Near-infrared reflectance spectroscopy as a fast and non-destructive tool to predict foliar organic constituents of several woody species

Near-infrared reflectance spectroscopy (NIRS) was used to estimate N, neutral detergent fibre (NDF), acid detergent fibre (ADF), lignin and cellulose contents in leaves of a heterogeneous group of 17 woody species from the Central Western region of the Iberian Peninsula. The sample set consisted of 182 samples of leaves of deciduous and evergreen species, showing a wide range of concentrations determined by reference methods: 6.60–35.2 g kg⁻¹ (N), 15.5–66.0% (NDF), 10.2–57.3% (ADF), 3.45–27.4% (lignin) and 5.79–31.3% (cellulose). Reflectance spectra, obtained for samples of dried and ground leaves, were recorded as log1/R (R=reflectance) from 1,100 to 2,500 nm. NIRS calibrations were developed using multiple linear (MLR) and partial least-squares (PLSR) regressions, and tested by external validation. Spectral data were transformed to the first and second derivative (1D, 2D). The PLSR method and derivative transformations provided the best statistics and showed lower standard errors of calibration (SEC) and higher coefficients of multiple determination (R ²). In the external validation the standard errors of prediction (SEP) were 0.76 g kg⁻¹ (N), 2.11% (NDF), 1.47% (ADF), 0.85% (lignin) and 0.86% (cellulose). The results obtained show that NIRS is very effective for the estimation of these organic constituents in leaf tissue of woody species. This technique can be used in ecological or ecophysiological studies as an alternative to the more time-consuming standard methods.     

Evaluation of two procedures to determine acid and neutral detergent fibers in ruminant feeds of the temperate region of Argentina

The objective of this work was to compare the traditional Van Soest's procedure to analyze neutral detergent fibers (NDF) and acid detergent fibers (ADF) using filtering crucibles (VS) with a semiautomatic method which uses filter bags in an ANKOM Technology Corp. instrument (ANK). Nine ruminant feeds widely used in the temperate region of Argentina were analyzed: soybean meal expeller, alfalfa, pasture silage, ryegrass, corn silage, weeping lovegrass, tall wheatgrass, guinea grass, and barley grass. Four runs were done for each technique and feed. The comparison of ADF and NDF means by the means test for paired samples showed no significant differences between techniques (alpha = 0.01). The variability among runs was greater with the VS method than the ANK, both for NDF, standard deviation (SD) = 0.71 vs 0.39, and for ADF, SD = 0.83 vs 0.56, but the differences were not significant. The linear regressions were VS = 1.43 + 0.95 ANK; R2 = 0.99, and VS = 0.53 + 0.98 ANK; R2 = 0.99 for NDF and ADF, respectively, which indicated a strong linear relationship among the results of both procedures. It was concluded that the ANK procedure gave results comparable to those of the VS method when ruminant feeds from the temperate region of Argentina were analyzed.     

应用近红外透射光谱法测定稻米淀粉消减值的研究

以183份稻米为样品,利用近红外透射光谱分析仪,对样品进行光谱扫描,并用快速黏度分析仪测定黏滞特性值消减值.采用多种计量数学处理方法和不同的回归统计方法进行定标曲线的开发和比较,得到了稻米消减值测定的近红外分析数学模型,数学模型的定标标准偏差(SEC)、交叉检验标准误差(SECV)和定标决定系数(RSQ)分别为:18.69,19.08和O.949 7.相关性达极显著水平,内部交叉验证和外部验证结果表明近红外定量分析消减值有很高的准确度.该研究利用近红外透射光谱技术为快速准确无损测定黏滞特性指标提供了一条新途径.     

Correlating detergent fiber analysis and dietary fiber analysis data for corn stover collected by NIRS

There exist large amounts of detergent fiber analysis data [neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL)] for many different potential cellulosic ethanol feedstocks, since these techniques are widely used for the analysis of forages. Researchers working in the area of cellulosic ethanol are interested in the structural carbohydrates in a feedstock (principally glucan and xylan), which are typically determined by acid hydrolysis of the structural fraction after multiple extractions of the biomass. These so-called dietary fiber analysis methods are significantly more involved than detergent fiber analysis methods. The purpose of this study was to determine whether it is feasible to correlate detergent fiber analysis values to glucan and xylan content determined by dietary fiber analysis methods for corn stover. In the detergent fiber analysis literature cellulose is often estimated as the difference between ADF and ADL, while hemicellulose is often estimated as the difference between NDF and ADF. Examination of a corn stover dataset containing both detergent fiber analysis data and dietary fiber analysis data predicted using near infrared spectroscopy shows that correlations between structural glucan measured using dietary fiber techniques and cellulose estimated using detergent techniques, and between structural xylan measured using dietary fiber techniques and hemicellulose estimated using detergent techniques are high, but are driven largely by the underlying correlation between total extractives measured by fiber analysis and NDF/ADF. That is, detergent analysis data is correlated to dietary fiber analysis data for structural carbohydrates, but only indirectly; the main correlation is between detergent analysis data and solvent extraction data produced during the dietary fiber analysis procedure.     

Effect of urea and urea–gamma treatments on cellulose degradation of Thai rice straw and corn stalk

Cellulose degradation of 20% urea treated and 20% urea–10 kGy gamma treated Thai rice straw and corn stalk showed that combination effect of urea and gamma radiation gave a higher % decrease in neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), cellulose, hemicellulose, and lignin and cutin in comparison with urea effect only for both room temperature storage and room temperature +258 K storage. The results also indicated that cellulose degradation proceeded with time, even at 258 K. A drastic drop to less than half of the original contents in NDF, ADF, and ADL could not be obtained in this study.     

Sucrose as chiral selector for determining enantiomeric composition of phenylalanine by UV-vis spectroscopy and chemometrics

The determination of enantiomeric composition by partial least squares(PLS) modeling of UV-vis spectral data was investigated for samples of phenylalanine(phe) using sucrose as a chiral auxiliary.And a new data preprocess method,reference band normalization,was introduced to eliminate the spectral variations due to the changes of total concentration of phe.The determination coefficient(R~2) and the standard error of calibration set(SEC) of 13 standard samples are 0.9987 and 0.0128 respectively.The standard error of validation set(SECV) of 7 validation samples is 0.0049.The standard error of predict(SEP) of 6 blind samples for evaluating the robustness of the model is 0.0366.The regression model is robust to determine enantiomeric composition when total concentration varied.It is demonstrated that the reference band normalization is a convenient method of compensating for variations in total concentrations without knowing that in advance.     

Effects of gamma irradiation on cell-wall constituents of some agricultural residues

The effects of 150 kilogray (kGy) of γ irradiation on cell-wall constituents of cottonwood (CW), lentils straw (LS), apple pruning products (AP) and olive cake (OC) were investigated. Samples were irradiated by γ irradiation at a dose level of 150 kGy under identical conditions of temperature and humidity and analyzed for crude fibre (CF), neutral-detergent fibre (NDF), acid detergent fibre (ADF) and acid-detergent lignin (ADL). The results indicate that γ irradiation decreased CF contents by about 29% for CW, LS and AP and by 17% for OC. NDF values were also decreased by about 4% for CW and OC, and by about 12% for LS and AP. γ Irradiation treatment also decreased ADF values only for CW by 8%. ADL contents decreased by 8% for CW and 5% for OC with no effects for LS and AP. The percentage of cellulose (CL): CF ratio increased by 30, 34, 38 and 20% for CW, LS, AP and OC, respectively. Also, the percentage of hemicellulose (HCL): CF increased by 57% for CW and 16% for OC and decreased by 7% for LS and AP. The percentage of HCL: ADL increased by 22% for CW but decreased by 33% for LS and AP with no changes for OC. There were no changes in CL: ADL ratio for all residues.     

Screening Inorganic Arsenic in Rice by Visible and Near-Infrared Spectroscopy

The potential of near-infrared spectroscopy (NIRS) for screening the inorganic arsenic (i-As) content in commercial rice was assessed. Forty samples of rice were freeze-dried and scanned by NIRS. The i-As contents of the samples were obtained by acid digestion-solvent extraction followed by hydride generation atomic absorption spectrometry, and were regressed against different spectral transformations by modified partial least square (MPLS) regression. The second derivative transformation equation of the raw optical data, previously standardized by applying standard normal variate (SNV) and De-trending (DT) algorithms, resulted in a coefficient of determination in the cross-validation (1-VR) of 0.65, indicative of equations useful for correct separation of the samples in low, medium and high groups. The standard deviation (SD) to standard error of cross-validation (SECV) ratio, expressed in the second derivative equation, was similar to those obtained for other trace metal calibrations reported in NIRS reflectance. Spectral information relating to starch, lipids and fiber in the rice grain, and also pigments in the caryopsis, were the main components used by MPLS for modeling the selected prediction equation. This pioneering use of NIRS to predict the i-As content in rice represents an important reduction in labor input and cost of analysis.     

Noncontact analysis of the fiber weight per unit area in prepreg by near-infrared spectroscopy

The fiber weight per unit area in prepreg is an important factor to ensure the quality of the composite products. Near-infrared spectroscopy (NIRS) technology together with a noncontact reflectance sources has been applied for quality analysis of the fiber weight per unit area. The range of the unit area fiber weight was 13.39–14.14 mg cm⁻². The regression method was employed by partial least squares (PLS) and principal components regression (PCR). The calibration model was developed by 55 samples to determine the fiber weight per unit area in prepreg. The determination coefficient (R²), root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were 0.82, 0.092, 0.099, respectively. The predicted values of the fiber weight per unit area in prepreg measured by NIRS technology were comparable to the values obtained by the reference method. For this technology, the noncontact reflectance sources focused directly on the sample with neither previous treatment nor manipulation. The results of the paired t-test revealed that there was no significant difference between the NIR method and the reference method. Besides, the prepreg could be analyzed one time within 20 s without sample destruction.     

Rapid Simultaneous Determination of Andrographolides in Andrographis paniculata by Near-Infrared Spectroscopy

The potential of near-infrared spectroscopy (NIRS) for the quality control of traditional Chinese medicine has been evaluated. Seven quantitative parameters, andrographolide, deoxyandrographolide, dehydroandrographolide, neoandrographolide, moisture, ash content, and alcohol-soluble extract of Andrographis paniculata, were evaluated by NIRS. The reference values of andrographolides were determined by high-performance liquid chromatography, and the others were obtained using the standard methods of the 2015 Chinese Pharmacopoeia. The predicted values were determined by a quantitative model using NIRS based on partial least square regression. Different spectral preprocessing methods, spectral ranges, and optimum number of factors were selected to optimize the models. All models were estimated by the combination of various parameters, including the correlation coefficient of calibration for andrographolide, deoxyandrographolide, dehydroandrographolide, neoandrographolide, moisture, ash content, alcohol-soluble extract (values of 0.980, 0.984, 0.989, 0.983, 0.987, 0.988, 0.979, respectively), root mean square error of calibration (values of 0.156, 0.038, 0.050, 0.029, 0.604, 0.431, 0.135, respectively), root mean square error of prediction (values of 0.169, 0.041, 0.050, 0.033, 0.280, 0.493, 0.140, respectively), root mean square error of cross-validation (values of 0.626, 0.114, 0.158, 0.046, 1.145, 0.774, 0.508, respectively), and ratio of standard deviation to standard error of prediction (values of 4.583, 4.690, 4.796, 4.899, 4.899, 4.690, 5.099, respectively). The results show that the calibration models by NIRS are reliable and can be applied for the quantification for seven parameters from A. paniculata for quality control in traditional Chinese medicine production and processing.     

A feasibility study on the use of visible and short wavelengths in the near-infrared region for the non-destructive measurement of wine composition

The aim of this study was to explore the capability of spectroscopy in the visible (Vis) and short wavelength near-infrared (NIR) regions for the non-destructive measurement of wine composition in intact bottles. In this study we analysed a wide range of commercial wines obtained in Australia in different types of bottles (e.g. colours, diameters and heights), including different wine styles and varieties. Wine bottles were scanned in the Vis-NIR region (600–1,100 nm) in a monochromator instrument in transflectance mode. Principal component analysis (PCA) and partial least-squares (PLS) regression were used to interpret the spectra and develop calibrations for wine composition. Due to the relatively small number of samples available full cross-validation (leave-one-out) was used as validation. The coefficient of correlation in calibration and the standard error of cross-validation (SECV) were 0.67 (SECV: 0.48%), 0.83 (SECV: 4.01 mg L⁻¹), 0.70 (SECV: 28.6 mg L⁻¹) and 0.50 (SECV: 0.15) for alcohol content, total SO₂, free SO₂ and pH, respectively, in the set of wine samples analysed. These preliminary results showed that the assessment of wine composition by Vis and short wavelengths in the NIR is possible for either qualitative analysis (e.g. low-, medium- and high-quality grading), or for screening of composition during bottling and storage. Although low accuracy and precision were obtained for the chemical parameters routinely analysed in wine, calibration models for the chemical parameters were considered acceptable for screening purposes in terms of the standard errors obtained.     

Analysis of elements in wine using near infrared spectroscopy and partial least squares regression

The use of visible (VIS) and near infrared spectroscopy (NIRS) to measure the concentration of elements in Australian wines was investigated. Both white (n=32) and red (n=94) wine samples representing a wide range of varieties and regions were analysed by inductively coupled plasma mass spectrometry (ICP-MS) for the concentrations of calcium (Ca), potassium (K), magnesium (Mg), phosphorus (P), sodium (Na), sulphur (S), iron (Fe), boron (B) and manganese (Mn). Samples were scanned in transmittance mode (1mm path length) in a monochromator instrument (400-2500nm). The spectra were pre-treated by second derivative and standard normal variate (SNV) prior to developing calibration models using partial least squares (PLS) regression method with cross-validation. The highest coefficients of determination in cross-validation (R(val)(2)) and the lowest errors of cross-validation (SECV) were obtained for Ca (0.90 and 9.80mgL(-1)), Fe (0.86 and 0.65mgL(-1)) and for K (0.89 and 147.6mgL(-1)). Intermediate R(val)(2) (<0.80) and SECV were obtained for the other minerals analysed. The results showed that some macro- and microelements present in wine might be measured by VIS-NIRS spectroscopy.     

Application of attenuated total reflectance Fourier transform infrared spectrometry to the determination of sodium percarbonate in washing powder detergent

In this paper, a novel and precise analytical procedure has been developed for quantitative determination of sodium percarbonate (SPC) in washing powder. The method is based on the partial least squares (PLS) treatment of data obtained by attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectrometry in wavenumber region of 1435-1342 cm⁻¹. The statistical parameters such as R², RSD, SEC and SECV have been evaluated, and number of factors, number of scan and the resolution have been optimized. In this method R² and RSD for five independent analyses of a 0.552 g per 100 g solution of SPC, SEC for 10 standard samples and SECV for five validation samples were 0.998, 1.011, 0.002 and 0.039 respectively.Results obtained for six different commercial washing powders compared well with those obtained with a standard method.     

Measurement of lactate in whole human blood with near-infrared transmission spectroscopy

We have evaluated the potential of near-infrared spectroscopy (NIRS) as a technique for rapid analysis of lactate in whole blood. To test the NIRS technique, a comparison was made with a standard clinical method using whole blood samples taken from five exercising human subjects at three different stage of exercise. To expand lactate concentration within the physiological range, standard additions method was used to generate 45 unique data points. Spectra were collected over the 2050-2400 nm spectral range with a 1 mm optical path length quartz cell. Reference lactate concentrations in the samples were determined by enzymatic measurements. Estimates and calibration of the lactate concentration with NIRS was made using partial least squares (PLS) regression analysis and leave-N-out cross validation on second derivative spectra. Separate calibrations were determined from each of the subject samples and cumulative PRESS was used to determine the number of PLS factors in the final model. The results from the PLS model presented are generated from the five individual calibration coefficient vectors and provided a correlation coefficient of 0.978 and a standard error of cross validation of 0.65 mmol l⁻¹ between the enzymatic assay and the NIRS technique. To study the parameters that impact the spectra baseline and the correlation between the calculated model and the data, referenced measurements of lactate against baseline spectrum were made for each individual. A correlation coefficient of 0.992 and a standard error of cross validation of 0.21 mmol l⁻¹ were found. The results suggest that NIRS may provide a valuable tool to assess physiological status for both research and clinical needs.     

Gravimetric determination of amylase-treated neutral detergent fiber in feeds with refluxing in beakers or crucibles: collaborative study

As an important constituent of animal feeds, fiber represents the portion of feeds that is bulky and difficult to digest. The neutral detergent fiber (NDF) method, developed over 30 years ago, is the method of choice for measuring total fiber in forages and other feeds. Several modifications that were made to improve its general applicability to all feeds and others developed in individual laboratories often resulted in variability among laboratories in measuring NDF. The amylase-treated NDF (aNDF) method, therefore, was developed as an accurate and precise method of measuring total insoluble fiber in feeds. A collaborative study was conducted to evaluate the repeatability and reproducibility of the aNDF method over the full range of animal feed materials. Twelve laboratories representing research, feed company, regulatory, and commercial feed testing laboratories analyzed 11 materials as blind duplicates. The materials represented feed matrixes, including animal products; high-protein, high-fat, and high-pectin feeds; oil seeds; grains; heated by-product feeds; and legume and grass hays and silages. Materials selected varied in chemical composition and contained 0-90% aNDF, 1-16% ash, 1-20% crude fat, 1-40% crude protein, and 0-50% starch. Correcting results for changes in blanks and reporting results as ash-free aNDF organic matter (aNDFom) improved the repeatability and reproducibility of results when aNDF was <25%. The within-laboratory repeatability standard deviation (Sr) for percentage aNDFom in feeds varied from 0.21 to 1.82 and among-laboratory reproducibility standard deviation (S(R)) varied from 0.37 to 2.24. The HORRAT was <2 for all materials except feed materials containing >10% fat. However, standard deviations of repeatability and reproducibility for feeds with >10% fat were similar to those of other materials. It is recommended that the aNDF method be accepted for Official First Action status.     

近红外光谱快速分析青贮饲料pH值和发酵产物

采用近红外光谱技术,结合偏最小二乘回归法,研究了142个不同种类的秸秆青贮饲料样品的pH值和发酵产物(乳酸、乙酸、丙酸、丁酸和氨态氮),建立了干燥粉碎和新鲜样品的近红外漫反射光谱定量分析模型以及浸提液样品的近红外透射光谱定量分析模型。研究发现,pH值的近红外漫反射光谱和透射光谱的分析效果均较好,校正模型决定系数R2和验证集样品预测值与化学值的相关关系决定系数r2都大于0.80,并且干燥粉碎、新鲜和浸提液样品的RPD值分别为3.44、2.50和2.27;3种状态样品的乳酸、乙酸、丁酸和氨态氮的定量分析模型精度需进一步提高;R2在0.64~0.85之间;RPD值在1.38~1.93之间;丙酸含量的测定结果较差。方差分析显示,3种状态样品的测定结果之间均无显著性差异(P>0.05)。     

Determination of moisture, starch, protein, and fat in common beans (Phaseolus vulgaris L.) by near infrared spectroscopy

The presence of moisture, starch, protein, and fat was determined in common beans (Phaseolus vulgaris L.) by near infrared (NIR) spectroscopy without any previous sample pretreatment except grinding. A set of 96 samples was used to calibrate the instrument by modified partial least-squares regression. The following statistical results were achieved: standard error of calibration (SEC) = 0.31 and square correlation coefficient (R2) = 0.96 for moisture; SEC = 0.76 and R2 = 0.92 for starch; SEC = 0.39 and R2 = 0.98 for protein; and SEC = 0.14 and R2 = 0.80 for fat. To validate the calibration, a set of 25 bean samples was used. Standard errors of prediction were 0.39, 0.90, 0.56, and 0.13 for moisture, starch, protein, and fat, respectively, and R2 for the regression of measurements by the reference method versus NIR analysis were 0.94, 0.88, 0.94, and 0.74 for moisture, starch, protein, and fat, respectively. To compare the results obtained for all 4 components of the validation set by NIR spectroscopy with those obtained by the reference methods, linear regression and paired t tests were applied, and the methods did not give significantly different results, P = 0.05.     

基于正交信号校正的秸秆青贮饲料粗蛋白近红外分析模型传递方法

探讨了基于不同数据预处理方法的正交信号校正在秸杆饲料近红外光谱模型传递中的应用.以141个秸杆青贮饲料样品为研究对象,以其粗蛋白含量为目标参数,研究了基于无处理、局部中心化、全局中心化和Z-score标准化预处理方法的正交信号校正,在源仪器(SPECTRUM ONE NTS)和目标仪器1(ANTA-RIS)与目标仪器2(FOSS 6500)之间的模型传递效果.实验表明:对于两台傅里叶变换型近红外光谱仪,采用局部中心化、全局中心化和Z-score标准化预处理方法的正交信号校正均可成功实现模型传递,其中局部中心化和全局中心化法的作用效果基本一致,且优于Z-score标准化法.对于傅立叶变换和光栅型近红外光谱仪,全局中心化的作用效果明显优于其它3组处理效果,且只有全局中心化预处理的正交信号校正传递后的模型可用于实际预测.     

Near-infrared spectroscopy quantitative determination of Pefloxacin mesylate concentration in pharmaceuticals by using partial least squares and principal component regression multivariate calibration

Pefloxacin mesylate, a broad-spectrum antibacterial fluoroquinolone, has been widely used in clinical practice. Therefore, it is very important to detect the concentration of Pefloxacin mesylate. In this research, the near-infrared spectroscopy (NIRS) has been applied to quantitatively analyze on 108 injection samples, which was divided into a calibration set containing 89 samples and a prediction set containing 19 samples randomly. In order to get a satisfying result, partial least square (PLS) regression and principal components regression (PCR) have been utilized to establish quantitative models. Also, the process of establishing the models, parameters of the models, and prediction results were discussed in detail. In the PLS regression, the values of the coefficient of determination (R²) and root mean square error of cross-validation (RMSECV) of PLS regression are 0.9263 and 0.00119, respectively. For comparison, though applying PCR method to get the values of R² and RMSECV we obtained are 0.9685 and 0.00108, respectively. And the values of the standard error of prediction set (SEP) of PLS and PCR models are 0.001480 and 0.001140. The result of the prediction set suggests that these two quantitative analysis models have excellent generalization ability and prediction precision. However, for this PFLX injection samples, the PCR quantitative analysis model achieved more accurate results than the PLS model. The experimental results showed that NIRS together with PCR method provide rapid and accurate quantitative analysis of PFLX injection samples. Moreover, this study supplied technical support for the further analysis of other injection samples in pharmaceuticals.     

Radiation pasteurised oil palm empty fruit bunch fermented with Pleurotus sajor-caju as feed supplement to ruminants

In solid state fermentation, Pleurotus sajor-caju has been found to be able to degrade at least 30% oil palm empty Fruit Bunch (EFB) fibre leaving 70 % useful materials. Conditions under which fermentation carried out were investigated. It was found that, in the temperature range between 25– 28 °C, relative ph between 6–8, moisture between 60–70 % and medium composition of CaCO₃: rice bran 2 %: 5 % were the optimum conditions. The results showed in fermented products that, there were substantial reduction in cellulosic component such as Crude Fiber (CF, 18 %); Acid Detergent Fibre (ADF, 45 %), Neutral Detergent Fibre (NDF, 61 %) and Acid Detergent Lignin (ADL, 14 %). However, Crude Protein (CP, 10%) increased resulted from single cell protein enrichment of mycelial microbial mass. The mass reductions of substrate in fermentation process corresponds to the CO₂ released during fermentation. Hence, attributable to the decreased in content of CF, ADF, NDF, and ADL. The digestibility study has also been carried out to determine the useful level of this product to ruminant. Aflatoxin content was detected low in both the initial substrates and products. Based on nutritional value and low content of aflatoxin, the product is useful as a source of roughage to ruminant.