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.     

Constructing DNA fingerprinting of Hemarthria cultivars using EST-SSR and SCoT markers

DNA fingerprinting of known cultivars may provide much-needed data to assist with the identification of such cultivars. From 86 pairs of expressed sequence tag SSRs (EST-SSR) and 45 start-codon targeted polymorphism (SCoT) primers, eight pairs of EST-SSR primers and seven SCoT primers were chosen to construct the DNA fingerprinting of six Hemarthria cultivars in this study. Using genomic DNA from six cultivars, a total of eight pairs of EST-SSR primers were able to amplify 193 bands, producing an average of 24.1 bands per primer pair. The percentage of polymorphic bands (PPB) was 83.4 %, and the polymorphism information content (PIC) ranged from 0.480 to 0.695, with an average of 0.602. A total of seven SCoT primers amplified 105 bands with an average of 15 bands per sample. The PPB was 84.8 %, and the PIC ranged from 0.471 to 0.758, with an average of 0.612. The unweighted pair-group method with arithmetic mean dendrogram from EST-SSR and SCoT markers grouped the six Hemarthria cultivars into two major groups of the same. These clusters are in accordance with their known species and origin. Our results indicate a rich genetic diversity in these six Hemarthria cultivars. The six cultivars we assayed could be easily identified using these eight pairs of EST-SSR and seven pairs of SCoT primers.     

Studying the extent of genetic diversity among Gossypium arboreum L. genotypes/cultivars using DNA fingerprinting

Genetic diversity is an area of concern for sustaining crop yield. Information on genetic relatedness/diversity among Gossypium arboreum L. cultivars/genotypes is scanty. We have used random amplified polymorphic DNA (RAPD) analysis to assess the genetic divergence/relationship among 30 genotypes/cultivars of G. arboreum. Of 45 primers surveyed, 63% were polymorphic. Out of the total number of loci amplified, 36% were polymorphic. The calculated genetic similarity between the cultivars/genotypes was in the range of 47.05–98.73%. Two genotypes, HK-244 and Entry-17, were the most distantly related. The average genetic relatedness among all the genotypes was 80.46%. However, most of the cultivated varieties showed a close genetic relationship, indicating a narrow genetic base in comparison to the non-cultivated germplasm. The calculated coefficients were used to construct a dendrogram using the unweighted pair group of arithmetic means (UPGMA) algorithm, which grouped the genotypes/cultivars into two major and three smaller clusters. The study is the first comprehensive analysis of the genetic diversity of G. arboreum germplasm and identifies cultivars that will be useful in extending the genetic diversity of cultivated varieties and future genome mapping projects.     

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.     

Discriminating between village and commercial hunting of apes

Hunting is the major driver of large mammal decline in Central African forests. In slowly reproducing species even low hunting pressure leaves spatial gradients with wildlife density increasing with distance from transport routes and human settlements. Park management can use this pattern formation to identify sources of threats, but also to discriminate between different threat scenarios, such as the impact of subsistence vs. commercial hunting. We conducted an ape survey in the mountainous Moukalaba Doudou National Park, Gabon, to evaluate whether potential population gradients would emanate from the three human population centers in the region or the villages surrounding the park. Using generalized linear modeling we found hill slope as a good predictor of ape nest occurrence probability and the distance to human population centers a better predictor of ape nest density and ape nest group size than distance to villages. In fact ape nest density was three times lower at the park borders close to the human population centers than in the park’s interior. The results indicate that Moukalaba’s ape population is more impacted by commercial than subsistence hunting and suggest that park management should focus conservation efforts on the human population centers. We conclude that in particular for slowly reproducing species geographic information on wildlife population gradients are of additional value for guiding protected area management. The hunting impact on those species might be easily underestimated, if derived only from market surveys or transport route controls, where they are only rarely found.     

Kinetics of the stability of broccoli (Brassica oleracea Cv. Italica) myrosinase and isothiocyanates in broccoli juice during pressure/temperature treatments

The Brassicaceae plant family contains high concentrations of glucosinolates, which can be hydrolyzed by myrosinase yielding products having an anticarcinogenic activity. The pressure and temperature stabilities of endogenous broccoli myrosinase, as well as of the synthetic isothiocyanates sulforaphane and phenylethyl isothiocyanate, were studied in broccoli juice on a kinetic basis. At atmospheric pressure, kinetics of thermal (45-60 degrees C) myrosinase inactivation could be described by a consecutive step model. In contrast, only one phase of myrosinase inactivation was observed at elevated pressure (100-600 MPa) combined with temperatures from 10 up to 60 degrees C, indicating inactivation according to first-order kinetics. An antagonistic effect of pressure (up to 200 MPa) on thermal inactivation (50 degrees C and above) of myrosinase was observed indicating that pressure retarded the thermal inactivation. The kinetic parameters of myrosinase inactivation were described as inactivation rate constants (k values), activation energy (Ea values), and activation volume (Va values). On the basis of the kinetic data, a mathematical model describing the pressure and temperature dependence of myrosinase inactivation rate constants was constructed. The stability of isothiocyanates was studied at atmospheric pressure in the temperature range from 60 to 90 degrees C and at elevated pressures in the combined pressure-temperature range from 600 to 800 MPa and from 30 to 60 degrees C. It was found that isothiocyanates were relatively thermolabile and pressure stable. The kinetics of HP/T isothiocyanate degradation could be adequately described by a first-order kinetic model. The obtained kinetic information can be used for process evaluation and optimization to increase the health effect of Brassicaceae.     

Forest soil acidification assessment using principal component analysis and geostatistics

Soil acidification and consequent Al release is a problem particularly under forests in mountainous areas of the Czech Republic. It is controlled by a number of factors, like acid deposition, forest type, parent rock, altitude, etc. The Jizera Mountains region presents an area heavily influenced by acidification and forest decline. This paper focused on the effect of stand factors on spatial distribution of soil characteristics of the surface organic (O) and sub-surface (B) horizons from 98 sites using a combination of principal component analysis (PCA) and geostatistics. In the PCA, five principal components (PC) describing more than 70% of total variation were selected. The properties of the O and B horizons (pH, C, N, and S content, potentially dangerous Al forms) were in most cases separated, suggesting different processes and effects in each horizon. Spatial variation of PC scores was analysed using variograms, maps of their distribution were created using kriging. Spatial correlation with stand factors (altitude, slope aspect, forest type and age, soil unit, liming, and grass cover) was analysed using cross-variograms. The surface horizons are more sensitive to external influence (acid deposition, liming, grass expansion) and their spatial variation is stronger. The B horizons are more influenced by forest type (beech vs. spruce) and age, and by soil units (cambic vs. spodic horizons). The effect of stand factors is complex and often indirect. Nevertheless, used combination of pedometrical methods provided concise information about spatial variation and relationships between soil characteristics and the effect of stand factors.     

Classification of Ilex species based on metabolomic fingerprinting using nuclear magnetic resonance and multivariate data analysis

The metabolomic analysis of 11 Ilex species, I. argentina, I. brasiliensis, I. brevicuspis, I. dumosavar. dumosa, I. dumosa var. guaranina, I. integerrima, I. microdonta, I. paraguariensis var. paraguariensis, I. pseudobuxus, I. taubertiana, and I. theezans, was carried out by NMR spectroscopy and multivariate data analysis. The analysis using principal component analysis and classification of the (1)H NMR spectra showed a clear discrimination of those samples based on the metabolites present in the organic and aqueous fractions. The major metabolites that contribute to the discrimination are arbutin, caffeine, phenylpropanoids, and theobromine. Among those metabolites, arbutin, which has not been reported yet as a constituent of Ilex species, was found to be a biomarker for I. argentina,I. brasiliensis, I. brevicuspis, I. integerrima, I. microdonta, I. pseudobuxus, I. taubertiana, and I. theezans. This reliable method based on the determination of a large number of metabolites makes the chemotaxonomical analysis of Ilex species possible.     

Rapid differentiation of three Chamaecyparis species (Cupressaceae) grown in Taiwan using solid-phase microextraction-gas chromatography/mass spectrometry, cluster analysis, and principal component analysis

Three Chamaecyparis species (C. formosensis, C. obtusa, and C. obtusa var. formosana) are difficult to distinguish by the naked eye. Therefore, from the chemotaxonomic point of view, it would be valuable to find a simple and rapid method to differentiate these three Chamaecyparis species. In this study, the chemical compositions of biogenic volatile organic compounds (BVOCs) from mature leaves were analyzed using solid-phase microextraction-gas chromatography/mass spectrometry (SPME-GC/MS). Then cluster analysis (CA) and principal component analysis (PCA) were conducted for the BVOC constituents to reveal the differences among these three species. Results from SPME-GC/MS showed that the compositions of BVOCs from the three species were distinctly different. Moreover, these species were clearly differentiated according to the results of CA and PCA. In conclusion, the findings of this study suggest that SPME-GC/MS coupled with CA and PCA is a feasible and rapid technique to differentiate Chamaecyparis species with similar morphological characteristics.     

The effect of post-harvest and packaging treatments on glucoraphanin concentration in broccoli (Brassica oleracea var. italica)

The effects of post-harvest and packaging treatments on glucoraphanin (4-methylsulfinylbutyl glucosinolate), the glucosinolate precursor of anticancer isothiocyanate sulforaphane [4-methylsulfinylbutyl isothiocyanate], were examined in broccoli (Brassica oleracea var. italica) during storage times. The results showed that at 20 degrees C, 55% loss of glucoraphanin concentration occurred in broccoli stored in open boxes during the first 3 days of the treatment and 56% loss was found in broccoli stored in plastic bags by day 7. Under both air and controlled atmosphere (CA) storage, glucoraphanin concentration appeared to fluctuate slightly during 25 days of storage and the concentrations under CA was significantly higher than those stored under air treatment. In modified atmosphere packaging (MAP) treatments, glucoraphanin concentration in air control packaging decreased significantly whereas there were no significant changes in glucoraphanin concentration in MAP with no holes at 4 degrees C and two microholes at 20 degrees C for up to 10 days. Decreases in glucoraphanin concentration occurred when the broccoli heads deteriorated. In the present study, the best method for preserving glucoraphanin concentration in broccoli heads after harvest was storage of broccoli in MAP and refrigeration at 4 degrees C. This condition maintained the glucoraphanin concentration for at least 10 days and also maintained the visual quality of the broccoli heads.     

Characterization of puff-by-puff resolved cigarette mainstream smoke by single photon ionization-time-of-flight mass spectrometry and principal component analysis

Soft single photon ionization-time-of-flight mass spectrometry (SPI-TOFMS) and principal component analysis (PCA) were applied for the characterization and discrimination of the chemical patterns of all individual cigarette puffs from the 2R4F University of Kentucky research reference cigarette. The SPI-TOFMS was connected to a smoking machine, and 10 cigarettes were smoked under defined smoking conditions. A total of 41 detected mass signals could be clearly assigned to smoke constituents (e.g., unsaturated hydrocarbons, aromatic species, sulfurous compounds, and nitrogen-containing substances). For further analysis, the on-line recorded mass signals were added up for each cigarette puff resulting in a single summed mass spectrum for each puff. The so-achieved puff-by-puff resolved yields were additionally normalized by the corresponding total ion signal, which eliminated the influences of varying amounts of burnt tobacco. These values were incorporated into a PCA to find differences and similarities in the chemical patterns of the individual cigarette puffs. In addition, absolute (without normalization) and normalized puff resolved yields were used to clarify occurring trends. Thereby, it was shown that the chemical pattern of the first cigarette puff was very unique, whereby extraordinary high yields of unsaturated hydrocarbons are mainly responsible for this. Depending on the smoking procedure, the chemical pattern of the second puff can also be separated from the first and the third puff. In this case, nitrogen-containing substances play an important role. Puffs three to eight show only small but observable differences. These changes are greater influenced by oxygen-containing and sulfurous smoke constituents. The findings reveal that the overall chemical patterns of machine-smoked cigarette puffs vary quite a lot during the smoking process. This lets us assume that the burden of hazardous compounds for the human smoker also differs from puff to puff.     

Classification and structural analysis of live and dead Salmonella cells using Fourier transform infrared spectroscopy and principal component analysis

Fourier transform infrared spectroscopy (FT-IR) was used to detect Salmonella Typhimurium and Salmonella Enteritidis food-borne bacteria and to distinguish between live and dead cells of both serotypes. Bacteria cells were prepared in 10(8) cfu/mL concentration, and 1 mL of each bacterium was loaded individually on the ZnSe attenuated total reflection (ATR) crystal surface (45° ZnSe, 10 bounces, and 48 mm × 5 mm effective area of analysis on the crystal) and scanned for spectral data collection from 4000 to 650 cm(-1) wavenumber. Analysis of spectral signatures of Salmonella isolates was conducted using principal component analysis (PCA). Spectral data were divided into three regions such as 900-1300, 1300-1800, and 3000-2200 cm(-1) based on their spectral signatures. PCA models were developed to differentiate the serotypes and live and dead cells of each serotype. Maximum classification accuracy of 100% was obtained for serotype differentiation as well as for live and dead cells differentiation. Soft independent modeling of class analogy (SIMCA) analysis was carried out on the PCA model and applied to validation sample sets. It gave a predicted classification accuracy of 100% for both the serotypes and its live and dead cells differentiation. The Mahalanobis distance calculated in three different spectral regions showed maximum distance for the 1800-1300 cm(-1) region, followed by the 3000-2200 cm(-1) region, and then by the 1300-900 cm(-1) region. It showed that both of the serotypes have maximum differences in their nucleic acids, DNA/RNA backbone structures, protein, and amide I and amide II bands.     

Spectral fingerprinting: sediment source discrimination and contribution modelling of artificial mixtures based on VNIR-SWIR spectral properties

Purpose

Knowledge of the origin of suspended sediment is important for improving our understanding of sediment dynamics and thereupon support of sustainable watershed management. An direct approach to trace the origin of sediments is the fingerprinting technique. It is based on the assumption that potential sediment sources can be discriminated and that the contribution of these sources to the sediment can be determined on the basis of distinctive characteristics (fingerprints). Recent studies indicate that visible–near-infrared (VNIR) and shortwave-infrared (SWIR) reflectance characteristics of soil may be a rapid, inexpensive alternative to traditional fingerprint properties (e.g. geochemistry or mineral magnetism).

Materials and methods

To further explore the applicability of VNIR-SWIR spectral data for sediment tracing purposes, source samples were collected in the Isábena watershed, a 445 km² dryland catchment in the central Spanish Pyrenees. Grab samples of the upper soil layer were collected from the main potential sediment source types along with in situ reflectance spectra. Samples were dried and sieved, and artificial mixtures of known proportions were produced for algorithm validation. Then, spectral readings of potential source and artificial mixture samples were taken in the laboratory. Colour coefficients and physically based parameters were calculated from in situ and laboratory-measured spectra. All parameters passing a number of prerequisite tests were subsequently applied in discriminant function analysis for source discrimination and mixing model analyses for source contribution assessment.

Results and discussion

The three source types (i.e. badlands, forest/grassland and an aggregation of other sources, including agricultural land, shrubland, unpaved roads and open slopes) could be reliably identified based on spectral parameters. Laboratory-measured spectral fingerprints permitted the quantification of source contribution to artificial mixtures, and introduction of source heterogeneity into the mixing model decreased accuracies for some source types. Aggregation of source types that could not be discriminated did not improve mixing model results. Despite providing similar discrimination accuracies as laboratory source parameters, in situ derived source information was found to be insufficient for contribution modelling.

Conclusions

The laboratory mixture experiment provides valuable insights into the capabilities and limitations of spectral fingerprint properties. From this study, we conclude that combinations of spectral properties can be used for mixing model analyses of a restricted number of source groups, whereas more straightforward in situ measured source parameters do not seem suitable. However, modelling results based on laboratory parameters also need to be interpreted with care and should not rely on the estimates of mean values only but should consider uncertainty intervals as well.     

Sediment source analysis using the fingerprinting method in a small catchment of the Loess Plateau,China

Journal of Soils and Sediments - This paper aims to use the composite fingerprinting method to reconstruct the environmental history after the Grain-for-Green Project and to provide effective...     

Quince (Cydonia oblonga miller) fruit characterization using principal component analysis

This paper presents a large amount of data on the composition of quince fruit with regard to phenolic compounds, organic acids, and free amino acids. Subsequently, principal component analysis (PCA) is carried out to characterize this fruit. The main purposes of this study were (i) the clarification of the interactions among three factors-quince fruit part, geographical origin of the fruits, and harvesting year-and the phenolic, organic acid, and free amino acid profiles; (ii) the classification of the possible differences; and (iii) the possible correlation among the contents of phenolics, organic acids, and free amino acids in quince fruit. With these aims, quince pulp and peel from nine geographical origins of Portugal, harvested in three consecutive years, for a total of 48 samples, were studied. PCA was performed to assess the relationship among the different components of quince fruit phenolics, organic acids, and free amino acids. Phenolics determination was the most interesting. The difference between pulp and peel phenolic profiles was more apparent during PCA. Two PCs accounted for 81.29% of the total variability, PC1 (74.14%) and PC2 (7.15%). PC1 described the difference between the contents of caffeoylquinic acids (3-O-, 4-O-, and 5-O-caffeoylquinic acids and 3,5-O-dicaffeoylquinic acid) and flavonoids (quercetin 3-galactoside, rutin, kaempferol glycoside, kaempferol 3-glucoside, kaempferol 3-rutinoside, quercetin glycosides acylated with p-coumaric acid, and kaempferol glycosides acylated with p-coumaric acid). PC2 related the content of 4-O-caffeoylquinic acid with the contents of 5-O-caffeoylquinic and 3,5-O-dicaffeoylquinic acids. PCA of phenolic compounds enables a clear distinction between the two parts of the fruit. The data presented herein may serve as a database for the detection of adulteration in quince derivatives.     

Preparative method for gas chromatographic/mass spectral analysis of trace quantities of pesticides in fish tissue.

A large capacity, low efficiency pesticide cleanup method is combined with a small capacity, high efficiency method for gas chromatographic/mass spectral analysis of fish tissue. Trace chemicals are extracted from the tissue, removed from the bulk of the co-extracted lipids through selective desorption from Micro Cel-E, and isolated from the remaining lipids by gel permeation chromatography. The procedure is capable of cleaning up the extract from several hundred grams of fish, minimizes sample contamination, and permits identification of xenobiotic chemicals present at ng/g concentrations.     

Heat inactivation and reactivation of broccoli peroxidase

Heat inactivation characteristics differed for acidic (A), neutral (N), and basic (B) broccoli peroxidase. At 65 degrees C, A was the most heat stable followed by N and B. The activation energies for denaturation were 388, 189, and 269 kJ/mol for A, N, and B, respectively. Reactivation of N occurred rapidly, within 10 min after the heated enzyme was cooled and incubated at room temperature. The extent of reactivation varied from 0 to 50% depending on the isoenzyme and heating conditions (temperature and time). The denaturation temperature allowing the maximum reactivation was 90 degrees C for A and horseradish peroxidase (HRP) and 70 and 80 degrees C for B and N, respectively. In all cases, heat treatment at low temperatures for long times prevented reactivation of the heated enzymes. Calcium (5 mM) increased the thermal stability of N and B but had no effect on reactivation. The presence of 0.05% bovine serum albumin decreased thermal stability but increased the extent of reactivation of A..