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.     

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.     

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.     

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.     

Honey from Luso region (Portugal): Physicochemical characteristics and mineral contents

This work was conducted to evaluate the quality of 38 honey samples from Luso region (Portugal), and to study the relation between Eucalyptus pollen and chemical properties of honey. Mean values obtained for physicochemical parameters were: pH 3.83; 16.65% moisture; 80.7 °Brix sugar; 0.35% ash; 419.6 μS cm^− 1 electrical conductivity; 21.5 meq/kg free acidity; 9.6 meq/kg lactonic acidity; 31.2 meq/kg total acidity; 9.41 mg/kg HMF and 18.3° Gothe diastase activity. The mineral content was determined by atomic absorption spectrometry, and in the analysed samples, potassium was the major element, being magnesium the minor one. Mean values obtained were (mg/kg): Ca, 59.88; K, 1150.10; Mg, 35.57; Na, 261.43. Among the overall determined parameters, only Mg, ash and electrical conductivity were influenced by the presence of Eucalyptus pollen in the honey samples: the values obtained for Mg, ash and electrical conductivity in multifloral honey without Eucalyptus were lower than those of either monofloral or multifloral honey with Eucalyptus. The results obtained for physicochemical characteristics of Luso honey indicate a good quality level, adequate processing, good maturity and freshness.     

On-line preconcentration and speciation of arsenic by flow injection hydride generation atomic absorption spectrophotometry

A flow injection-column preconcentration-hydride generation atomic absorption spectrophotometric (FI-column-HGAAS) method was developed for determining μg/l levels of As(III) and As(V) in water samples, with simultaneous preconcentration and speciation. The speciation scheme involved determining As(V) at neutral pH and As(III + V) at pH 12, with As(III) obtained by difference. The enrichment factor (EF) increased with increase in sample loading volume from 2.5 to 10 ml, and for preconcentration using the chloride-form anion exchange column, EFs ranged from 5 to 48 for As(V) and 4 to 24 for As(III + V), with corresponding detection limits of 0.03-0.3 and 0.07-0.3 μg/l. Linear concentration range (LCR) also varied with sample loading volume, and for a 5-ml sample was 0.3-5 and 0.2-8 μg/l for As(V) and As(III + V), respectively. Sample throughput, which decreased with increase in sample volume, was 8-17 samples/h. For the hydroxide-form column, the EFS for 2.5-10 ml samples were 3-23 for As(V) and 2-15 for As(III + V), with corresponding detection limits of 0.07-0.4 and 0.1-0.5 μg/l. The LCR for a 5-ml sample was 0.3-10 μg/l for As(V) and 0.2-20 μg/l for As(III + V). Sample throughput was 10-20 samples/h. The developed method has been effectively applied to tap water and mineral water samples, with recoveries ranging from 90 to 102% for 5-ml samples passed through the two columns.     

Development of a tetramethylrhodamine-labeled probe for a capillary electrophoresis-based competitive immunoassay of staphylococcal enterotoxin B

Staphylococcal enterotoxin B (SEB) was labeled with tetramethylrhodamine isothiocyanate (TRITC) and used as a probe for a competitive immunoassay. Labeling conditions such as solution pH and time were varied to observe the effect on the fluorescent product. It was found that solution pH of the labeling reaction had little effect on the fluorescence signal of the resulting products. However, labeling at pH 7.0 produced a probe that had a higher affinity for the antibody used in this study than the probes produced at pH 8.0 and 9.0. The fluorescent probes were used to perform a competitive assay for SEB in model skim milk samples. Detection limit was approximately 300 fg of SEB. Quantitation was achieved by curve fitting of fluorescent signals for bound/free probe versus log[SEB] with logarithmic functions. Accuracy in the model skim milk samples was acceptable for 3 and 5 nM SEB, but decreased considerably for a concentration of less than 1 nM SEB. The error was attributed to deviation in linearity in the standard curve at lower concentrations. Reproducibility for the analysis of both standard solutions used for the calibration curves and the model skim milk samples was excellent, with standard deviations of approximately 10% from data collected over a 3-week period. No cross-reactivity was found when the assay was tested with a 700 nM sample of staphylococcal enterotoxin A. Although competitive immunoassays are usually used for small molecules, such as therapeutic drugs, the results demonstrate that relatively large molecules (SEB, 27 kDa) can also be assayed with the technique.     

Potential of visible-near infrared spectroscopy combined with chemometrics for analysis of some constituents of coffee and banana residues

Banana (stalk, leaf, rhizome, rachis and stem) and coffee (leaf and husks) residues are promising feedstock for fuel and chemical production. In this work we show the potential of near-infrared spectroscopy (NIR) and multivariate analysis to replace reference methods in the characterization of some constituents of coffee and banana residues. The evaluated parameters were Klason lignin (KL), acid soluble lignin (ASL), total lignin (TL), extractives, moisture, ash and acid insoluble residue (AIR) contents of 104 banana residues (B) and102 coffee (C) residues from Brazil. PLS models were built for banana (B), coffee (C) and pooled samples (B + C). The precision of NIR methodology was better (p < 0.05) than the reference method for almost all the parameters, being worse for moisture. With the exception of ash (B and C) and ASL (C) content, which was predicted poorly (R² < 0.80), the models for all the analytes exhibited R² > 0.80. The range error ratios varied from 4.5 to 16.0. Based on the results of external validation, the statistical tests and figures of merit, NIR spectroscopy proved to be useful for chemical prediction of banana and coffee residues and can be used as a faster and more economical alternative to the standard methodologies.     

Analysis of hexachlorocyclohexanes in aquatic samples by one-step microwave-assisted headspace controlled-temperature liquid-phase microextraction and gas chromatography with electron capture detection

A microwave-assisted headspace controlled-temperature liquid-phase microextraction (HS-CT-LPME) technique was applied for the one-step sample extraction of hexachlorocyclohexanes (HCHs) from aqueous samples with complicate matrices, followed by gas chromatographic (GC) analysis with electron capture detector (ECD). Microwave heating was applied to accelerate the evaporation of HCHs into the headspace and an external-cooling system was used to control the temperature in the sampling zone for HS-LPME. Parameters affecting extraction efficiency, such as LPME solvent, sampling position and temperature, microwave power and irradiation time (the same as sampling time), sample pH, and salt addition were thoroughly investigated. From experimental results, the following conditions were selected for the extraction of HCHs from 10-mL water sample (pH 2.0) by using 1-octanol as the LPME solvent, with sampling done at 38 °C for 6 min under 167 W of microwave irradiation. The detections were linear in the concentration of 0.1–10 μg/L for α-HCH and γ-HCH, and 1–100 μg/L for β-HCH and δ-HCH. Detection limits were 0.05, 0.4, 0.03 and 0.1 μg/L for α-, β-, γ- and δ-HCH, respectively. Environmental water samples were analyzed with recovery between 86.4% and 102.4% for farm-field water, and between 92.2% and 98.6% for river water. The proposed method proved to serve as a simple, rapid, sensitive, inexpensive, and eco-friendly procedure for the determination of HCHs in aqueous samples.     

Determination of Ascorbic Acid,Total Ascorbic Acid,and Dehydroascorbic Acid in Bee Pollen Using Hydrophilic Interaction Liquid Chromatography-Ultraviolet Detection

Ascorbic acid (AA) is one of the essential nutrients in bee pollen, however, it is unstable and likely to be oxidized. Generally, the oxidation form (dehydroascorbic acid (DHA)) is considered to have equivalent biological activity as the reduction form. Thus, determination of the total content of AA and DHA would be more accurate for the nutritional analysis of bee pollen. Here we present a simple, sensitive, and reliable method for the determination of AA, total ascorbic acids (TAA), and DHA in rape (Brassica campestris), lotus (Nelumbo nucifera), and camellia (Camellia japonica) bee pollen, which is based on ultrasonic extraction in metaphosphoric acid solution, and analysis using hydrophilic interaction liquid chromatography (HILIC)-ultraviolet detection. Analytical performance of the method was evaluated and validated, then the proposed method was successfully applied in twenty-one bee pollen samples. Results indicated that contents of AA were in the range of 17.54 to 94.01 µg/g, 66.01 to 111.66 µg/g, and 90.04 to 313.02 µg/g for rape, lotus, and camellia bee pollen, respectively. In addition, percentages of DHA in TAA showed good intra-species consistency, with values of 13.7%, 16.5%, and 7.6% in rape, lotus, and camellia bee pollen, respectively. This is the first report on the discriminative determination between AA and DHA in bee pollen matrices. The proposed method would be valuable for the nutritional analysis of bee pollen.     

Importance of control of enzymatic degradation for determination of bisphenol A from fruits and vegetables

The purpose of this study was to develop an analytical method for determination of bisphenol A (BPA) from fruits and vegetables. The present method developed for extraction of BPA from samples was based on solid-phase extraction (SPE) method and solvent extraction. Recovery results in the samples spiked with a 10 ng/ml BPA [no detection (<1 ng/g) to 77%] were lower than those in the samples with a 50 ng/ml BPA (26-96%). The fact that the low recovery results were caused by BPA degradation by enzymes is found. These problems were proved by the pH (pH ≤3) and the heating treatment (at ≥80 °C for 5 min). However, because the heating treatment at temperatures of ≥80 °C for 5 min is more difficult and time-consuming method than the pH control, we suggest that the pH control is useful to prevent BPA degradation. Good recovery results (82-101%) were obtained from all fruit and vegetable samples after pH treatment (pH ≤3). Effective elimination of impurities and a good detection limit (1 ng/g) were obtained with a method involving two SPE cartridges (OASIS HLB and Sep-Pak Florisil cartridge).     

Micro Salting-Out Assisted Matrix Solid-Phase Dispersion: A Simple and Fast Sample Preparation Method for the Analysis of Bisphenol Contaminants in Bee Pollen

In the present work, a novel sample preparation method, micro salting-out assisted matrix solid-phase dispersion (μ-SOA-MSPD), was developed for the determination of bisphenol A (BPA) and bisphenol B (BPB) contaminants in bee pollen. The proposed method was designed to combine two classical sample preparation methodologies, matrix solid-phase dispersion (MSPD) and homogenous liquid-liquid extraction (HLLE), to simplify and speed-up the preparation process. Parameters of μ-SOA-MSPD were systematically investigated, and results indicated the significant effect of salt and ACN-H₂O extractant on the signal response of analytes. In addition, excellent clean-up ability in removing matrix components was observed when primary secondary amine (PSA) sorbent was introduced into the blending operation. The developed method was fully validated, and the limits of detection for BPA and BPB were 20 μg/kg and 30 μg/kg, respectively. Average recoveries and precisions were ranged from 83.03% to 94.64% and 1.76% to 5.45%, respectively. This is the first report on the analysis of bisphenol contaminants in bee pollen sample, and also on the combination of MSPD and HLLE. The present method might provide a new strategy for simple and fast sample preparation of solid and semi-solid samples.     

Near-infrared diffuse reflectance spectroscopy and neural networks for measuring nutritional parameters in chocolate samples

A rapid and non-destructive method has been developed for the characterization of chocolate samples based on diffuse reflectance near-infrared Fourier transform spectroscopy (DRIFTS) and artificial neural networks (ANNs). This methodology provides a potentially useful alternative to time-consuming chemical methods of analysis. To assess its utility, 36 chocolate samples purchased from the Spanish market were analyzed for the determination of the main nutritional parameters like carbohydrates, fat, proteins, energetic value and cocoa content.Direct triplicate measurements of each sample were carried out by DRIFTS. Cluster hierarchical analysis was used for selecting calibration and validation data sets, resulting in a calibration set comprised of 19 samples and a validation data set of 17 samples. As it is common the presence of non-linear effect in reflectance spectroscopy, ANNs was chosen for data pretreatment. The root-mean-square error of prediction (RMSEP) values obtained for carbohydrates, fat, energetic value and cocoa were 1.0% (w/w), 1.0% (w/w), 50 kJ (100 g)⁻¹ and 1.4%, respectively. The mean difference (d_x-y) and standard deviation of mean differences (s_x-y) of the carbohydrates, fat, proteins content, energetic value and cocoa content were 0.9 and 2.4% (w/w), 0.2 and 1.0% (w/w), 9.1 and 50 kJ (100 g)⁻¹, and −0.5 and 1.4%, respectively. The maximum relative error for the prediction (QC) of any of these parameters for a new sample did not exceed 5.2%.     

Direct Determination of Urinary Lysozyme Using Surface Plasmon Resonance Light-Scattering of Gold Nanoparticles

The purpose of this study was to establish a simple and sensitive analytical method for lysozyme using Plasmon Resonance Light-Scattering (PRLS) technique with Gold Nanoparticles (AuNPs) as the probe. Nanomolar level of lysozyme induced AuNPs aggregation with enhanced PRLS. For 1.4 nM citrate-capped AuNPs (13 nm in diameter), the linear range of the calibration curve was 15-50 nM with a detection limit of 13.1 nM for lysozyme. Six nanomolar lysozyme can produce an observable PRLS enhancement. Most potential interfering substances present in urine had a negligible effect on the determination. The interference from human serum albumin in the urinary sample can be reduced by precipitating the albumin with ethanol at pH 4.8-4.9. The 90.1-118.2% recovery was achieved for 8 individual lysozyme-spiked urinary samples. This simple and sensitive method for lysozyme does not require sample clean-up and AuNPs modification, thus provided an alternative for urinary lysozyme determination.     

On-column liquid–liquid–liquid microextraction coupled with base stacking as a dual preconcentration method for capillary zone electrophoresis

A simple and efficient dual preconcentration method of on-column liquid–liquid–liquid microextraction (LLLME) coupled with base stacking was developed for capillary zone electrophoresis (CZE) in this paper. Four N-methyl carbamates were used as target compounds to evaluate the enrichment means. The carbamates in sample solutions (donor phase) were extracted into a dodecanol phase immobilized on a porous hollow fiber, hydrolyzed and back extracted into 0.20 μL running buffer (acceptor phase) of 30 mmol/L methylamine hydrochloride (pH 11.6) containing 0.5 mmol/L tetradecyltrimethylammonium bromide inside the hollow fiber, stacked further with 0.5 mol/L NaOH injected at −10 kV for 60 s, and separated by CZE. Analytical parameters affecting the LLLME, base stacking and CZE were investigated, including sample solution volume, pH and temperature, extraction time, stirring rate, buffer component, buffer pH, NaOH concentration, stacking time, etc. The enrichment factors of the carbamates were higher than 1100. The relative standard deviation (RSD) of peak height and limits of detection (LODs) were 4.5–5.5% (n = 6) and 2–4 ng/mL (S/N = 3) for standard solutions, respectively. The proposed method was applied to the analysis of vegetable and fruit samples with the RSD less than 6.0% (n = 3) and LODs of 6–10 ng/g (S/N = 3). The calibration solutions were prepared by diluting the stock solutions with blank sample solutions, and the calibration concentrations ranged from 0.012 to 1.0 μg/mL (r > 0.9951). The analytical results demonstrated that the LLLME coupled with base stacking was a simple, convenient and reliable on-column sample pretreatment method for the analysis of anionic analytes in CZE.     

Simultaneous quantification of amphetamines, caffeine and ketamine in urine by hollow fiber liquid phase microextraction combined with gas chromatography-flame ionization detector

A method of hollow fiber (HF) liquid phase microextraction (LPME) combined with gas chromatography (GC)-flame ionization detection (FID) was developed for the simultaneous quantification of trace amphetamine (AP), methamphetamine (MA), methylenedioxyamphetamine (MDA), methylenedioxymethamphetamine (MDMA), caffeine and ketamine (KT) in drug abuser urine samples. The factors affecting on the extraction of six target analytes by HF-LPME were investigated and optimized, and the subsequent analytical performance evaluation and real sample analysis were performed by the extraction of six target analytes in sample solution containing 30% NaCl (pH 12.5) for 20 min with extraction temperature of 30 °C and stirring rate of 1000 rpm. Under such optimal conditions, the limits of detection (LODs, S/N = 3) for the six target analytes were ranged from 8 μg/L (AP, KT) to 82 μg/L (MDA), with the enrichment factors (EFs) of 5-227 folds, and the relative standard deviations (RSDs, n = 7) were in the range of 6.9-14.1%. The correlation coefficients of the calibration for the six target analytes over the dynamic linear range were higher than 0.9958. The application feasibility of HF-LPME-GC-FID in illegal drug monitoring was demonstrated by analyzing drug abuser urine samples, and the recoveries of target drugs for the spiked sample ranging from 75.2% to 119.3% indicated an excellent anti-interference capability of the developed method. The proposed method is simple, effective, sensitive and low-cost, and provides a much more accurate and sensitive detection platform over the conventional analytical techniques (such as immunological assay) for drug abuse analysis.     

Characterization of estuarine sediments by near infrared diffuse reflectance spectroscopy

It has been developed a partial least squares near infrared (PLS-NIR) method for the determination of estuarine sediment physicochemical parameters. The method was based on the chemometric treatment of first order derivative reflectance spectra obtained from samples previously lyophilized and sieved through a lower than 63 μm grid. Spectra were scanned from 833 to 2976 nm, averaging 36 scans per spectrum at a resolution of 8 cm⁻¹, using chromatographic glass vials of 9.5 mm internal diameter as measurement cells. Models were built using reference data of 31 samples selected through the use of a hierarchical cluster analysis of NIR spectra of sediments obtained from the Ria de Arousa estuary and prediction parameters were established from a validation set of 50 samples of the same area. pH, redox potential (Eh), carbon (C), nitrogen (N) and hydrogen (H) content together with Sn, Pb, Cd, As, Sb and total Cr and also acid soluble, reducible and oxidable Cr fractions were employed as characteristic parameters of the studied sediments. Standard error of prediction values for C and N content were of the order of 4 and 1.3 mg g⁻¹ for H. Prediction errors for pH and Eh were 0.15 units and 37 mV, respectively, thus indicating the good prediction capabilities of the method. Regarding trace metal concentrations PLS-NIR provided prediction error levels for unknown samples around 20% for Sn, Pb, As and Sb and root mean square errors of prediction around 40% for concentration levels of 400 ng g⁻¹ Cd and 100 μg g⁻¹ Cr. For the different extractable fractions of Cr the residual prediction deviation varied from 1.3 to 1.7 but relative errors found for samples of the validation set were only useful for screening purposes.     

High-throughput salting-out assisted liquid/liquid extraction with acetonitrile for the simultaneous determination of simvastatin and simvastatin acid in human plasma with liquid chromatography

Simvastatin (SS) is an effective cholesterol-lowering medicine, and is hydrolyzed to simvastatin acid (SSA) after oral administration. Due to SS and SSA inter-conversion and its pH and temperature dependence, SS and SSA quantitation is analytically challenging. Here we report a high-throughput salting-out assisted liquid/liquid extraction (SALLE) method with acetonitrile and mass spectrometry compatible salts for simultaneous LC-MS/MS analysis of SS and SSA. The sample preparation of a 96-well plate using SALLE was completed within 20 min, and the SALLE extract was diluted and injected into an LC-MS/MS system with a cycle time of 2.0 min/sample. The seamless interface of SALLE and LC-MS eliminated drying down step and thus potential sample exposure to room or higher temperature. The stability of SS and SSA in various concentration ratios in plasma was evaluated at room and low (4 °C) temperature and the low temperature (4 °C) was found necessary to maintain sample integrity. The short sample preparation time along with controlled temperature (2-4 °C) and acidity (pH 4.5) throughout sample preparation minimized the conversion of SS → SSA to ≤0.10% and the conversion of SSA → SS to 0.00% The method was validated with a lower limit of quantitation (LLOQ) of 0.094 ng mL⁻¹ for both SS and SSA and a sample volume of 100 μL. The method was used for a bioequivalence study with 4048 samples. Incurred sample reproducibility (ISR) analysis of 362 samples from the study exceeded ISR requirement with 99% re-analysis results within 100 ± 20% of the original analysis results.     

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.     

Determination of organophosphorous pesticides in water using in-syringe ultrasound-assisted emulsification and gas chromatography with electron-capture detection

An in-syringe ultrasound-assisted emulsification microextraction (USAEME) was developed for the extraction of organophosphorus pesticides (OPPs) from water samples. The OPPs subsequently analyzed gas chromatography (GC) using a microelectron capture detector (μECD). Ultrasound radiation was applied to accelerate the emulsification of μL-level low-density organic solvent in aqueous solutions to enhance the microextraction efficiency of OPPs in the sample preparation for GC-μECD. Parameters affecting the efficiency of USAEME, such as the extraction solvent, solvent volume, pH, salt-addition, and extraction time were thoroughly investigated. Based on experimental results, OPPs were extracted from a 5 mL aqueous sample by the addition of 20 μL toluene as the extraction solvent, followed by ultrasonication for 30 s, and then centrifugation for 3 min at 3200 rpm, offered the best extraction efficiency. Detections were linear in the concentration of 0.01–1 μg/L with detection limits between 1 ng/L and 2 ng/L for OPPs. Enrichment factors ranged from 330 to 699. Three spiked aqueous samples were analyzed, and recovery ranged from 90.1% to 104.7% for farm-field water, and 90.1% to 101.8% for industrial wastewater. The proposed method provides a simple, rapid, sensitive, inexpensive, and eco-friendly process for determining OPPs in water samples.