Fluorescence of cereal flours.

Front-surface fluorescence spectra of cereal flours are easily measured with a commercial spectrofluorometer and a simple cell. The emission spectra are intense in the range 290-600 nm in which three emission bands are active. The most intense is due to the aromatic amino acid residues present in the proteins of flours. At least two other fluorophores are active in the above spectral range and compete for light with the chromophores present in the flours. Four absorption bands are revealed in the same spectral region by reflectance spectra, the most intense being due to the amino acidic fluorophores. Thus, the measured emission is the result of absorption, scattering, emission, and reabsorption processes. Information on the microenvironment of some fluorophores can be obtained. The possibility to recognize different species of cereals, even of different cultivars, is shown.     

Origin of French virgin olive oil registered designation of origins predicted by chemometric analysis of synchronous excitation-emission fluorescence spectra

The authentication of virgin olive oil samples requires usually the use of sophisticated and very expensive analytical techniques, so there is a need for fast and inexpensive analytical techniques for use in a quality control methodology. Virgin olive oils present an intense fluorescence spectra. Synchronous excitation-emission fluorescence spectroscopy (SEEFS) was assessed for origin determination of virgin olive oil samples from five French registered designation of origins (RDOs) (Nyons, Vallée des Baux, Aix-en-Provence, Haute-Provence, and Nice). The spectra present bands between 600 and 700 nm in emission due to chlorophylls a and b and pheophytins a and b. The bands between 275 and 400 nm in emission were attributed to alpha-, beta-, and gamma-tocopherols and to phenolic compounds, which characterize the virgin olive oils compared to other edible oils. The chemometric treatment (PLS1) of synchronous excitation-emission fluorescence spectra allows one to determine the origin of the oils from five French RDOs (Baux, Aix, Haute-Provence, Nice, and Nyons). Results were quite satisfactory, despite the similarity between two denominations of origin (Baux and Aix) that are composed by some common cultivars (Aglandau and Salonenque). The interpretation of the regression coefficients shows that RDOs are correlated to chlorophylls, pheophytins, tocopherols, and phenols compounds, which are different for each origin. SEEFS is part of a global analytic methodology that associates spectroscopic and chromatographic techniques. This approach can be used for traceability and vindicates the RDOs.     

Simplified electrophoretic assay for human salivary alpha-amylase inhibitor detection in cereal seed flours

Alpha-amylase inhibitors are antinutritional proteins largely found in cereal seeds. An in-gel assay was developed that allowed the rapid screening of these compounds in complex seed extracts. The assay was based on the electrophoretic separation of the extract proteins on starch-containing gels, followed by the detection of alpha-amylase-inhibiting proteins after incubation of the gel in an alpha-amylase solution; inhibitors were revealed by a staining method based on iodine binding to nondigested starch. The one-dimensional method can be useful to test inhibitory activity of purified proteins or to assay fractions recovered during a purification procedure. A two-dimensional (IEF x PAGE) non-denaturing system with second-dimension separation on starch-PAGE was also developed; the technique allowed the screening of complex protein mixtures for multiple inhibitory proteins. The newly developed assay method was used to test the presence of inhibitory activity in a crude extract from wheat flour, and it was validated by comparing in-gel and in-solution assays of commercially available alpha-amylase inhibitors.     

Direct fluorometric determination of fluorescent substances in powders: the case of riboflavin in cereal flours

Front-face emission spectra of powders can be recorded with a commercial spectrofluorometer. By combining the emissions of a scatterer powder and of a wheat flour sample, the scattering contribution to the front-face emission spectra of flour is removed, and the fluorescence of the flour is isolated. The fluorescence depends on the concentration of the fluorophores. By choosing convenient measurement parameters and by measuring the emission spectra of flour samples suitably enriched with riboflavin, the fluorescence of riboflavin could be isolated from that of other substances present in flours and the concentration of vitamin B(2) in native substrates could be determined. This method is particularly apt for the measurement of vitamin B(2) in low riboflavin-containing powders such as wheat flours, which are usually analyzed through complex chemical and microbiological methods. The method is essentially phenomenological, in view of the interpretation difficulties connected to the origin of the fluorescence resulting from the absorption of multiply scattered photons.     

Determination of capsaicinoids in habanero peppers by chemometric analysis of UV spectral data

A novel spectrophotometric method for the determination of capsaicinoids in habanero pepper extracts is described that does not require prior analyte separation. The method uses partial-least-squares (PLS-1) multivariate regression modeling techniques in conjunction with ordinary UV absorption spectral data obtained on alcoholic extracts of habanero peppers (Capsicum chinese). The PLS-1 regression models were developed by correlating the known total concentration of the two major capsaicinoids (capsaicin and dihydrocapsaicin) in the extracts as determined by high-performance liquid chromatography with the spectral data. The regression models were subsequently validated with laboratory-prepared test sets. The validation studies revealed that the root-mean-square error of prediction varied from 4 to 8 ppm, based on the results obtained from models prepared from nine test sets. Once a regression model has been developed and validated, analyses of the extracts can be accomplished rapidly by ordinary spectrophotometric procedures without any prior separation steps.     

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.     

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.     

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.     

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.     

Correlations between the amounts of free asparagine and saccharides present in commercial cereal flours in the United Kingdom and the generation of acrylamide during cooking

A range of commercially available cereals (mainly rye and wheat) used to manufacture U.K. bakery products were obtained, and the levels of free amino acids and sugars were measured. Selected samples were cooked as flours and doughs to generate acrylamide and the data compared with those obtained from a model system using dough samples that had been additionally fortified with asparagine (Asn) and sugars (glucose, fructose, maltose, and sucrose). In cooked flours and doughs, Asn was the key determinant of acrylamide generation. A significant finding for biscuit and rye flours was that levels of Asn were correlated with fructose and glucose. The results suggest that for these commercial cereals, selection based on low fructose and glucose contents, and hence low asparagine, could be beneficial in reducing acrylamide in products (e.g., crackers and crispbreads) that have no added sugars.     

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.

     

Sap analysis for diagnosis of nitrate accumulation in cereal forages

Abstract

Development of a quantitative, preharvest quiektest for NO₃ levels in cereal forages would improve crop management options to avoid NO₃ toxicity in livestock. Our objective was to determine if concentrations of NO₃ in sap expressed from oat (Avenasativa) and barley (Hordeum vulgare) are correlated with those in dry tissue of simultaneously harvested hay, and to test the reliability of the Cardy portable NO₃ meter for sap analysis in these species. In 1993, whole plant samples were gathered from plots fertilized with variable nitrogen (N) rates at four environments in Montana, and were analyzed for NO₃ concentration in lower‐internode sap and in whole plant dry matter. In 1994 and 1995, the study was repeated at two environments. The sampling technique included three subsamples from each plot for sap analysis, followed immediately by harvest of the entire plot for hay, and further subsampling for dry matter NO₃ analysis after drying. Linear correlations between dry matter and sap NO₃ concentrations were found across species at each environment in 1993 with r values of 0.64 to 0.81. No relationship was established for oat at one environment. Locations differed in the coefficient of correlation, indicating environmental influences on the relationship and/ or variability due to sampling technique. In 1994 and 1995, each species fit a separate linear correlation across site‐years with r values of 0.89 (oat) and 0.87 (barley). The consistency across site‐years (1994–1995) indicates that the variability in preliminary results was overcome with sampling technique. We propose a quantitative quiektest for NO₃ levels in cereal forages using conditional predictions of dry matter NO₃ based on observed values of sap NO₃. Since sap NO₃ readings with the Cardy portable nitrate meter were well correlated (r=0.93) with Accumet ISE readings across critical ranges, quiektest procedures are practical.     

Quantification of soil structural changes induced by cereal anchorage failure: Image analysis of thin sections

Cereal anchorage failure, or lodging, is the permanent displacement of a crop from the vertical and results in significant annual yield losses globally. Several factors have been identified as contributors to this phenomenon but the precise mechanisms of failure are still largely unknown because of difficulties in observing these processes as they occur in situ. To identify potential soil management practices to minimize losses associated with cereal root failure, an understanding of the nature of root‐soil interactions attributed to lodging is needed. An experiment was conducted that involved field impregnation and subsequent thin sectioning of lodged and unlodged root‐soil complexes from contrasting soils, cereal crops, and management practices to elucidate the effects of lodging on soil structure and porous architecture. Using image analysis, size and distribution of pores in soils were quantified at both meso‐ (100–30 μm) and microscales (<30 μm). A significant effect of lodging on porosity was recorded whereby lodging reduced total porosity through compaction created by movement of the stem base, although this was variable among soil types. Pore‐size distributions comprehensively supported these trends since alteration in the relative frequency of pores within specific size classes was clearly observed. The effects of lodging were more pronounced at the mesoscale because the data were more susceptible to variations created by natural soil heterogeneity at the microscale. These data suggested that sideways movement of the subterranean stem within the soil is a significant factor which is likely to affect the propensity for a cereal plant to lodge, indicating soil strength in the upper part of the soil profile is crucial.     

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.     

Characteristics of pregelatinized ae mutant rice flours prepared by boiling after preroasting

As ae mutant rice, such as EM10, lacks the starch branching enzyme IIb, its amylopectin contains more long-chain glucans than that of ordinary Indica and Japonica rice grains. Although boiled grains of ae rice cultivars are too hard and nonsticky for table rice, they are promising in terms of biofunctionality, such as prevention of diabetes. The present paper investigates the characterization of a novel group of four ae mutant rice cultivars (EM72, EM145, EM174, and EM189). They were subjected to the evaluation for their main chemical components, physical properties, and enzyme activities at different grain conditions (raw milled rice, roasted rice, boiled rice, and rice boiled after preroasting). These mutant rice grains are characterized by high apparent amylose, high protein and high glucose contents, high pasting temperature, high α-amylase activities, high resistant starch, and low degree of gelatinization. A novel method was developed to maintain the high resistant starch contents of gelatinized rice grains. Rice boild after preroasting showed a higher ratio of resistant starch and a lower amount of glucose than ordinary boiled rice. It became possible to produce high-quality and biofunctional pregelatinized rice flours by boiling with frozen fruits, such as tomatoes, after rice grains had been preroasted. These ae mutants were found to be suitable materials for rice/fruit or rice/vegetable products to serve as palatable, low-glucose, and high resistant starch rice products.     

Phytochemical diversity of cranberry (Vaccinium macrocarpon Aiton) cultivars by anthocyanin determination and metabolomic profiling with chemometric analysis

Originally native to the eastern United States, American cranberry ( Vaccinium macrocarpon Aiton, family Ericaceae) cultivation of native and hybrid varieties has spread across North America. Herein is reported the phytochemical diversity of five cranberry cultivars (Stevens, Ben Lear, Bergman, Pilgrim, and GH1) collected in the Greater Vancouver Regional District, by anthocyanin content and UPLC-TOF-MS metabolomic profiling. The anthocyanin content for biological replicates (n = 5) was determined as 7.98 ± 5.83, Ben Lear; 7.02 ± 1.75, Bergman; 6.05 ± 2.51, GH1; 3.28 ± 1.88, Pilgrim; and 2.81 ± 0.81, Stevens. Using subtractive metabonomic algorithms 6481 compounds were found conserved across all varietals, with 136 (Ben Lear), 84 (Bergman), 91 (GH1), 128 (Pilgrim), and 165 (Stevens) unique compounds observed. Principal component analysis (PCA) did not differentiate varieties, whereas partial least-squares discriminate analysis (PLS-DA) exhibited clustering patterns. Univariate statistical approaches were applied to the data set, establishing significance of values and assessing quality of the models. Metabolomic profiling with chemometric analysis proved to be useful for characterizing metabonomic changes across cranberry varieties.     

Sorption of volatile flavor compounds by microcellular cereal starch

Wheat starch based microcellular foam (MCF) forms of (dry) starch possess a significant percentage of micropores in the range of 5-14 A. The present study confirmed earlier preliminary studies that MCF starch (in a 0.25-1.0 mm diameter bead form) is effective in sorbing and lowering the headspace partial pressure of many volatile compounds in a manner similar (although less efficient) to that exhibited by other microcavity sorbants such as charcoal. It was found that the proportion of polar compounds sorbed was much greater than the proportion of nonpolar compounds. A major portion of the sorbed volatile compound was readily displaced from the MCF microcellular starch by the addition of water. These properties make this form of edible starch a potential useful carrier of flavor compounds for dried foods.     

Nutritional evaluation of ethanol-extracted lentil flours

Lentil flours were extracted with 80% ethanol at 25 and 50 degrees C for 1, 2, or 3 h. The various nitrogen fractions, soluble carbohydrates, three amino acids (Lys, His, and Tyr), available lysine, protein digestibility, and vitamins B(1) and B(2) were analyzed to evaluate the effect of extraction. Extraction resulted in an increase in the total nitrogen content of the extracted flours, with extraction temperature affecting the nature of the nitrogen (protein or nonprotein) content. There was also a large reduction in the oligosaccharides of the raffinose family, although the effect of temperature was appreciable only in the case of stachyose. There was hardly any effect on the concentrations of the amino acids analyzed or on protein digestibility; however, a positive correlation between protein digestibility and the available lysine was recorded in the samples. The vitamin B(1) and B(2) contents underwent variable decreases depending on extraction temperature.     

Use of the 1H nuclear magnetic resonance spectra signals from polyphenols and acids for chemometric characterization of cider apple juices

The low field region (5.8-9.0 ppm) corresponding to aromatic protons and the region 1.8-3.0 ppm of the (1)H NMR spectra were used for characterization and chemometric differentiation of 52 apple juices obtained from six cider apple varieties. The data set consisted of 14 integrated areas corresponding to resonances from acids and phenolic compounds. Multivariate procedures based on hierarchical cluster and discriminant analysis were performed on selected signals of the spectra to determine whether it was possible to distinguish the different juices. Cluster analysis was able to satisfactorily classify the six apple varieties. Discriminant analysis, by means of stepwise procedure for variables selection and leave-one-out for cross-validation, was applied to 40 samples from the year 2001, obtaining recognition and prediction abilities of 100%. The most discriminant variables corresponded to poliphenols, (-)-epicatechin, phloridzin-phloretin, and p-coumaric, chlorogenic, and malic acids. The classification model was applied to 12 samples from apples harvested in the years 2002 and 2003, and the prediction ability was 91.7%.