Discrimination of geographic origin of agricultural products is a important issue in Korea because the price difference between Korean domestic and imported cereals is a key among some reasons. NIRS (Near Infrared Reflectance Spectroscopy) has been applied to classify the geographical origin of soybeans. Total 135 samples (Korean domestic 92 and foreign 43) were used to obtain calibration equation through 400~2,500 nm wavelength. The math treatment with 1st derivative and 4 nm gap and the modified partial least squares(MPLS)regression was outstanding for calibration equation. The standard error of calibration and determination coefficient in calibration set(n=115) was 6.65 and 0.98, respectively. And it showed that the extra 20 samples for validation equation were identified their authentication correctly. This study describes that the application of NIRS would be possible for discrimination of geographical origin between Korean domestic and imported soybeans.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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2001.06a
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pp.1612-1612
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2001
The production of grain for export and domestic use is one of Australia's most important agricultural industries, and the NIR technique has been used extensively over many years for the routine monitoring of grain quality, particularly moisture and protein content. Because most Australian grain is intended for human food production, the determinants of grain quality for livestock feed, apart from protein, have been largely ignored. However the increasing use of grain for feeding to pigs, poultry, beef cattle and dairy cows has led to an important national research project entitled “Premium Grains for Livestock”. Two of the objectives of this project are to determine the compositional and functional characteristics of grains which influence their nutritional quality for the various classes of livestock, and to adopt rapid and objective analytical tests for these quality criteria. NIR has been used in this project firstly to identify a set of grain samples from a large population of breeders' lines which showed a wide spectral variation, and hence a potentially wide variation in nutritional value. The selected samples were not only subjected to an extensive array of chemical, physical and in vitro analyses, but also were grown out to produce sufficient quantities of grain to feed to animals in vivo studies. Additional grains were also strategically selected from farms in order to include the effect of weather damage, such as rain, drought and frost. In this study to date, NIR calibrations have been derived or attempted, on both ground and whole grains, for in vivo dry matter digestibility (DMD), pepsin-cellulase dry matter disappearance, protein, fat, acid detergent fibre, neutral detergent fibre, starch, in sacco DMD and in vitro assays to simulate starch digestion in the lumen and small intestine. Results so far indicate high calibration accuracy for chemical components (SECV 0.3 to 2.6%) and very promising statistics for in vivo DMD (SECV 1.8, $R^2$ 0.93, SD 7.0, range 61.9 to 92.3, n=60). There appears to be some potential for NIR to estimate some in vitro properties, depending upon the accuracy of reference methods and appropriate sample populations. Current work is in progress to extend the range of grains with in vivo DMD values (a very laborious and expensive process) and to increase the robustness of the various NIR calibrations, with the aim of implementing uniform testing procedures for nutritional value of grains throughout Australia.
The variation of chemical structure and physical properties of crosslinked polyethylene (XLPE) during thermal aging process was investigated. The formation of carbonyl functional group resulting from thermal oxidation reaction of XLPE was monitored using X-ray photoelectron spectroscopy and near infrared (NIR) spectroscopy. It was observed that the intensity of carbonyl peak observed at 1715 nm linearly increased with aging time in NIR spectroscopy. The linear relationship between NIR peak absorbance and aging time confirmed that NIR spectroscopy might be used as a proper tool for monitoring the aging process of polymeric materials. Also the formation of crosslinks during the aging process was monitored using thermal mechanical analysis, stress-strain test, and Shore hardness test. The change in the physical properties, such as the increase in the glass transition temperature from 110 to 132$^{\circ}C$, the decrease in the strain from 265 to 110%, as well as the increase in the shore D hardness from 32 to 50, was observed during the aging process.
It is very important to add uniformly casing materials on tobacco for taste and flavor. However, analysis of casing materials was spent much time, effort and money. The object of this study was the development of a rapid method for the determination of glycerine, propylene glycol(PG), sucrose, glucose, fructose and water in the casing materials using the NIR transmittance method. Hundreds of calibration samples, with extended ranges (50%, 75%, 100%, 125%, and 150% of standard addition) in each constituent, were prepared in the casing materials at the various temperatures $(25^{\circ}C\;and\;30^{\circ}C)$. Calibration equation was developed by modified partial least square (MPLS) method using second derivative. The standard error of calibration and $R^2$ between added value and NIR estimated value results were $0.007{\sim}0.034\;and\;0.996{\sim}1.000$ for the casing sample set, respectively. The standard error of prediction and R2 between added value and NIR estimated value results were $0.010{\sim}0.034\;and\;0.997{\sim}1.000$ for the casing sample set, respectively. The analysis result was not different significantly between the NIR and added value. These results show that the NIR measurement system is an effective tool to ensure quality on the casing materials.
The high-resolution near-infrared (NIR) spectroscopy can reveal the evidence of the accretion burst (e.g., the broadened absorption features produced by the Keplerian disk motion) although the moment of the outburst was not caught. The embedded protostar IRAS 16316-1540 observed with the Immersion Grating Infrared Spectrograph (IGRINS, $R={\Delta}{\lambda}/{\lambda}{\sim}45000$) shows the broad absorption features in atomic and CO transitions, as seen in FU Orionis objects (FUors), indicative of an outburst event. We examine whether the spectra of IRAS 16316-1540 arise from the rotating inner hot gaseous disk. Using the IGRINS spectral library, we show that the line profiles of IRAS 16316-1540 are more consistent with an M1.5 V template spectrum convolved with a disk rotation profile than the protostellar photosphere absorption features with a high stellar rotation velocity. We also note that the absorption features deviated from the expected line profile of the accretion disk model can be explained by a turbulence motion generated in the disk atmosphere. From previous observations that show the complex environment and the misaligned outflow axes in IRAS 16316-1540, we suggest that an impact of infalling clumpy envelope material against the disk induces the disk precession, causing the accretion burst from the inner disk to the protostar.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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2001.06a
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pp.1129-1129
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2001
Maize, in Hungary, is the fodder-plant grown in the biggest quantity. It is not only used as a fodder but other products such as iso-sugar are made from it, too. The quality of the fodder and the produce is largely dependent on the composition of the supplied maize to the processing site. The examination of quality parameters besides conventional methods are investigated and measured by NIR spectroscopy on a routine basis. The investigated parameters are the following: water, total protein, starch and oil content. The accuracy and precision of determining these parameters we, apart from the wet chemical methods, influenced by sample preparation to a great extent. One of the main features of this is the sample particle size and its distribution across the sample. The uneven distribution of particle size negatively influences the measurement accuracy, decreases model robustness and prediction ability. With these in mind the aim of our experiment was to investigate the effect of particle size on the accuracy of maize composition determination using reflection measurement setup. In addition, we tested different spectrum transformations, which are suitable for canceling this effect. In our experiment 47 samples were analyzed with three different mesh sizes (1.5mm, 1.8mm and 2mm). The results of our findings are presented here.
This study investigates the prediction of soil OM on Korean soils using the Visible-Near Infrared (Vis-NIR) spectroscopy. The ASD Field Spec Pro was used to acquire the reflectance of soil samples to visible to near-infrared radiation (350 to 2500 nm). A total of 503 soil samples from 61 Korean soil series were scanned using the instrument and OM was measured using the Walkley and Black method. For data analysis, the spectra were resampled from 500-2450 nm with 4 nm spacing and converted to the $1^{st}$ derivative of absorbance (log (1/R)). Partial least squares regression (PLSR) and regression rules model (Cubist) were applied to predict soil OM. Regression rules model estimates the target value by building conditional rules, and each rule contains a linear expression predicting OM from selected absorbance values. The regression rules model was shown to give a better prediction compared to PLSR. Although the prediction for Andisols had a larger error, soil order was not found to be useful in stratifying the prediction model. The stratification used by Cubist was mainly based on absorbance at wavelengths of 850 and 2320 nm, which corresponds to the organic absorption bands. These results showed that there could be more information on soil properties useful to classify or group OM data from Korean soils. In conclusion, this study shows it is possible to develop good prediction model of OM from Korean soils and provide data to reexamine the existing prediction models for more accurate prediction.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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2001.06a
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pp.1273-1273
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2001
The efficiency of the luminal fermentation process influences overall efficiency of luminal production, animal health and reproduction. Ruminant production systems have a significant impact on the global environment, as well. Animal wastes contribute to pollution of the environment as ammonia volatilized to the air and nitrate leached to ground water. Microbial protein synthesis in the rumen satisfies a large proportion of the protein requirements of animals. Quantifying the microbial synthesis is possible by using markers for lumen bacteria and protozoa such as nucleic acids, purine bases, some specific amino acids, or by isotopic $^{15}N,^{32}P,\;and\;^{35}S$ labelled feeds. All those methods require cannulated animals, they are time-consuming and some methods are very expensive as well. Many attempts have been made to find an alternative method for indirect measurement of microbial synthesis in intact animals. The present investigations aimed to assess possibilities of NIRS for prediction of purine nitrogen excretion and ruminal microbial nitrogen synthesis by NIR spectra of urine. Urine samples were collected from 12 growing sheep,6 of them male, and 6- female. The sheep were included in feeding experiment. The ration consisted of sorghum silage and protein supplements -70:30 on dry matter basis. The protein supplements were chosen to differ in protein degradability. The urine samples were collected daily in a vessel containing $60m{\ell}$ 10% sulphuric acid to reduce pH below 3 and diluted with tap water to 4 liters. Samples were stored in plastic bottles and frozen at $-20^{\circ}C$ until chemical and NIRS analysis. The urine samples were analyzed for purine derivates - allantoin, uric acid, xantine and hypoxantine content. Microbial nitrogen synthesis in the lumen was calculated according to Chen and Gomes, 1995. Transmittance urine spectra with sample thickness 1mm were obtained by NIR System 6500 spectrophotometer in the spectral range 1100-2500nm. The calibration was performed using ISI software and PLS regression, respectively. The following statistical results of NIRS calibration for prediction of purine derivatives and microbial protein synthesis were obtained.(Table Omitted). The result of estimation of purine nitrogen excretion and microbial protein synthesis by NIR spectra of urine showed accuracy, adequate for rapid evaluation of microbial protein synthesis for a large number of animals and different diets. The results indicate that the advantages of the NIRS technology can be extended into animal physiological studies. The fast and low cost NIRS analyses could be used with no significant loss of accuracy when microbial protein synthesis in the lumen and the microbial protein flow in the duodenum are to be assessed by NIRS.
Hsu, Hua;Zuidhof, Martin J.;Recinos-Diaz, Guillermo;Wang, Zhiquan
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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2001.06a
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pp.1510-1510
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2001
NIRS uses reflectance signals resulting from bending and stretching vibrations in chemical bonds between carbon, nitrogen, hydrogen, sulfur and oxygen. These reflectance signals are used to measure the concentration of major chemical composition and other descriptors of homogenized and freeze-dried whole broiler carcasses. Six strains of chicken were analyzed and the NIRS model predictions compared to reference data. The results of this comparison indicate that NIRS is a rapid tool for predicting dry matter (DM), fat, crude protein (CP) and ash content in the broiler carcass. Males and females of six commercial strain crosses of broiler chicken (Gallus domesticus) were used in this study (6$\times$2 factorial design). Each strain was grown to 16 weeks of age, and duplicate serial samples were taken for body composition analysis. Each whole carcass was pressure-cooked, homogenized, and a representative sample was freeze-dried. Body composition determined as follows: DM by oven dried method at 105$^{\circ}C$ for 3 hours, fat by Mojonnier diethyl ether extraction, CP by measuring nitrogen content using an auto-analyzer with Kjeldhal digest and ash by combustion in a muffle furnace for 24 hour at 55$0^{\circ}C$. These homogenized and freeze-dried carcass samples were then scanned with a Foss NIR Systems 6500 visible-NIR spectrophotometer (400-2500nm) (Foss NIR Systems, Silver Spring, MD., US) using Infra-Soft-International, ISI, WinISl software (ISI, Port Matilda, US). The NIRS spectra were analyzed using principal component (PC) analysis. This data was corrected for scatter using standard normal “Variate” and “Detrend” technique. The accuracy of the NIRS calibration equations developed using Partial Least Squares (PLS) for predicting major chemical composition and carcass descriptors- such as body mass (BM), bird dry matter and moisture content was tested using cross validation. Discrimination analysis was also used for sex and strain identification. According to Dr John Shenk, the creator of the ISI software, the calibration equations with the correlation coefficient, $R^2$, between reference data and NIRS predicted results of above 0.90 is excellent and between 0.70 to 0.89 is a good quantifying guideline. The excellent calibration equations for DM ($R^2$= 0.99), fat (0.98) and CP (0.92) and a good quantifying guideline equation for ash (0.80) were developed in this study. The results of cross validation statistics for carcass descriptors, body composition using reference methods, inter-correlation between carcass descriptors and NIRS calibration, and the results of discrimination analysis for sex and strain identification will also be presented in the poster. The NIRS predicted daily gain and calculated daily gain from this experiment, and true daily gain (using data from another experiment with closely related broiler chicken from each of the six strains) will also be discussed in the paper.
Pena, Francisco;Gallardo, Natalia;Campillo, Carmen Del;Garrido, Ana;Cabanas, Victor Fernandez;Delgado, Antonio
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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2001.06a
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pp.1615-1615
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2001
During the past ten years, Near Infrared Spectroscopy has been successfully applied to the analysis of a great variety of agriculture products. Previous works (Morra et al., 1991; Salgo et al., 1998) have shown the potential of this technology for soil analysis, estimating different parameters just with one single scan. The main advantages of NIR applications in soils are the speed of response, allowing the increase of the number of samples analysed to define a particular soil, and the instantaneous elaboration of recommendations for fertilization and soil amendment. Another advantage is to avoid the use of chemical reagents at all, being an environmentally safe technique. In this paper, we have studied a set of 129 soil samples selected from representative glasshouse soils from Southern Spain. The samples were dried, milled, and sieved to pass a 2 mm sieve and then analysed for organic carbon, total nitrogen, inorganic nitrogen (nitrate ammonium), hygroscopic humidity, pH and electrical conductivity in the 1:1 extract. NIR spectra of all samples were obtained in reflectance mode using a Foss NIR Systems 6500 spectrophotometer equipped with a spinning module. Calibration equations were developed for seven analytical parameters (ph, Total nitrogen, organic nitrogen, organic carbon, C/N ratio and Electric Conductivity). Preliminary results show good correlation coefficients and standard errors of cross validation in equations obtained for Organic Carbon, Organic Nitrogen, Total Nitrogen and C/N ratio. Calibrations for nitrates and nitrites, ammonia and electric conductivity were not acceptable. Calibration obtained for pH had an acceptable SECV, but the determination coefficient was found very poor probably due to the reduced range in reference values. Since the estimation of Organic Carbon and C/N ratio are acceptable NIIRS could be used as a fast method to assess the necessity of organic amendments in soils from Mediterranean regions where the low level of organic matter in soils constitutes an important agronomic problem. Furthermore, the possibility of a single and fast estimation of Total Nitrogen (tedious determination by modifications of the Kjeldahl procedure) could provide and interesting data to use in the estimation of nitrogen fertilizer rates by means of nitrogen balances.
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