Pressurized liquid extraction of capsaicinoids from peppers

A method has been developed for the extraction of capsaicinoids from peppers by pressurized liquid extraction (PLE); these compounds are determined by reverse phase high-performance liquid chromatography (HPLC), with detection by fluorescence spectrophotometry and mass spectrometry (MS). The stability of capsaicin and dihydrocapsaicin has been studied at different temperatures (50-200 degrees C), and several extraction variables have been assayed: solvent (methanol, ethanol, and water), different percentages of water in the methanol (0-20%) and in the ethanol (0-20%), and the number of extraction cycles. The study has evaluated the repeatability (RSD < 7%) and the reproducibility (RSD < 7%) of the method. Finally, the PLE method developed has been applied to quantify the capsaicinoids present in three varieties of hot peppers cultivated in Spain, quantifying five capsaicinoids: nordihydrocapsaicin, capsaicin, dihydrocapsaicin, an isomer of dihydrocapsaicin, and homodihydrocapsaicin.     

Analysis of eight capsaicinoids in peppers and pepper-containing foods by high-performance liquid chromatography and liquid chromatography-mass spectrometry

Diverse procedures have been reported for the isolation and analysis of secondary metabolites called capsaicinoids, pungent compounds in the fruit of the Capsicum (Solanaceae) plant. To further improve the usefulness of high-performance liquid chromatography (HPLC), studies were carried out on the analysis of extracts containing up to eight of the following capsaicinoids: capsaicin, dihydrocapsaicin, homocapsaicin-I, homocapsaicin-II, homodihydrocapsaicin-I, homodihydrocapsaicin-II, nonivamide, and nordihydrocapsaicin. HPLC was optimized by defining effects on retention times of (a) the composition of the mobile phase (acetonitrile/0.5% formic acid in H2O), (b) the length of the Inertsil column, and (c) the capacity values (k) of the column packing. Identification was based on retention times and mass spectra of individual peaks. Quantification was based on the UV response at 280 nm in HPLC and recoveries from spiked samples. The method (limit of detection of approximately 15-30 ng) was successfully used to quantify capsaicinoid levels of parts of the pepper fruit (pericarp, placenta, seeds, and in the top, middle, and base parts of whole peppers) in 17 species of peppers and in 23 pepper-containing foods. The results demonstrate the usefulness of the method for the analysis of capsaicinoids ranging from approximately 0.5 to 3600 microg of capsaicin equiv/g of product. The water content of 12 fresh peppers ranged from 80.8 to 92.7%. The described freeze-drying, extraction, and analysis methods should be useful for assessing the distribution of capsaicinoids in the foods and in defining the roles of these biologically active compounds in the plant, the diet, and medicine.     

Ground red peppers: capsaicinoids content,Scoville scores,and discrimination by an electronic nose

High-pressure liquid chromatography (HPLC) was used to determine the capsaicin, dihydrocapsaicin, and total capsaicinoids levels of different ground red pepper samples obtained from local retail markets in Izmir, Turkey. Scoville scores were determined using sensory tests. An electronic nose (EN) was used to discriminate ground red pepper samples by headspace volatiles. EN data were analyzed using discriminant function analysis (DFA). An overall correct classification rate of pepper varieties by EN of 91% was obtained. A linear correlation between capsaicin, dihydrocapsaicin, and total capsaicinoids and Scoville scores was also observed, and R (2) values of 0.89, 0.85, and 0.91 were obtained, respectively.     

Preliminary studies for the differentiation of apple juice samples by chemometric analysis of solid-phase microextraction-gas chromatographic data

A combination of gas chromatography (GC) and chemometrics was evaluated for its ability to differentiate between apple juice samples on the basis of apple variety and applied heat treatment. The heat treatment involved exposure of 15 mL juice samples for 30 s in a 900 W domestic microwave oven. The chromatographic results were subjected to two chemometric procedures: (1) partial least squares (PLS) regression and (2) linear discriminant analysis (LDA) applied to principal component (PC) scores. The percent correct classification of samples were obtained from PLS and LDA in terms of separation on the basis of apple variety and applied heat treatment. PLS gave the highest level of correct classification of the apple juice samples according to both variety and heat treatment, 92.5% correct classification in each case. When LDA was performed on the PC scores obtained from GC analysis, 87.5% and 80% of samples were correctly classified according to apple variety used and applied heat treatment, respectively.     

chemometric analysis of hydro-chemical data of an alluvial river – a case study

Hydrochemistry of an alluvial river was investigated employing the chemometric techniques such as cluster analysis (CA), principal component analysis (PCA), discriminant analysis (DA) and partial least square (PLS) with a view to extract information about the variables responsible for spatial and temporal variations in river hydrochemistry and water quality, the hidden factors explaining the structure of the hydro-chemical database of the river, factors/processes influencing the river hydro-chemistry. Analysis of spearman's correlation coefficient revealed non-significant correlation of the pollution indicator (BOD, COD, SO₄, F, NH₄-N, NO₃-N) variables with season and significant correlation with site, indicating contribution of the site-specific anthropogenic sources in the catchments. Spatial CA clustered the monitoring sites (10nos.) into three groups of relatively non-polluted sites, moderately polluted sites, and highly polluted sites. Temporal CA differentiated among the samples of monsoon and non-monsoon months. PCA rendered considerable data reduction, in terms of eight parameters explaining about 71% of the total variance and evolved six PCs. PCA grouped samples belonging to different seasons and sites distinctly correlating them with natural and anthropogenic variables. Temporal and spatial DA rendered 97 and 92% correct assignations of the samples, respectively, and revealed that temperature, pH, BOD, DO, alkalinity and Ca are the most significant variables to discriminate between the different seasons and account for most of the expected temporal variations in hydrochemistry of the river, whereas, hardness, DO, BOD, COD, Ca and Mg were the most significant discriminating variables in space. Spatial and temporal groupings of the samples were successfully achieved through PLS modeling. PLS showed that the summer season samples are dominated by PO₄, TDS, F, K, COD, BOD, Na, Cl, hardness and alkalinity, whereas, samples of winter season by DO, pH, NH₄-N and coliforms. Furthermore, PLS indicated site-specific dominance of anthropogenic contaminants suggesting for their pollution sources in the corresponding catchments of these sites.     

Predicting the age and type of tuocha tea by fourier transform infrared spectroscopy and chemometric data analysis

Fourier transform infrared (FTIR) spectroscopy combined with chemometric multivariate methods was proposed to discriminate the type (unfermented and fermented) and predict the age of tuocha tea. Transmittance FTIR spectra ranging from 400 to 4000 cm(-1) of 80 fermented and 98 unfermented tea samples from Yunnan province of China were measured. Sample preparation involved finely grinding tea samples and formation of thin KBr disks (under 120 kg/cm(2) for 5 min). For data analysis, partial least-squares (PLS) discriminant analysis (PLSDA) was applied to discriminate unfermented and fermented teas. The sensitivity and specificity of PLSDA with first-derivative spectra were 93 and 96%, respectively. Multivariate calibration models were developed to predict the age of fermented and unfermented teas. Different options of data preprocessing and calibration models were investigated. Whereas linear PLS based on standard normal variate (SNV) spectra was adequate for modeling the age of unfermented tea samples (RMSEP = 1.47 months), a nonlinear back-propagation-artificial neutral network was required for calibrating the age of fermented tea (RMSEP = 1.67 months with second-derivative spectra). For type discrimination and calibration of tea age, SNV and derivative preprocessing played an important role in reducing the spectral variations caused by scattering effects and baseline shifts.     

Analysis of water quality data using spectral analysis

Considerable effort has been expended by many State, Federal and private agencies in collecting data by installing automatic water quality monitoring stations on many streams and estuaries. This work discusses techniques for analyzing the data and presents some results based on the analysis of monitoring stations along the Ohio, Detroit, Missouri, and Coosa Rivers. Autocorrelation, spectral estimates, cross correlation, amplitude of transfer function and coherence square have been evaluated to correlate a water quality variable measured at different positions or different variables measured at the same location. Results from the different rivers have been compared and some conclusions have been drawn.     

Classification of cereal flours by chemometric analysis of MIR spectra

Different kinds of cereal flours submitted to various technological treatments were classified on the basis of their mid-infrared spectra by pattern recognition techniques. Classification in the wavelet domain was achieved by using the wavelet packet transform for efficient pattern recognition (WPTER) algorithm, which allowed singling out the most discriminant spectral regions. Principal component analysis (PCA) on the selected features showed an effective clustering of the analyzed flours. Satisfactory classification models were obtained both on training and test samples. Furthermore, mixtures of varying composition of the studied flours were distributed in the PCA space according to their composition.     

紫外分光光度法测定啤酒大麦籽粒脂氧合酶活力的研究

为了明确影响啤酒大麦籽粒脂氧合酶(LOX-1)活力的参数,以甘啤4号啤酒大麦籽粒为研究对象,采用紫外分光光度法探究底物浓度、提取缓冲液p H、反应体系缓冲液p H、提取时间、粗酶加入量∶底物加入量等对LOX-1活力的影响。结果表明,LOX-1活力随底物浓度的增加表现为先增加后减小的趋势,当底物浓度达到0.30mmol·L~(-1)时,LOX-1活力显著高于其它处理;随提取缓冲液p H的增加,LOX-1活力表现为双峰变化趋势,且在p H值5.0处,酶活力为9.85U·g~(-1),显著高于其它处理;粗酶提取时间为30min时,LOX-1活力显著高于其它处理,低于或者高于30min,酶活力均呈现降低趋势;LOX-1活力随反应体系p H的增加,表现为双峰变化趋势,当p H值为6.4时,酶活力最大,且与其它处理间存在显著差异;在其它条件不变,粗酶加入量为50μL的情况下,增加底物加入量,LOX-1活力表现为先增加后减小的趋势,且底物加入量为200μL时,酶活力显著高于其它处理。最终确定紫外分光光度法的测定参数:粗酶提取时间为30min,底物浓度为0.25mmol·L~(-1),提取液和反应体系缓冲液分别为p H值5.0醋酸盐缓冲液与p H值6.4磷酸盐缓冲液,粗酶加入酶量∶底物加入量为1∶4。研究结果为紫外分光光度法在啤酒大麦籽粒LOX-1活力测定中的应用提供了参考。     

UV spectral fingerprinting and analysis of variance-principal component analysis: a useful tool for characterizing sources of variance in plant materials

UV spectral fingerprints, in combination with analysis of variance-principal components analysis (ANOVA-PCA), can differentiate between cultivars and growing conditions (or treatments) and can be used to identify sources of variance. Broccoli samples, composed of two cultivars, were grown under seven different conditions or treatments (four levels of Se-enriched irrigation waters, organic farming, and conventional farming with 100 and 80% irrigation based on crop evaporation and transpiration rate). Freeze-dried powdered samples were extracted with methanol-water (60:40, v/v) and analyzed with no prior separation. Spectral fingerprints were acquired for the UV region (220-380 nm) using a 50-fold dilution of the extract. ANOVA-PCA was used to construct subset matrices that permitted easy verification of the hypothesis that cultivar and treatment contributed to a difference in the chemical expression of the broccoli. The sums of the squares of the same matrices were used to show that cultivar, treatment, and analytical repeatability contributed 30.5, 68.3, and 1.2% of the variance, respectively.     

Determination of total gossypol in cottonseed and cottonseed meals by derivative UV spectrophotometry

A new method for the determination of total gossypol in cottonseed and cottonseed meals has been developed. The method involves oxalic acid hydrolysis of the bound gossypol in a methyl ethyl ketone-water azeotrope, partitioning the liberated gossypol into chloroform, and quantification by 2nd derivative UV spectrophotometry. The 2nd derivative transformation and measurement of the conventional analytical band around 300 nm permits direct quantification of all compounds containing naphthalene nuclei; chromogenic reaction is not required. The method was tested at concentration levels of total gossypol normally expected for cottonseed and cottonseed meal. Precision and accuracy data suggested an overall relative standard deviation of 4.0% and an overall recovery of 89.5%. Although results for cottonseed and solvent-extracted cottonseed meal analyses were comparable to those obtained by use of American Oil Chemists' Society methods, results were lower for screw-pressed meals. The lower results were attributed to the partial conversion of gossypol, during the cooking process of these meals, to compounds that differ in composition and structure from gossypol and which react with aniline to give false readings.     

Prediction of macronutrients in plant leaves using chemometric analysis and wavelength selection

Purpose

Fast and real-time prediction of leaf nutrient concentrations can facilitate decision-making for fertilisation regimes on farms and address issues raised with over-fertilisation. Cacao (Theobroma cacao L.) is an important cash crop and requires nutrient supply to maintain yield. This project aimed to use chemometric analysis and wavelength selection to improve the accuracy of foliar nutrient prediction.

Materials and methods

We used a visible-near infrared (400–1000 nm) hyperspectral imaging (HSI) system to predict foliar calcium (Ca), potassium (K), phosphorus (P) and nitrogen (N) of cacao trees. Images were captured from 95 leaf samples. Partial least square regression (PLSR) models were developed to predict leaf nutrient concentrations and wavelength selection was undertaken.

Results and discussion

Using all wavelengths, Ca (R²_CV?=?0.76, RMSE_CV?=?0.28), K (R²_CV?=?0.35, RMSE_CV?=?0.46), P (R²_CV?=?0.75, RMSE_CV?=?0.019) and N (R²_CV?=?0.73, RMSE_CV?=?0.17) were predicted. Wavelength selection increased the prediction accuracy of Ca (R²_CV?=?0.79, RMSE_CV?=?0.27) and N (R²_CV?=?0.74, RMSE_CV?=?0.16), while did not affect prediction accuracy of foliar K (R²_CV?=?0.35, RMSE_CV?=?0.46) and P (R²_CV?=?0.75, RMSE_CV?=?0.019).

Conclusions

Visible-near infrared HSI has a good potential to predict Ca, P and N concentrations in cacao leaf samples, but K concentrations could not be predicted reliably. Wavelength selection increased the prediction accuracy of foliar Ca and N leading to a reduced number of wavelengths involved in developed models.

     

Biochemical profiling and chemometric analysis of seventeen UK-grown black currant cultivars

Black currant fruits are recognized as being an important dietary source of health-related compounds, such as anthocyanins and ascorbic acid. In the present study, the biochemical composition (viz., nonstructural carbohydrates, individual anthocyanins, total anthocyanins, total phenolics, and organic acids, including ascorbic acid) from 17 UK-grown black currant cultivars was analyzed. Berry composition was significantly affected by genotype. Nonstructural carbohydrates ranged from 85.09 to 179.92 mg g(-1) on a fresh weight (FW) basis, while concentration for organic acids ranged from 36.56 to 73.35 mg g(-1) FW. Relative concentrations of cyanidin 3-glucoside, cyanidin 3-rutinoside, delphinidin 3-glucoside and delphinidin 3-rutinoside were 3.1-7.9%, 35.4-47.0%, 7.6-12.5% and 36.9-50.9%, respectively. Differences in the biochemical profile among cultivars were emphasized by principal component analysis (PCA) and hierarchical cluster analysis (HCA). PCA was able to discriminate between cultivars, especially on the basis of health-related compounds. Initial exploration revealed that individual anthocyanins, total phenolics, and ascorbic acid could be used to characterize and classify different cultivars. HCA showed that the biochemical composition of the different cultivars was related to parentage information.     

辣椒素类物质在烤制加工和储藏中的稳定性

为了解辣椒素类物质在烤制加工和储藏过程中的稳定性,该文研究了不同加热温度和时间处理以及不同储藏条件下（常温和冷藏,真空和非真空）,野山椒中辣椒素类物质的含量变化。试验结果表明：烤制加热温度（80～180℃）及其时间（2～16 min）对辣椒素类物质的影响均显著（p<0.01）;不同储藏条件下,随着储藏时间的延长,野山椒中辣椒素类物质的含量均有不同程度下降。9个月后,真空包装冷藏的辣椒粉中辣椒素类物质含量降低了16.44%,非真空包装冷藏的降低了17.00%,真空包装常温储藏的降低了23.58%,非真空包装常温储藏的降低了24.11%,真空包装对其稳定性影响不大,低温更有利于保存辣椒素类物质。     

基于波谱分析技术的遥感作物分类方法

为获取东北三省作物类型分布信息,精确地进行粮食估产,该文以250mMODIS时间序列NDVI数据为主要数据源,以东北三省主要粮食作物水稻、玉米、大豆、小麦为研究对象,利用波谱分析方法对东北三省作物类型的空间分布进行研究。研究结果表明,大豆的遥感反演面积和统计面积的相关性最好(R2=0.770),其次是玉米(R2=0.710),水稻(R2=0.686)。该文使用的作物分类方法适用于试验条件有限,实测数据较难获得并以遥感数据为主要数据源且研究区域较大、作物类型单一、种植面积广的情况。     

Evaluation of soil erosion protective cover by crop residues using vegetation indices and spectral mixture analysis of multispectral and hyperspectral data

Crop residues are efficient in reducing erosion and surface water runoff on agricultural soils. Evaluating the crop residue cover fraction and its spatial distribution is important to scientists involved in the modelling of soil erosion and surface runoff, and also to authorities wishing to assess soil conservation adoption by farmers. This study focuses on the evaluation of four remote sensing techniques to estimate the cover fraction of cereal crop residues (i.e., wheat and corn) from multispectral and hyperspectral measurements. These are the Soil Adjusted Corn Residue Index (SACRI), the Crop Residue Index Multiband (CRIM), the Normalized Difference Index (NDI) and the spectral mixture analysis technique (SMA). Field campaigns that were carried out by the FLOODGEN project in Sainte-Angèle-de-Monnoir, Québec, Canada and in the Pays-de-Caux located in the Normandy region of France, allowed us to gather digital photographs, spectra and other measurements to determine the actual ground cover fraction. A linear regression analysis between results derived from Landsat-5 TM simulated field spectra and the actual ground cover fractions showed best results for the CRIM on the Ste-Angèle-de-Monnoir study site (R² = 0.96), and equally good results for the Pays-de-Caux study site (R² = 0.94). Results were not as good when SMA was applied to the same Landsat-5 TM simulated field spectra with R² values of 0.70 and 0.68 for both sites, respectively. However, results improved significantly when SMA was applied to the hyperspectral data in which case the R² values increased to 0.92 for the Sainte-Angèle-de-Monnoir site and 0.89 for the Pays-de-Caux study site. Results obtained with the NDI and SACRI from both simulated TM and hyperspectral field spectra were not conclusive.     

Determination of polymer additives-antioxidants and ultraviolet (UV) absorbers by high-performance liquid chromatography coupled with UV photodiode array detection in food simulants

An analytical method for the quantitative determination of migration levels of polymer additives such as antioxidants and UV absorbers in food packages by high-performance liquid chromatography coupled with UV-vis photodiode array detection has been developed. The pretreatment step involved solid-phase extraction with silica C18 cartridges. The analytical method showed good linearity, presenting regression coefficients (R(2)) ≥ 0.9990 for all compounds. This optimized method was also validated with respect to precision, reproducibility, stability, and accuracy. The limits of detection and quantification were between 0.09 and 1.72 μg mL(-1) and between 0.20 and 5.64 μg mL(-1) for 12 analytes, respectively. Recoveries were in the range of 67.48 and 108.55%, with relative standard deviations between 2.76 and 9.81%. Migration levels of antioxidants and UV absorbers were determined. Butylated hydroxyanisole, 2,6-di-tert-butyl-4-methylphenol (BHT), 2,4-di-tert-butylphenol, Cyanox 2246, Irganox 1035, Tinuvin 326, Tinuvin 328, Irganox 1010, and Irganox 1330 were detected; BHT and Cyanox 2246 were at higher levels than the specific migration levels in some food simulants.     

Fourier transform infrared spectroscopy and chemometric analysis of white wine polysaccharide extracts

Monovarietal white wines from Maria Gomes and Bical Portuguese Bairrada varieties were prepared according to different maceration and pectic enzyme clarification procedures. The polysaccharide-rich extracts, obtained by wine concentration, dialysis, and lyophilization, were fractionated by graded ethanol precipitation. A wide range of fractions rich in polysaccharides were obtained. Using the spectral region between 1200 and 800 cm(-)(1) of the FTIR spectra of the wine polysaccharide dry extracts, using PCA and CCA chemometric methods, it was possible to discriminate the extracts on the basis of their polysaccharide composition. Moreover, it was possible to identify the wine-making processes involved and their influence on the wine polysaccharides. Furthermore, a calibration model using a PLS1 was proposed for the quantification of mannose in the samples obtained by precipitation with 60% ethanol aqueous solutions. This information will allow an expeditious assessment and monitoring of the polysaccharide composition and modifications that occur during the wine-making processing and evolution.