Determination of inorganic elements in animal feeds by NIRS technology and a fibre-optic probe

In the present work we study the use of near infra-red spectroscopy (NIRS) technology together with a remote reflectance fibre-optic probe for the analysis of the mineral composition of animal feeds. The method allows immediate control of the feeds without prior sample treatment or destruction through direct application of the fibre-optic probe on the sample.The regression method employed was modified partial least squares (MPLS). The calibration results obtained using forty samples of animal feeds allowed the determination of Fe, Mn, Ca, Na, K, P, Zn and Cu, with a standard error of prediction (SEP(C)) and a correlation coefficient (RSQ) of 0.129 and 0.859 for Fe; 0.175 and 0.816 for Mn; 5.470 and 0.927 for Ca; 2.717 and 0.862 for Na; 4.397 and 0.891 for K; 2.226 and 0.881 for P; 0.153 and 0.764 for Zn, and 0.095 and 0.918 for Cu, respectively.The robustness of the method was checked by applying it to 10 animal feeds samples of unknown mineral composition in the external validation.     

Near-infrared spectroscopy (NIRS) reflectance technology for the determination of tocopherols in alfalfa

The vitamin E (α- and (β+γ)-tocopherol) contents present in alfalfa (fresh or dehydrated) were analysed using near-infrared spectroscopy (NIRS) technology together with a remote reflectance fibre-optic probe. The range of vitamin E was 0.55–5.16 mg/100 g for α-tocopherol and 0.07–0.48 for (β+γ)-tocopherol. The regression method employed was modified partial least squares (MPLS). The equations developed using the fibre-optic probe for 69 samples of alfalfa (dehydrated and fresh) to determine the content of vitamin E in feeds had multiple correlation coefficients (RSQs) and prediction corrected standard errors (SEP (C)) of 0.946 and 0.321 mg/100 g for α-tocopherol and 0.956 and 0.022 mg/100 g for (β+γ)-tocopherol. The predicted values of vitamin E in feeds using NIRS technology applying the fibre-optic probe directly on the sample with neither previous treatment nor manipulation are comparable to those obtained using the chemical method, which included alkaline hydrolysis and hexane extraction of the vitamin from the unsaponifiable fraction before chromatographic determination.     

Determination of the percentage of milk (cow's, ewe's and goat's) in cheeses with different ripening times using near infrared spectroscopy technology and a remote reflectance fibre-optic probe

In the present work we studied the use of near infrared spectroscopy (NIRS) technology employing a remote reflectance fibre-optic probe (with a 5 cm × 5 cm quartz window) for the analysis of the percentage of milk (cow's, ewe's and goat's) used in the elaboration of cheeses with different ripening times. To do so, cheeses with known and varying percentages of cow's, ewe's and goat's milk were elaborated (112 samples with milk collected in winter and 112 samples with milk collected in summer) and used as reference material, and ripening controls were performed over 6 months. The method allows immediate control of the cheese without prior sample treatment or destruction by direct application of the fibre-optic probe to the sample. The regression method employed was modified partial least squares (MPLS). Of all the samples (224), 200 formed to so-called calibration set and the other 24 were used for external validation. The calibration results obtained using 200 samples of cheese allowed the percentage of cow's, ewe's and goat's milk to be measured. The multiple correlation coefficients (RSQ) and prediction corrected standard errors (SEP(C)) obtained were respectively, 0.834 and 11.6% for cow's milk; 0.871 and 9.8% for goat's milk; 0.880 and 10.6% for ewe's milk. The ratio performance deviation (RPD) values obtained indicate that the NIRS equations can be applied to unknown samples.     

Potential of near infrared spectroscopy for the analysis of mycotoxins applied to naturally contaminated red paprika found in the Spanish market

The potential of the near infrared spectroscopy (NIRS) technique for the analysis of red paprika for aflatoxin B(1), ochratoxin A and total aflatoxins is explored. As a reference, the results from a chromatographic method with fluorescence detection (HPLC-FD) following an immunoaffinity cleanup (IAC) were employed. For the NIRS measurement, a remote reflectance fibre-optic probe was applied directly onto the samples of paprika. There was no need for pre-treatment or manipulation of the sample. The modified partial least squares (MPLS) algorithm was employed as a regression method. The multiple correlation coefficients (RSQ) and the prediction corrected standard errors (SEP(C)) were respectively 0.955 and 0.2 microg kg(-1), 0.853 and 2.3 microg kg(-1), 0.938 and 0.3 microg kg(-1) for aflatoxin B(1), ochratoxin A and total aflatoxins, respectively. The capacity for prediction of the developed model measured as ratio performance deviation (RPD) for aflatoxin B(1) (5.2), ochratoxin A (2.8) and total aflatoxins (4.4) indicate that NIRS technique using a fibre-optic probe offers an alternative for the determination of these three parameters in paprika, with an advantageously lower cost and higher speed as compared with the chemical method. Content of aflatoxin B(1) and total aflatoxins are the parameters currently employed by the food regulations to limit the levels of the four aflatoxins in many foodstuffs. In addition, aflatoxin B(1) itself is an excellent indicator for aflatoxins' contamination since it is always the most abundant and toxic.     

Use of NIRS technology with a remote reflectance fibre-optic probe for predicting major components in cheese

In the present work the potential of near infra-red spectroscopy technology (NIRS) together with the use of a remote reflectance fibre-optic probe for the analysis of fat, moisture, protein and chlorides contents of commercial cheeses elaborated with mixtures of cow's, ewe's and goat's milk and with different curing times was examined. The probe was applied directly, with no previous sample treatment. The regression method employed was modified partial least squares (MPLS). The equations developed for the cheese samples afforded fat, moisture, protein, and chloride contents in the range 13-52%, 10-62%, 20-30%, and 0.7-2.9%, respectively. The multiple correlation coefficients (RSQ) and prediction corrected standard errors (SEP (C)) obtained were respectively 0.97 and 0.995% for fat; 0.96% and 1.640% for moisture; 0.78% and 0.760% for protein, and 0.89% and 0.112% for chlorides.     

Use of NIRS technology with a remote reflectance fibre-optic probe for predicting mineral composition (Ca,K, P,Fe, Mn,Na, Zn), protein and moisture in alfalfa

In the present work we study the use of near-infrared spectroscopy (NIRS) technology together with a remote reflectance fibre-optic probe for the analysis of major (Ca, K, P) and minor (Fe, Mn, Na, Zn) elements, protein and moisture in alfalfa. The method allows immediate analysis of the alfalfa without prior sample treatment or destruction through direct application of the fibre-optic probe on ground samples in the case of the mineral composition and on-ground and compacted (baled) samples in the case of protein and humidity. The regression method employed was modified partial least-squares (MPLS). The calibration results obtained using samples of alfalfa allowed the determination of Ca, K, P, Fe, Mn, Na and Zn, with a standard error of prediction (SEP(C)) and a correlation coefficient (RSQ) expressed in mg/kg of alfalfa of 1.37 × 10³ and 0.878 for Ca, 1.10 × 10³ and 0.899 for K, 227 and 0.909 for P, 103 and 0.948 for Fe, 5.1 and 0.843 for Mn, 86.2 and 0.979 for Na, and of 1.9 and 0.853 for Zn, respectively. The SEP(C) and RSQ values (in %) for protein and moisture in ground samples were 0.548 and 0.871 and 0.150 and 0.981, respectively; while in the compacted samples they were 0.564 and 0.826 and 0.262 and 0.935, respectively. The prediction capacity of the model and the robustness of the method were checked in the external validation in alfalfa samples of unknown composition, and the results confirmed the suitability of the method.     

Detection and quantification of additives (urea, biuret and poultry litter) in alfalfas by NIR spectroscopy with fibre-optic probe

The additives (urea, biuret and poultry litter) present in alfalfa, which contribute non-proteic nitrogen, were analysed using near infrared spectroscopy (NIRS) technology together with a remote reflectance fibre-optic probe. We used 75 samples of known alfalfa without additives and 75 samples with each of the additives, urea (0.01-10%), biuret (0.01-10%) and poultry litter (1-25%). Using the discriminant partial least squares (DPLS) algorithm, the presence or absence of the additives urea, biuret and poultry litter is classified and predicted with a high prediction rate of 96.9%, 100% and 100%, obtaining the equations of discrimination for each additive. The regression method employed for the quantification was modified partial least squares (MPLS). The equations were developed using the fibre-optic probe to determine the content of urea, biuret and poultry litter with multiple correlation coefficients (RSQ) and prediction corrected standard errors (SEP (C)) of 0.990, 0.28% for urea, 0.991, 0.29% for biuret and 0.925, 2.08% for poultry litter. The work permits the instantaneous and simultaneous prediction and determination of urea, biuret and poultry litter in alfalfas, applying the fibre-optic directly on the ground samples of alfalfa.     

HPLC Analysis of Amino Acids with Ion Exchange Chromatography and O-Phthalaldehyde Post-Column Derivatization: Applications to the Assay of Endogenous Free Amino Acids and Their Transport in Human Placental Villus

Abstract

A method using high performance liquid chromatography (HPLC) for the analysis of primary amino acids in human placenta is described. This method involves separation of primary amino acids by high performance ion-exchange chromatography followed by post column derivatization using O-phlthalaldehyde (OPA) and 2-mercaptoethanol and fluorescence (excitation 340 nm and emission 410 nm) detection of derivatives. Waters 840 HPLC Amino Acid System was used for this purpose.

For analysis, villus tissue was extracted with acetonitrile, and the recovered amino acids were reconstituted in a sodium diluent (pH 2.2). The complete profile of the primary amino acids in the sample could be constructed in about 90 minutes. Up to 44 samples can be analyzed without special attention. Using this method, essential amino acids (threonine, valine, methionine, isoleucine, leucine, tyrosine, phenylalanine, lysine, histidine) and nonessential amino acids (aspartic acid, serine, glutamic acid, glycine, alanine, arginine) were detected and quantified in human placental villus in pmol quantities. Plots of peak heights (or areas) were linear for several amino acids. The same method was also used for (a) the assay of free primary amino acids in umbilical bloods, (b) the efflux of amino acids from isolated human placental villus, and (c) to study the uptake of α-aminoisobutyric acid (AIB), a non-metabolizable amino acid, by the isolated placental villus.     

Polyamide Layer Chromatography. Identification of Amino Acids in Angelica acutiloba Kitagawa via DNP Derivative

Eighteen amino acids; proline, alanine, valine, leucine, isoleucine, hydroxyproline, phenylalanine, ornithine, glycine, serine, aspartic acid, glutamic acid, threonine, asparagine, lysine, tyrosine, tryptophan, and arginine were identified by polyamide layer chromatography via DNP (dinitrophenly) derivatives in Angelica acutiloba Kitagawa (Tang-Kwei)     

Use of NIRS technology with a remote reflectance fibre-optic probe for predicting major components in bee pollen

In the present work, we study the use of near infra-red spectroscopy (NIRS) technology together with a remote reflectance fibre-optic probe for determination of the major components in bee pollen. The method allows immediate control of the bee pollen without prior sample treatment or destruction through direct application of the fibre-optic probe to the sample.The regression method employed was modified partial least squares (MPLS). The calibration results obtained using 45 samples of bee pollen allowed the measurement of protein, moisture, ash, reducing sugars, and pH with multiple correlation coefficients (RSQ) and prediction corrected standard errors (SEPC) of 0.91, 0.56% for protein, of 0.78 and 0.49% for moisture; 0.92 and 0.049% for ash; 0.81 and 1.32 g of glucose/100 g of bee pollen; 0.84 and 0.15 for pH, respectively.The prediction capacity of the pattern was checked by applying it to samples of unknown pollen in external validation.     

Quantitative NMR spectroscopy for accurate purity determination of amino acids,and uncertainty evaluation for different signals

Purity evaluation of amino acids using nuclear magnetic resonance spectroscopy is reported. Three amino acids (aspartic acid, valine, and arginine) and certified reference materials (CRMs), such as acidic, neutral, and basic amino acids, as well as a low pure sample of valine were used as the analytes. DCl solution, D₂O, and NaOD solution were used as the preparation solvents. The quantitative values were obtained from all observed signals and compared with the certified values of the CRMs. When an amino acid was dissolved in water, a strong HOD signal due to proton exchange was observed. When the signal adjoining the HOD signal was considered in the evaluation, the accurate quantitative value could not be obtained. Therefore, under optimized conditions, the analyte signals separated from the HOD signal were chosen for purity determination of amino acids. As a result, the quantitative values were in agreement with the certified values of CRMs. An expanded uncertainty was estimated to be approximately 0.002 kg kg^?1. We also discuss the effect of impurities on purity determination based on all signals and conclude that agreement of quantitative values determined from different signals in a molecule is a good indication of the accuracy of the results.     

Analysis of cyclic pyrolysis products formed from amino acid monomer

Amino acid was mixed with silica and tetramethylammonium hydroxide (TMAH) to favor pyrolysis of amino acid monomer. The pyrolysis products formed from amino acid monomer were using GC/MS and GC. 20 amino acids of alanine, arginine, asparagine, aspartic acid, cysteine, glutamic acid, glutamine, glycine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, proline, serine, threonine, tryptophan, tyrosine, and valine were analyzed. The pyrolysis products were divided into cyclic and non-cyclic products. Among the 20 amino acids, arginine, asparagine, glutamic acid, glutamine, histidine, lysine, and phenylalanine generated cyclic pyrolysis products of the monomer. New cyclic pyrolysis products were formed by isolation of amino acid monomers. They commonly had polar side functional groups to 5-, 6-, or 7-membered ring structure. Arginine, asparagine, glutamic acid, glutamine, histidine, and phenylalanine generated only 5- or 6-membered ring products. However, lysine generated both 6- and 7-membered ring compounds. Variations of the relative intensities of the cyclic pyrolysis products with the pyrolysis temperature and amino acid concentration were also investigated.     

Comprehensive Evaluation of Amino Acids and Polyphenols in 69 Varieties of Green Cabbage (Brassica oleracea L. var. capitata L.) Based on Multivariate Statistical Analysis

The biological activities of the primary metabolites and secondary metabolites of 69 green cabbage varieties were tested. The LC-MS detection method was used to determine the content of 19 free amino acids (lysine, tryptophan, phenylalanine, methionine, threonine, isoleucine, leucine, valine, arginine, asparagine, glycine, proline, tyrosine, glutamine, alanine, aspartic acid, serine, and glutamate). The content of 10 polyphenols (chlorogenic acid, gallic acid, 4-coumaric acid, ferulic acid, gentisic acid, cymarin, erucic acid, benzoic acid, rutin, and kaempferol) was determined by the HPLC detection method. Considering the complexity of the data obtained, variance analysis, diversity analysis, correlation analysis, hierarchical cluster analysis (HCA), and principal component analysis (PCA) were used to process and correlate amino acid or polyphenol data, respectively. The results showed that there were significant differences between the different amino acids and polyphenols of the 69 cabbage varieties. The most abundant amino acids and polyphenols were Glu and rutin, respectively. Both amino acids and polyphenols had a high genetic diversity, and multiple groups of significant or extremely significant correlations. The 69 cabbage varieties were divided into two groups, according to 19 amino acid indexes, by PCA. Among them, seven varieties with high amino acid content all fell into the fourth quadrant. The HCA of amino acids also supports this view. Based on 10 polyphenols, the 69 cabbage varieties were divided into two groups by HCA. Based on 29 indexes of amino acids and polyphenols, 69 cabbage varieties were evaluated and ranked by PCA. Therefore, in this study, cabbage varieties were classified in accordance with the level of amino acids and polyphenols, which provided a theoretical basis for the genetic improvement of nutritional quality in cabbage.     

Identification of garlic in old gildings by gas chromatography-mass spectrometry

The proteinaceous content of garlic (Allium sativum) was characterised according to its amino acid composition by using a gas chromatography-mass spectrometry (GC-MS) analytical procedure. The procedure was tested on fresh and aged garlic samples as well as on reference gilding specimens prepared according to old recipes. The proteinaceous pattern showed a characteristic distribution of amino acids with glutamic acid being the major component. The average amino acidic composition was: glutamic acid (Glu; 29%), aspartic acid (Asp; 17%), serine (Ser; 11%), alanine, glycine, valine, leucine, lysine and phenylalanine (Ala, Gly, Val, Leu, Lys and Phe; 5-6%), isoleucine, proline and tyrosine (Ile, Pro and Tyr; 2-3%), methionine and hydroxyproline (Met and Hyp; 0.5%). In order to distinguish this material from animal glue and egg, which are the other proteinaceous media commonly used in gilding techniques, a database of amino acid percentages of the three proteins was built up and submitted to principal component analysis. Three separate clusters were obtained, allowing the protein identification. The application of the procedure on several gilding samples from Italian wall and easel paintings (13th-17th century) permitted to evidence the use of garlic as a gluing agent.     

Effect of some amino acids and peptides on silicic acid polymerization

The polymerization of silicic acid in aqueous solutions at different pH was followed by the colorimetric molybdosilicate method. The role of four amino acids (serine, lysine, proline and aspartic acid) and the corresponding homopeptides was studied. All four amino acids behave the same way and favor the condensation of silicic acid. Peptides exhibit a stronger catalytic effect than amino acids but they appear to behave in very different ways depending on the nature of side-groups and pH. Poly-lysine and poly-proline for instance lead to the precipitation of solid phases containing both silica and peptides. The role of these biomolecules on the polymerization of silicic acid is discussed in terms of electrostatic interactions, hydrogen bonds and solubility.     

Racemic D,L-asparagine causes enantiomeric excess of other coexisting racemic D,L-amino acids during recrystallization: a hypothesis accounting for the origin of L-amino acids in the biosphere

When recrystallizations were performed using a mixture of 12 D,L-amino acids (alanine, aspartic acid, arginine, glutamic acid, glutamine, histidine, leucine, methionine, serine, valine, phenylalanine, and tyrosine) with excess D,L-asparagine, all amino acids with the same configuration as asparagine were preferentially co-crystallized, indicating that it is the nature of a mixture of racemic amino acids to produce a spontaneous high enantiomeric excess.     

One Step up the Ladder of Prebiotic Complexity: Formation of Nonrandom Linear Polypeptides from Binary Systems of Amino Acids on Silica

Evidence for the formation of linear oligopeptides with nonrandom sequences from mixtures of amino acids coadsorbed on silica and submitted to a simple thermal activation is presented. The amino acid couples (glutamic acid+leucine) and (aspartic acid+valine) were deposited on a fumed silica and submitted to a single heating step at moderate temperature. The evolution of the systems was characterized by X-ray diffraction, infrared spectroscopy, thermosgravimetric analysis, HPLC, and electrospray ionization mass spectrometry (ESI-MS). Evidence for the formation of amide bonds was found in all systems studied. While the products of single amino acids activation on silica could be considered as evolutionary dead ends, (glutamic acid+leucine) and, at to some extent, (aspartic acid+valine) gave rise to the high yield formation of linear peptides up to the hexamers. Oligopeptides of such length have not been observed before in surface polymerization scenarios (unless the amino acids had been deposited by chemical vapor deposition, which is not realistic in a prebiotic environment). Furthermore, not all possible amino acid sequences were present in the activation products, which is indicative of polymerization selectivity. These results are promising for origins of life studies because they suggest the emergence of nonrandom biopolymers in a simple prebiotic scenario.     

A peptide containing aspartic acid, glutamic acid and serine in calf brain synaptic vesicles

Free amino acids and other amino compounds in calf brain synaptic vesicles were identified and determined by thin-layer chromatography and ion-exchange chromatography. The vesicles contained ten identified amino acids with glutamic acid, aspartic acid, taurine and gamma-aminobutyric acid in the highest concentrations, and also cysteic acid (or cysteinesulfinic acid), glutamine, alanine, serine, glycine and lysine. The vesicles also contained certain unknown acid-labile, ninhydrin-positive compounds, one of which was a peptide yielding, after acid hydrolysis, about 40% aspartic acid, 30% serine, 15% glutamic acid, 10% glycine and possibly some alanine and lysine. The concentration of the peptide in the vesicles was as high as that of all the other amino compounds together.     

High‐speed separation and detection of amino acids in laver using a short capillary electrophoresis system

A high‐speed separation method of capillary MEKC with LIF detection had been developed for separation and determination of amino acids in laver. The CE system comprised a manual slotted‐vial array (SVA) for sample introduction that could improve the separation efficiency by reducing injection volume. Using a capillary with 80 mm effective separation length, the separation conditions for amino acids were optimized. Applied with the separation electric field strength of 300 V/cm, the ten amino acids could be completely separated within 2.5 min with 10 mol/L Na₂HPO₄–NaOH buffer (pH = 11.5) including 30 mmol/L SDS. Theoretical plates for amino acids ranged from 72 000 to 40 000 (corresponding to 1.1–2.0 μm plate heights) and the detection limits were between 25 and 80 nmol/L. Finally, this method was applied to analyze the composition of amino acids in laver and eight known amino acids could be found in the sample. The contents of five amino acids, tyrosine, glutamic acid, glycine, lysine, and aspartic acid that could be completely separated in real sample were determined. The recoveries ranged from 82.3% to 123% that indicated the good reliability for this method in laver sample analysis.     

毛细管电泳-间接紫外检测法测定蜂蜜中的氨基酸

采用毛细管电泳-间接紫外检测法同时分离测定蜂蜜中的赖氨酸、色氨酸、谷氨酸等9种氨基酸。考察了磷酸浓度、进样方式和缓冲液pH对分离效率和重现性的影响。在分离电压为-15 kV、检测波长为220 nm条件下,以含有0.5 mmol/L十六烷基三甲基溴化铵、20 mmol/L烟酸、10%甲醇的10 mmol/L磷酸二氢钠缓冲溶液(pH 10.2)为运行缓冲液,9种组分在11 min内达到基线分离;检出限最低可达到0.3 mg/L;线性范围为1.0~1000 mg/L;日间及日内精密度为0.64%~5.83%。实际样品中除甲硫氨酸外的8种氨基酸的加标回收率为60.00%~118.37%。将该方法应用于不同蜜源植物和产地的蜂蜜样品的测定,在市售的5种蜂蜜中均检测到脯氨酸、丝氨酸和天冬氨酸,而只在荔枝蜜中检测到苏氨酸。该方法可以为蜂蜜的蜜源鉴别及质量评估提供借鉴方法。