for measuring the soil organic matter were selected and compared to previous research results. The grouping system for soil organic matter consisted of light sensor with band pass filter measuring the reflectance energy of the cut soil surface, global positing system (GPS), analog-to-digital (AD) converter, computer and operating software. The regression models to predict the soil organic matter were developed and evaluated. From field test, the accuracies of the developed light sensor system were 81.3% for five-stage grouping of the soil organic matters and 91.0% for three-stages grouping of the soil organic matters, respectively. It could be possible to support the decision making for variable rate applications with the developed grouping system for soil organic matter in precision agriculture.

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Differentiation between Normal and White Striped Turkey Breasts by Visible/Near Infrared Spectroscopy and Multivariate Data Analysis

  • Zaid, Amal;Abu-Khalaf, Nawaf;Mudalal, Samer;Petracci, Massimiliano
    • 한국축산식품학회지
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    • 제40권1호
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    • pp.96-105
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    • 2020
  • The appearance of white striations over breast meat is an emerging and growing problem. The main purpose of this study was to employ the reflectance of visible-near infrared (VIS/NIR) spectroscopy to differentiate between normal and white striped turkey breasts. Accordingly, 34 turkey breast fillets were selected representing a different level of white striping (WS) defects (normal, moderate and severe). The findings of VIS/NIR were analyzed by principal component (PC1) analysis (PCA). It was found that the first PC1 for VIS, NIR and VIS/NIR region explained 98%, 97%, and 96% of the total variation, respectively. PCA showed high performance to differentiate normal meat from abnormal meat (moderate and severe WS). In conclusion, the results of this research showed that VIS/NIR spectroscopy was satisfactory to differentiate normal from severe WS turkey fillets by using several quality traits.

Rapid Prediction of Amylose Content of Polished Rice by Fourier Transform Near-Infrared Spectroscopy

  • Lee, Jin-Cheol;Yoon, Yeon-Hee;Kim, Sun-Min;Pyo, Byong-Sik;Hsieh, Fu-Hung;Kim, Hak-Jin;Eun, Jong-Bang
    • Food Science and Biotechnology
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    • 제16권3호
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    • pp.477-481
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    • 2007
  • Fourier transform near-infrared (FT-NIR) spectroscopy and partial least squares (PLS) regression were used to predict the amylose content of polished rice. Spectral reflectance data in a wavelength range of 1,000 to 2,500 nm were obtained with a commercial spectrophotometer for 60 different varieties of Korean rice. For a comparison of this spectroscopic method to a standard chemical analysis, the amylose contents of the tested rice samples were determined by the iodine-blue colorimetric method. The highest correlation for the rice amylose ($R^2=0.94$, standard error of prediction=0.20% amylose content) was obtained when using the FT-NIR spectrum data pre-treated with normalization, the first derivative, smoothing, and scattering correction.

SELECTION OF VISIBLE/NIR WAVELENGTHS FOR CHARACTERIZING FECAL AND INGESTA CONTAMINATION OF POULTRY CARCASSES

  • William R.Windham;Park, Bosoon;Kurt C.Lawarece;Douglas P.Smith
    • 한국근적외분광분석학회:학술대회논문집
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    • 한국근적외분광분석학회 2001년도 NIR-2001
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    • pp.3105-3105
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    • 2001
  • Ingests and fecal contamination on a poultry carcass is a food safety hazard due to potential microbiological contamination. A visible/near-infrared (NIR) spectrometer was used to discriminate among pure ingesta and fecal material, breast skin contaminated with ingesta or fecal material and uncontaminated breast skin. Birds were fed isocaloric diets formulated with either maize, mile, or wheat and soybean meal for protein requirements. Following completion of the feeding period (14 days), the birds were humanely processed and eviscerated to obtain ingests from the crop or proventriculus and feces from the duodenum, ceca, and colon portion of the digestive tract. Pure feces and ingesta, breast skin, and contaminated breast skin were scanned from 400 to 2500 nm and analyzed from 400 to 900 nm. Principal component analysis (PCA) of reflectance spectra was used to discriminate between contaminates and uncontaminated breast skin. Results indicate that visible (400 to 760 nm) and NIR 760-900 nm spectra can detect contaminates. From PCA analysis, key wavelengths were identified for discrimination of uncontaminated skin from contaminates based the evaluation of loadings weights.

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지상 원격탐사의 농업적 활용 (Agricultural Application of Ground Remote Sensing)

  • 홍순달;김재정
    • 한국토양비료학회지
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    • 제36권2호
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    • pp.92-103
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    • 2003
  • Research and technological advances in the field of remote sensing have greatly enhanced the ability to detect and quantify physical and biological stresses that affect the productivity of agricultural crops. Reflectance in specific visible and near-infrared regions of the electromagnetic spectrum have proved useful in detection of nutrient deficiencies. Especially crop canopy sensors as a ground remote sensing measure the amount of light reflected from nearby surfaces such as leaf tissue or soil and is in contrast to aircraft or satellite platforms that generate photographs or various types of digital images. Multi-spectral vegetation indices derived from crop canopy reflectance in relatively wide wave band can be used to monitor the growth response of plants in relation to environmental factors. The normalized difference vegetation index (NDVI), where NDVI = (NIR-Red)/(NIR+Red), was originally proposed as a means of estimating green biomass. The basis of this relationship is the strong absorption (low reflectance) of red light by chlorophyll and low absorption (high reflectance and transmittance) in the near infrared (NIR) by green leaves. Thereafter many researchers have proposed the other indices for assessing crop vegetation due to confounding soil background effects in the measurement. The green normalized difference vegetation index (GNDVI), where the green band is substituted for the red band in the NDVI equation, was proved to be more useful for assessing canopy variation in green crop biomass related to nitrogen fertility in soils. Consequently ground remote sensing as a non destructive real-time assessment of nitrogen status in plant was thought to be useful tool for site specific crop nitrogen management providing both spatial and temporal information.

DETERMINATION OF MOISTURE AND NITROGEN ON UNDRIED FORAGES BY NEAR INFRARED REFLECTANCE SPECTROSCOPY(NIRS)

  • Cozzolino, D.;Labandera, M.;Inia La Estanzuela
    • 한국근적외분광분석학회:학술대회논문집
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    • 한국근적외분광분석학회 2001년도 NIR-2001
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    • pp.1620-1620
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    • 2001
  • Forages, both grazed and conserved, provide the basis of ruminant production systems throughout the world. More than 90 per cent of the feed energy consumed by herbivorous animals world - wide were provided by forages. With such world - wide dependence on forages, the economic and nutritional necessity of been able to characterize them in a meaningful way is vital. The characterization of forages for productive animals is becoming important for several reasons. Relative to conventional laboratory procedures, Near Infrared Reflectance Spectroscopy (NIRS) offers advantages of simplicity, speed, reduced chemical waste, and more cost-effective prediction of product functionality. NIR spectroscopy represents a radical departure from conventional analytical methods, in that entire sample of forage is characterized in terms of its absorption properties in the near infrared region, rather than separate subsamples being treated with various chemicals to isolate specific components. This forces the analyst to abandon his/her traditional narrow focus on the sample (one analyte at a time) and to take a broader view of the relationship between components within the sample and between the sample and the population from which it comes. forage is usually analysed by NIRS in dry and ground presentation. Initial success of NIRS analysis of coarse forages suggest a need to better understand the potential for analysis of minimally processed samples. Preparation costs and possible compositional alterations could be reduced by samples presented to the instrument in undried and unground conditions. NIRS has gained widespread acceptance for the analysis of forage quality constituents on dry material, however little attention has been given to the use of NIRS for chemical determinations on undried and unground forages. Relatively few works reported the use of NIRS to determine quality parameters on undried materials, most of them on both grass and corn silage. Only two works have been found on the determination of quality parameters on fresh forages. The objectives of this paper were (1) to evaluate the use of NIRS for determination of nitrogen and moisture on undried and unground forage samples and (2) to explore two mathematical treatments and two NIR regions to predict chemical parameters on fresh forage. Four hundred forage samples (n: 400) were analysed in a NIRS 6500 instrument (NIR Systems, PA, USA) in reflectance mode. Two mathematical treatments were applied: 1,4,4,1 and 2,5,5,2. Predictive equations were developed using modified partial least squares (MPLS) with internal cross - validation. Coefficient of determination in calibration (${R^2}_{CAL}$) and standard error in cross-validation (SECV) for moisture were 0.92 (12.4) and 0.92 (12.4) for 1,4,4,1 and 2,5,5,2 respectively, on g $kg^{-1}$ dry weight. For crude protein NIRS calibration statistics yield a (${R^2}_{CAL}$) and (SECV) of 0.85 (19.8) and 0.85 (19.6) for 1,4,4,1 and 2,5,5,2 respectively, on a dry weight. It was concluded that NIRS is a suitable method to predict moisture and nitrogen on fresh forage without samples preparation.

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CALIBRATION TRANSFER FROM REFLECTANCE TO INTERACTANCE-REFLECTANCE WITHOUT STANDARDS: USE OF MATHEMATICAL PRETREATMENTS

  • Fernandez Cabanas, Victor-M.;Varo, Garrido;Dardenne, Pierre
    • 한국근적외분광분석학회:학술대회논문집
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    • 한국근적외분광분석학회 2001년도 NIR-2001
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    • pp.1242-1242
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    • 2001
  • The use of fibre optic probes for NIR quality control in the industry is becoming very important, as it provides a powerful tool to reduce sample analysis time and it facilitates the implementation of on-line analyses. However, most of the applications of fibre optics and probes have been done on suspensions, clear liquids and films, chemical and pharmaceutical products and also on fruits and animal products. Traditional applications of near infrared spectroscopy in agriculture have been developed in reflectance mode and calibration transfer could be an interesting way to reduce efforts. Classical methods for calibration transfer between different instruments involve the use of sealed reference cups, but, as fibre optic analysis does not use cups, it is necessary to develop new methods for calibration transfer without standards (Blank et al., 1996). In this paper, we have studied how the most used mathematical pretreatments (three methods of Multiplicative Scatter Correction, Standard Normal Variate, Detrending and derivatives) and their combinations applied to calibration development can contribute to reduce spectral differences between instruments. Calibration equations were obtained for three sets of cereals (barley, wheat and maize) scanned in reflectance mode and then they were validated with samples analysed in reflectance and interactance-reflectance mode (fibre optic). Preliminary results show how some combination of pretreatments reduce the differences in the predicted values, measured as standard error of differences, facilitating the use of calibrations obtained in reflectance for samples analysed by interactance-reflectance. However, the application of pretreatments is not enough to satisfy the control limits for calibration transfer suggested by Shenk et al. (1992), and it should be necessary to combine them with a specific algorithm for instruments standardization.

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초분광 근적외선 영상 기술을 이용한 흙의 함수비 측정 기술 (Soil Water Content Measurement Technology Using Hyperspectral Visible and Near-Infrared Imaging Technique)

  • 임환희;전에녹;이득환;전준서;이승래
    • 한국지반공학회논문집
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    • 제35권11호
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    • pp.51-62
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    • 2019
  • 본 연구에서는 초분광 근적외선 영상을 이용하여 광역지역의 흙의 함수비 변화를 간편한 방법으로 예측하기 위해 수행되었다. 근적외선(VNIR) 영역대에서 변화되는 함수비 별로 모래, 화강풍화토(우면산, 구룡산, 대모산, 황령산), 카오리나이트를 초분광 카메라로 촬영하여 반사율을 추출하였고, 흙의 함수비와 가장 연관성 높은 매개변수를 찾기 위하여 선정된 매개변수와 함수비를 변수로하여 Partial Least Square Regression(PLSR) 분석을 이용하여 함수비 예측모델을 구축하였다. 함수비 예측모델을 구축한 결과, 흙의 종류에 관계없이 Area of reflectance(Near-infrared, NIR)의 매개변수가 흙의 함수비와 가장 연관성 높은 매개변수임을 확인하였고, 모든 흙에서 예측모델의 정확도(R2)는 0.9 이상임을 확인하였다. 또한 흙의 실제 함수비와 비교 검증해본 결과, 평균절대백분율(mean absolute percentage error, MAPE)이 15%이내로 확인되었다. 따라서 대상 흙들에서 50% 이내에서 변화되는 함수비 예측 가능성을 확인하였다. 본 연구를 통해 초분광 근적외선 영상을 이용하여 모래, 화강풍화토, 카오리나이트의 함수비 예측 가능성을 확인하였고, 모델의 정확도 개선 및 더 높은 범위의 함수비 예측을 위해서는 흙의 분류모델 개발이 추가적으로 필요하다고 판단된다.