Exploring the use of near infrared reflectance spectroscopy to predict minerals in straw

The use of near infrared reflectance spectroscopy (NIRS) to predict minerals concentration (K, Na, Ca, Mg, Fe) in straw samples was investigated in this study. A total of 222 straw samples were collected in rural area of most provinces in China. Two types of straw samples were prepared, directly cut specimens and oven-dried, milled specimens. The spectra of two kinds of samples were employed to correlate with minerals concentration. Different spectral pre-treatments and regression methods were trialled to optimize the calibration. Coefficient of determination in prediction and standard error of prediction (SEP) were 0.69, 0.54, 0.73, 0.79, 0.41 and 3.77 mg g⁻¹, 0.69 mg g⁻¹, 0.58 mg g⁻¹, 0.31 mg g⁻¹, 0.11 mg g⁻¹ for directly cut straw; 0.85, 0.70, 0.82, 0.85, 0.63 and 2.35 mg g⁻¹, 1.46 mg g⁻¹, 0.47 mg g⁻¹, 0.27 mg g⁻¹, 0.13 mg g⁻¹ for dried milled samples, respectively.     

The use of near infrared reflectance spectroscopy in the control of flour protein content

Near infrared reflectance spectroscopy (NIR) is a rapid (50s) and non-destructive method of analysis of a wide variety of solid, semi-solid and liquid samples. Since no sample preparation is required for many sample types, particularly powders, NIR is an ideal technique for process control. The use of NIR to monitor the protein content of flour in order to optimise the milling conditions and the composition of the grist is described. Control of the blending of flours or supplementation with wheat gluten to achieve a composite flour of a given protein content is proposed.     

Estimating the content of free fatty acids in high‐oleic sunflower seeds by near‐infrared spectroscopy

The content of free fatty acids (FFA) in vegetable oils represents an important quality factor in oil crops. The objective of the investigation was to develop a near‐infrared (NIR) calibration for estimating the FFA content in high‐oleic sunflower seeds. A sample set of different varieties from the harvest of 2004 as well as of 2005 from two locations in Germany was used; additionally seeds from 2003 were stored under unsuitable conditions to obtain samples utilised for calibration with an extended FFA range. A direct titration method for FFA determination was developed and adjusted to the official AOCS method. The modified method is sufficiently reliable, much faster than the AOCS method and therefore suitable for use in the calibration of NIR spectrometers. The developed NIR spectroscopy (NIRS) calibration was calculated with a modified partial least square algorithm, standard normal variate and detrend scatter correction and the 2^nd derivative of the spectra of ground sunflower seeds. The standard error of prediction of the validated calibration was 0.20, and the multiple coefficient of determination (RSQ_val) reached 0.94. The obtained results demonstrated clearly the efficiency and how cost effective the NIRS method is for the estimation of FFA content in sunflower seeds.     

Gasoline classification by source and type based on near infrared (NIR) spectroscopy data

In this paper, we have tried to classify 382 samples of gasoline and gasoline fractions by source (refinery or process) and type. Three sets of near infrared (NIR) spectra (450, 415, and 345 spectra) were used for classification of gasolines into 3 or 6 classes. We have compared the abilities of three different classification methods: linear discriminant analysis (LDA), soft independent modeling of class analogy (SIMCA), and multilayer perceptron (MLP) - to build effective and robust classification model. In all cases NIR spectroscopy was found to be effective for gasoline classification purposes. MLP technique was found to be the most effective method of classification model building.     

Determination of free fatty acids in palm oil by near-infrared reflectance spectroscopy

A near-infrared (NIR) spectroscopy calibration was developed for the determination of free fatty acids (FFA) in crude palm oil and its fractions based on the NIR reflectance approach. A range of FFA concentrations was prepared by hydrolyzing oil with 0.15% (w/w) lipase in an incubator at 60°C (200 rpm). Sample preparation was performed in Dutch cup, and the spectra were measured in duplicate for each sample. The optimized calibration models were constructed with multiple linear regression analysis based on C=O overtone regions from 1850–2050 nm. The best wavelength combinations were 1882, 2010, and 2040 nm. Multiple correlation coefficients squared (R ²) were: 0.994 for crude palm oil, 0.961 for refined-bleached-deodorized (RBD) palm olein, and 0.971 for RBD palm oil. Calibrations were validated with an independent set of 8–10 samples. R ² of validation were 0.997, 0.943, and 0.945, respectively. The developed method was rapid, with a total analysis time of 5 min, and environmentally friendly, and its accuracy was generally good for raw-material quality control.     

Motor oil classification by base stock and viscosity based on near infrared (NIR) spectroscopy data

In this paper we have tried to build effective model for classification of motor oils by base stock and viscosity class. Three (3) sets of near infrared (NIR) spectra (1125, 1010, and 1050 spectra) were used for classification of motor oils into 3 or 4 classes according to their base stock (synthetic, semi-synthetic, and mineral), kinematic viscosity at low temperature (SAE 0W, 5W, 10W, and 15W) and kinematic viscosity at high temperature (SAE 20, 30, 40, and 50). The abilities of three (3) different classification methods: regularized discriminant analysis (RDA), soft independent modelling of class analogy (SIMCA), and multilayer perceptron (MLP) - were also compared. In all cases NIR spectroscopy was found to be quite effective for motor oil classification. MLP classification technique was found to be the most effective one.     

Influence of triacylglycerol characterics on the determination of free fatty acids in vegetable oils by fourier transform infrared spectroscopy

A rapid and direct Fourier transform infrared (FTIR) spectroscopic method using a 25-μm NaCl transmission cell was developed for the determination of free fatty acids (FFA) in six important vegetable oils (corn, soybean, sunflower, palm, palm kernel, and coconut oils) that differ in fatty acid profile. The calibrations were established by adding either standard FFA (oleic, lauric acids) or a representative mixture of FFA obtained after saponification of the refined oils. For all oils, up to a FFA level of 6.5% for coconut oil, the best correlation coefficient was obtained by linear regression of the free carboxyl absorption at 1711 cm⁻¹. All correlation coefficients were greater than 0.993, and no significant difference between the calibration methods could be detected. Upon validation of the calibration, no significant difference (α=0.05) between the “actual” and the “FTIR predicted” FFA values could be observed. The calibration models developed for the six oils differed significantly and indicate the need to develop a calibration that is specific for each oil. In terms of repeatability and accuracy, the FTIR method developed was excellent. Because of its simplicity, quick analysis time of less than 2 min, and minimal use of solvents and labor, the introduction of FTIR spectroscopy into laboratory routine for FFA determination should be considered.     

Rapid quantitative determination of free fatty acids in fats and oils by fourier transform infrared spectroscopy

Rapid direct and indirect Fourier transform infrared (FTIR) spectroscopic methods were developed for the determination of free fatty acids (FFA) in fats and oils based on both transmission and attenuated total reflectance approaches, covering an analytical range of 0.2–8% FFA. Calibration curves were prepared by adding oleic acid to the oil chosen for analysis and measuring the C=O band @ 1711 cm^–1 after ratioing the sample spectrum against that of the same oil free of fatty acids. For fats and oils that may have undergone significant thermal stress or extensive oxidation, an indirect method was developed in which 1% KOH/methanol is used to extract the FFAs and convert them to their potassium salts. The carboxylate anion absorbs @ 1570 cm^–1, well away from interfering absorptions of carbonyl-containing oxidation end products that are commonly present in oxidized oils. Both approaches gave results comparable in precision and accuracy to that of the American Oil Chemists’ Society reference titration method. Through macroprogramming, the FFA analysis procedure was completely automated, making it suitable for routine quality control applications. As such, the method requires no knowledge of FTIR spectroscopy on the part of the operator, and an analysis takes less than 2 min.     

Near‐infrared spectroscopy for analysis of oil content and fatty acid profile in almond flour

Almond kernels show large variability for oil content and fatty acid profile. The objective of this research was to evaluate the potential of near infrared (NIR) reflectance spectroscopy (NIRS) for the analysis of these traits in almond flour. Ground kernels of 181 accessions collected in 2009 were used for developing calibration equations for oil content and concentrations of individual fatty acids. Calibration equations were developed using second derivative transformation and modified partial least squares regression. They were validated with samples from 179 accessions collected in 2010. The accuracy of calibration equations was measured through the coefficient of determination (r²) in external validation and the ratio of the SD in the validation set to the standard error of prediction (RPD). Both r² and RPD were high for oil content (r² = 0.99; RPD = 9.24) and concentrations of oleic (r² = 0.97; RPD = 5.37) and linoleic acids (r² = 0.98; RPD = 7.35), revealing that calibration equations for these traits are highly accurate. Conversely, the accuracy of the calibration equations for palmitic (r² = 0.54; RPD = 1.41) and stearic acids (r² = 0.52; RPD = 1.44) was too low for allowing their application in practice. NIRS discrimination of oil content and concentrations of oleic and linoleic acids was mainly based on the spectral region from 2240 to 2380 nm. Practical applications : NIRS is a high‐throughput analytical technique that allows fast measurement of several traits in a single analysis without using chemical reagents. We evaluated the feasibility of analyzing oil content and concentrations of palmitic, stearic, oleic, and linoleic acids in almond flour using fruits collected during 2 years from a world germplasm collection. The fruits collected in 2009 were used for NIRS calibration, whereas the fruits collected in 2010 were used for validation. NIRS equations were highly accurate for measuring oil content and concentrations of oleic and linoleic acids, which are important traits defining the quality of almond flour for specific uses in the food industry. These results have applications both in the research laboratory and the food industry, where NIRS is becoming a widely used technique for quality control.     

The characterization of coal macerals by diffuse reflectance infrared spectroscopy

Diffuse reflectance Fourier transform infrared (DRIFT) spectroscopy was applied to study the structure of vitrinites, liptinites and fusinites isolated from different rank coals (77.0-91.5%C) using a centrifugal float-sink procedure. Among the macerals separated from a given coal, liptinites are characterized by the highest proportion of aliphatic CH groups, occurring principally as CH₂, and fusinites by the most aromatic structure. Macerals separated from the low rank coals show comparable content of hydroxyl groups that occur as free OH or form similar types of hydrogen bonds. Carbonyl groups appear not only as conjugated ketones and quinones in vitrinites, but also as carboxylic groups in liptinites and low rank fusinites. CH_ar/CH_al ratio does not vary with carbon content in liptinites, but increases in vitrinites and fusinites. In the case of liptinites and vitrinites, a linear relationship between CH_ar/CH_al and reflectance is observed up to vitrinite R₀ value of 1.80%. For all macerals, the ratio CH_ar/CC increases with reflectance, but at different rates. Structural parameters CH_ar/CH_al and CH_ar/CC calculated from DRIFT spectra are very helpful in monitoring the differences among macerals of given coal and following structural rearrangement occurring with rank.     

Determination of the fatty acid composition of the oil in intact-seed mustard by near-infrared reflectance spectroscopy

Near-infrared reflectance spectroscopy (NIRS) was used to estimate the fatty acid composition of the oil in intact-seed samples of Ethiopian mustard (Brassica carinata Braun) within a mutation breeding program that produced seeds with variable fatty acid compositions. Five populations, from 1992 to 1996 crops, were included in this study; and NIRS calibration equations for major fatty acids (palmitic, stearic, oleic, linoleic, linolenic, eicosenoic, and erucic) were developed within each single population. Furthermore, global calibration equations, including samples from the five populations, were developed. After external validation, the NIRS technique permitted us to obtain a reliable and accurate nondestructive estimation of the fatty acid composition of the oil, especially for the major acids—oleic, linoleic, linolenic, and erucic. For these, the r ² in external validation was higher than 0.95 by using both single-and multipopulation equations, and higher than 0.85 for the remaining fatty acids. Moreover, the multipopulation equations provided an accurate estimation of samples from a population not represented in the calibration data set, with values of coefficient of determination in validation (r ²) from 0.80 (palmitic and eicosenoic acids) to 0.97 (erucic acid). The ability of NIRS to discriminate among different fatty acid profiles was mainly due to changes within six spectral regions, 1140–1240, 1350–1400, 1650–1800, 1880–1920, 2140–2200, and 2240–2380 nm, all of them associated with fatty acid absorbers. Thus, NIRS can be used to estimate the fatty acid composition of Ethiopian mustard seeds with a high degree of accuracy, provided that calibration equations be developed from calibration sets that include large variability for the fatty acid composition of the oil.     

Triglyceride composition of ewe,cow, and goat milk fat

The separation and identification of the components in milk fat, which are mainly triglycerides, is a challenge due to its complex composition. A reverse-phase high-performance liquid chromatography (HPLC) method with gradient elution and light-scattering detection is described in this paper for the triglyceride analysis in ewes’ milk fat. Triglyceride identification was carried out by combining HPLC, gas-liquid chromatography (GLC), and the calculated equivalent carbon numbers of several triglyceride standards. Quantitation of partially resolved peaks in the HPLC chromatogram was accomplished by applying a peak deconvolution program. Forty-four fatty acids were identified by GLC analysis, but only 19 were used for the following prediction of triglyceride molecular species; 181 triglycerides were identified, some of which were grouped at the same peak and needed application of the deconvolution program. Consequently, coefficients of variation were close to or lower than 5%. Moreover, the triglyceride composition of ewe, cow, and goat milk fat were compared by using these methods. These results show that ewe milk fat is richer in short- and medium-chain triglycerides, and cow milk fat is richer in long-chain and unsaturated triglycerides.     

反式脂肪酸测定方法的研究

简要介绍了反式脂肪酸(TFA)的生成途径及主要的食物来源,反式脂肪酸对人体健康的主要危害和影响,综述了反式脂肪酸的分析检测方法如气相色谱法、红外光谱法、Ag离子色谱技术、毛细管电泳法等,并比较了各种方法的优缺点。     

Development of calibration equations to predict oil content and fatty acid composition in brassicaceae germplasm by near-infrared reflectance spectroscopy

The use of nondestructive analytical methods is critical for the evaluation of very small seed samples such as those from germplasm collections. The objective of this study was to evaluate the potential of near-infrared reflectance spectroscopy (NIRS) for the simultaneous analysis of seed oil content and concentration of major fatty acids in intact-seed samples of the family Brassicaceae. A total of 495 samples from 56 genera and 128 species were analyzed by NIRS. The fatty acid composition of the seed oil was determined in all the samples by gas-liquid chromatography (GLC). The total seed oil content was determined by solvent extraction in 129 samples from 22 genera. Calibration equations for oil content (n=97) and individual fatty acids (n=410) were developed and tested through external validation with the samples not included in the calibration sets. The calibration equations for oil content (r ²=0.97 in validation) and concentrations of C_18:1 (r ²=0.93), C_18:3 (r ²=0.95), and C_22:1 (r ²=0.94) showed very good performance and provided reliable estimations of these traits in the samples of the validation set. The calibration equations for C_16:0, C_18:0, and C_18:2 content were less reliable, with r ² from 0.67 to 0.73. There was practically no response of NIRS to differences in C_20:1 (r ²=0.31). These results demonstrated that the oil content and concentrations of C_18:1, C_18:3, and C_22:1 can be estimated reliably within the family Brassicaceae by using NIRS calibration equations integrating broad taxonomic variability.     

Measurement of soybean fatty acids by near-infrared spectroscopy: Linear and nonlinear calibration methods

A key element of successful development of new soybean cultivars is availability of inexpensive and rapid methods for measurement of FA in seeds. Published research demonstrated applicability of NIR spectroscopy for FA profiling in oilseeds. The objectives of this study were to investigate the applicability of NIR spectroscopy for measurement of FA in whole soybeans and compare performance of calibration methods. Equations were developed using partial least squares (PLS), artificial neural networks (ANN), and support vector machines (SVM) regression methods. Validation results demonstrated that (i) equations for total saturates had the highest predictive ability (r ²=0.91–0.94) and were usable for quality assurance applications, (ii) palmitic acid models (r ²=0.80–0.84) were usable for certain research applications, and (iii) equations for stearic (r ²=0.49–0.68), oleic (r ²=0.76–0.81), linoleic (r ²=0.73–0.76), and linolenic (r ²=0.67–0.74) acids could be used for sample screening. The SVM models produced significantly more accurate predictions than those developed with PLS. ANN calibrations were not different from the other two methods. Reduction in the number of calibration samples reduced predictive ability of all equations. The rate of performance degradation of SVM models with sample reduction was the lowest.     

Effect of Sn4+ doping on the photoactivity inhibition and near infrared reflectance property of mica-titania pigments for a solar reflective coating

The influence of Sn⁴⁺ doping on the photoactivity inhibition and near infrared reflectance property of mica-titania pigments was investigated. X-ray diffraction analysis confirmed that Sn⁴⁺doping promoted phase transformation from anatase to rutile. The rutile promoting effect of Sn⁴⁺ can be ascribed to the distortion of the crystal structure of anatase after the replacement of Ti⁴⁺ by Sn⁴⁺. Sn⁴⁺ doping had a great influence on the photoactivity of mica-titania pigments. The photoactivity of mica-titania pigments was enhanced at low dopant levels, whereas its photoactivity was inhibited at high dopant levels. Remarkably, the degradation rate constant of mica-titania pigments doped with 1.0 wt% of SnCl₄ was approximately 12.9% of that of the undoped sample. A possible mechanism for this effect was proposed. Moreover, the near-infrared solar reflectance of mica-titania pigments reached 0.97. An approximately 8.3 °C decrease in temperature was obtained for the inner surface of a calcium silicate board coated with mica-titania pigments. Furthermore, a solar reflective coating coloured with low photocatalytic mica-titania pigments exhibited high photostability against weathering conditions. Therefore, mica-titania pigments with high levels of the Sn⁴⁺dopant are excellent candidates for use in solar reflective coatings.     

Determination of totaltrans fatty acids in foods: Comparison of capillary-column gas chromatography and single-bounce horizontal attenuated total reflection infrared spectroscopy

The totaltrans fatty acid content of 18 food products was determined, after acid hydrolysis, extraction and methylation of fatty acids, by gas chromatography with a polar 100% cyanopropylsiloxane capillary column and by single-bounce horizontal attenuated total reflection spectroscopy (SB-HATR). Thetrans fatty acid methyl esters (FAME) of 9-hexadecenoate (9t-16:1), 9-octadecenoate (9t-18:1), and 9,12-octadecadienoate (9t,12t-18:2) were identified by comparison of their retention times with those of known standards and quantitated. The isomersc,t- andt,c-18:2 were identified from their published retention times and included in the quantitation oftrans FAME. Neat 50-μL portions of the FAME that were used for gas-chromatographic analysis also were analyzed by SB-HATR. This technique requires neither weighing nor quantitative dilution of test portions prior to spectroscopic quantitation of isolated double bonds oftrans configuration. A symmetric 966-cm⁻¹ absorption band on a horizontal background was obtained from unhydrogenated soybean oil FAME as the reference material. For 9 of 11 products withtrans fat content>5% of total fat, results obtained by SB-HATR were higher than those obtained by gas chromatography. Results obtained by the gaschromatographic procedure were slightly to significantly higher than those obtained by SB-HATR for the six foods in whichtrans fat content was <5% of total fat.     

Diffuse reflectance Fourier transform infrared spectroscopy of oleic acid adsorption on silicic acid

Diffuse reflectance Fourier transform infrared spectroscopy was used to observe adsorption complexes of oleic acid and isopropanol (IPA) on silicic acid in hexane. The spectra provide definite evidence of the molecular nature of the surface interaction. In addition, the effect on oleic acid adsorption of modifying the solvent with IPA, which competes for adsorption sites and modifies the solvent polarity, was studied. Oleic acid adsorption was reduced in the presence of an equimolar IPA concentration in hexane, relative to that from hexane alone. This could be explained by a combination of competitive adsorption of IPA and IPA interacting with oleic acid in solution. IPA, in solution, and silica are probably competing for the lipid. This is additional evidence that suggests that lipid adsorption onto silicic acid is influenced by competitive adsorption. The adsorption of oleic acid and IPA, from a mixture of the two in hexane, was controlled by (i) the equilibrium between surface-bound species and molecules in solution and (ii) the polar interaction between oleic acid and IPA in solution. Thus, washing pre-bound oleic acid with hexane removed only a small amount of oleic acid, while washing with a solution of IPA in hexane removed most of the pre-bound oleic acid.     

Nondestructive Estimation of Fat Constituents of Sesame (Sesamum indicum L.) Seeds by Near‐Infrared Reflectance Spectroscopy

A rapid and efficient method for oil constituent estimation in intact sesame seeds was developed through near‐infrared reflectance spectroscopy (NIRS) and was used to evaluate a sesame germplasm collection conserved in China. A total of 342 samples were scanned by reflectance NIR in a range of 950–1650 nm, and the reference values for oil content and fatty acid (FA) profiles were measured by Soxhlet and gas chromatograph methods. Useful chemometric models were developed using partial least squares regression with full cross‐validation. The equations had low standard errors of cross‐validation, and high coefficient of determination of cross‐validation (R_c²) values (>0.8) except for stearic acid (0.794). In external validation, r² values of oil and FA composition equations ranged from 0.815 (arachidonic acid) to 0.877 (linoleic acid). The relative predictive determinant (RPD_v) values for all equations were more than 2.0. The whole‐seed NIR spectroscopy equations for oil content and FA profiles can be used for sesame seed quality rapid evaluation. The background information of the 4399 germplasm resources and accessions with high linoleic acid content identified in this study should be useful for developing new sesame cultivars with desirable FA compositions in future breeding programs.     

Determination of trans fatty acids in hydrogenated vegetable oils by attenuated total reflection infrared spectroscopy: Two limited collaborative studies

An attenuated total reflection infrared spectroscopy procedure was collaboratively studied among two sets of five laboratories for quantitating the total trans fatty acid levels in neat (without solvent) hydrogenated vegetable oils, measured as triacylglycerols in one study, and as fatty acid methyl ester derivatives in the other. Unlike the fatty acid methyl esters, the triacylglycerols required no derivatization but had to be melted prior to measurement. To obtain a symmetric absorption band at 966 cm⁻¹ on a horizontal background, the single-beam spectrum of the trans-containing fat was "ratioed" against that of a refined oil or a reference material that contained only cis double bonds. A single-bounce horizontal attenuated total reflection cell that requires 50 μL of undiluted test samples was used for oils, melted fats, or their methyl esters. For fatty acid methyl esters, the reproducibility relative standard deviations were in the range of 0.9 to 18.46% for 39.08 to 3.41% trans, determined as methyl elaidate per total fatty acid methyl esters. For five pairs of triacylglycerol blind duplicates, the reproducibility and repeatability relative standard deviations were in the ranges of 1.62 to 18.97%, and 1.52 to 13.26%, respectively, for 39.12 to 1.95% trans, determined as trielaidin per total triacylglycerols. Six pairs of spiked triacylglycerol blind duplicates (quality assurance standards) exhibited high accuracy in the range of 0.53 to 40.69% trans and averaged a low bias of 1.3%. These statistical analysis results were compared to those collaboratively obtained by the recently adopted AOCS Cd14-95 and AOAC 994.34 Infrared Official Methods.