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Producción Científica, In the present study, the mineral composition of seventy-one bee pollen samples from four different apiaries was determined by means of inductively coupled plasma-optical emission spectrometry. The results showed that there were no significant differences in relation to the overall mineral content per sample in terms of the apiary of origin or the harvesting period; the most common elements were phosphorus and potassium with concentrations ranging from 2.3 to 5.1 g/kg (dry weight). Moreover, the mineral content of the samples analyzed was similar to or higher than the recommended as well-balanced food for bees. Regarding the nutritional value for humans, bee pollen samples could be considered as a food rich in copper, iron, magnesium, manganese, and phosphorus. Finally, a canonical discriminant analysis was performed, and it was found that the apiary of origin could be distinguished by using the first three canonical functions; furthermore, over 90% of the samples could be correctly assigned to their corresponding apiary. The results were even better as regards the harvesting period, as only the first two canonical functions were sufficient to make a distinction between the different harvesting periods, resulting in a perfect match (100% of success rate)., Ministerio de Economía y Competitividad (RTI2018-096268-B-100), Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (RTA 2015-00013-C03-01 and 03), FEDER and FSE (project AGRISOST-CM S2018/BAA-4330)

Provenance of seafood items is a concern for consumers and importers alike. Elemental profiling has been put forth as a potential tool to improve seafood traceability. Whiteleg shrimp Litopenaeus vannamei collected from farms in Ecuador, India, Indonesia, Vietnam, and Thailand were classified to country of origin based on element concentrations in muscle tissue. Shrimp were dried, digested, and analyzed via ICP-MS. Out of the 41 elements investigated, 33 are reported as being above detection limits. Twenty-eight elements were statistically different across countries, and of these 28, Ecuador had unique group membership in 7. A random forest classification model utilizing 16 elements had an overall accuracy of 91% of correctly classified samples to country of origin. A canonical discriminant analysis was conducted to understand the variation in the data and identify elements that were important to differentiation in multi-dimension space. Elements identified as important contributors were Al, As, B, Ca, Co, Cs, Sr, and V. This study shows that shrimp from Ecuador tend to be more mineralized than shrimp from Asia, and classification models can discern samples from these countries successfully. This demonstrates the potential of a traceability database for cultured shrimp products from predominant production countries.

There is an urgent need for screening patients of having a communicable viral disease to cut infection chains. We could recently demonstrate that MCC-IMS of breath is able to identify Influenza-A infected patients. With decreasing Influenza epidemic and upcoming SARS-CoV-2 infections we extended our study to the analysis of patients with suspected SARS-CoV-2 infections. 51 patients, 23m, 28f, aged 64 ± 16 years, were included in this study. Besides RT-PCR analysis of nasopharyngeal swabs all patients underwent MCC-IMS analysis of breath. 16 patients, 7m, 9f, were positive for SARS-CoV-2 by RT-PCR. There was no difference in gender or age according to the groups. Stepwise canonical discriminant analysis could correctly classify the infected and non-infected subjects in 98% by cross-validation. Afterwards we combined the Influenza-A sub study and the SARS-CoV-2- sub study for a total of 75 patients, 34m, 41f, aged 64·8 ± 1·8 years, 14 positive for Influenza-A, 16 positive for SARS-CoV-2, the remaining 44 patients were used as controls. In one patient RT-PCR was highly suspicious of SARS-CoV-2 but inconclusive. There was no imbalance between the groups for age or gender. 97·3% of the patients could be correctly classified to the respective group by discriminant analysis. Even the inconclusive patient could be mapped to the SARS-CoV-2 group applying the discrimination function. Conclusion: MCC-IMS is able to detect SARS-CoV-2 infection and Influenza-A infection in breath. As this method provides exact, fast non-invasive diagnosis it should be further developed for screening of communicable viral diseases. Study Registration: NCT04282135. Funding Statement: There was no external funding. Declaration of Interests: Gunther Becher is Consultant to Graupner medical solutions GmbH, Geyer, Germany Gunther Becher holds parts of the patent for the cluster analysis (EP 2 729 801 B1) All other authors state that there is no conflict of interests. Ethics Approval Statement: After written consent breath samples were taken and analysed by MCC-IMS. The study was approved by the Ethics Committee of Erlangen University, Erlangen, Germany (Nr 426_18B).

This study was conducted to characterize the indigenous goat population in five zones vis-a-vis South Gondar (S-Gondar), Jimma, Sidama, Gamo, and North Shoa (N-Shoa) representing various agroecological zones of Ethiopia using morphometric traits. Seven morphometric traits were measured from 2540 goats of both sex from various age groups ranging from yearling to four years and above. The traits scored were live weight (LW), body length (BL), wither height (WH), heart girth (HG), rump length (RL), rump width (RW) and ear length (EL). A multivariate canonical discriminant analysis in combination with cluster and discriminant analysis was applied to identify the combination of variables that best differentiate the five goat populations based on morphometric traits. Results indicated that the N-Shoa goats demonstrated the largest LW, HG and RL and could be considered as large-framed goat types. The S-Gondar goats had the highest WH describing them as the tallest goat types. Jimma goats had the smallest morphometric measurements and could be classified as small-sized goat types. Gamo goats had the lowest WH with a relatively larger RW being the shortest amongst the studied goat breeds. The cluster analyses showed that goats of Jimma tended to group separately whilst those of N-Shoa and S-Gondar as well as Sidama and Gamo clustered closely. The stepwise discriminant analysis indicated that RL followed by RW were the most discriminating variables to separate the five goat populations. The canonical discriminant analysis determined four canonical variables (CAN) of which CAN1 (RL and HG) and CAN2 (RW, EL, and LW) accounted for 80.2 and 14.3% of the total variation, respectively. The canonical discriminant analysis further showed that the Gamo goat is distinct from the other four populations. All Mahalanobis distances among goat population were significant (p

This is the first report on population differentiation based on composition of three different compound classes ( n -alkanes, primary alcohols and diterpenes) in the epicuticular waxes of European black pine ( Pinus nigra ) from Balkan Peninsula and Southern Carpathians. The n -hexane extracts of 263 samples, originating from 15 native populations of four P. nigra subspecies ( nigra , dalmatica , banatica and pallasiana ), were investigated by GC-MS and GC-FID analyses. In all studied populations n -alkanes represent the most abundant compound group, while the contents of diterpenes and alcohols were lower and variable. Multivariate statistical analyses (Canonical Discriminant Analysis and Agglomerative Hierarchical Clustering) suggest existence of two clearly differentiated chemical entities with the basic difference in the content of primary alcohols (especially cis -9-octadecen-1-ol and 1-hexadecanol). The first group (low alcohol content) included all populations of ssp. nigra , ssp. dalmatica and ssp. banatica , as well as the two northernmost populations of ssp. pallasiana from Serbia and Bulgaria, while the second group (high alcohol content) comprised individuals from Greek and Macedonian populations of ssp. pallasiana . According to the recently proposed concept of ancient split of major genetic lineages of P. nigra , both chemical entities detected in this study belong to the same (Balkan Peninsula) genetic group. Taxonomic implications of given results are briefly discussed in relation with previous data based on morphological and molecular characters.

Capers and caper berries (Capparis spinosa L.) from different Sicilian localities and marked by Protected Geographic Indication (PGI) and Protected Designation of Origin (PDO), along with corresponding non Sicilian commercial samples, were subjected to several analytical and multivariate techniques in an attempt to predict the provenance of Capparis spinosa L. within the Sicilian region, and to discriminate Sicilian products from the non Sicilian counterpart. All samples were screened in terms of FA composition and elemental fingerprint. Then, principal component analysis (PCA) and canonical discriminant analysis (CDA) tested the capacity of both chemical classes to differentiate and classify capers and caper berries according to the geographical provenance. About 99% of total samples were discriminated by FAs, as they did not allow for a correct geographical classification of 7 samples of capers and related caper berries. Conversely, elements provided an excellent sample discrimination and prediction over the four locations (100%), revealing specific variables of classification (Mg, K, and Ca). For the first time, a reliable traceability system based on the elemental profiles of caper and caper berries was proposed. It could be useful for protecting the authenticity of Sicilian PGI and PDO capers and caper berries.

To clarify the taxonomy and biostratigraphy of Southwest Pacific populations currently identified as Fohsella peripheroronda a morphometric study is reported on the shape of its aperture in collections from DSDP Sites 588A and 593, and from the stratotype of the New Zealand Lillburnian Stage. This material is compared with Globorotalia partimlabiata from Serravallian strata in Sicily. Shape analyses use 50 equally-spaced coordinates along the margin of the apertural re-entrant of the last-preserved chamber. Data are aligned by the Procrustes algorithm and projected onto principal component axes. Canonical discriminant analysis of these scores shows that convexity of the margin increases clinally. The cline is interpreted as primary evidence for a previously unrecognized lineage for which a provisional taxonomy is advanced. Globorotalia partimlabiata, which has individuals with strongly convex margins, represents the climax of the cline. The highest occurrence of its ancestor, recognized here informally as Globorotalia cf. peripheroronda, is determined by the highest sample whose mean shape does not differ significantly from its earliest representative at Site 593. There and at Site 588A that datum is close to, or within, Miocene isotope event Mi-3b. The architectural history of the lineage differs from the tropical fohsellids and its relation to them is unresolved.

A screening method based on meat quality parameters and production traits for detecting the effects of illegal administration of dexamethasone in Friesian bulls was assessed. Twenty finishing bulls were divided into an untreated control group (n=8) and two treatment groups receiving dexamethasone orally at dosages of 1.4 (n=6) or 0.7 (n=6)mg per head per day for 60 days. The animals were slaughtered 26days after cessation of treatment. Thirty-six parameters were measured on live animals, carcasses and samples of the longissimus thoracis muscle. The production traits were similar between groups, but there were significant differences in meat quality between treatment groups. The higher dosage of dexamethasone improved meat tenderness, while the lower dosage resulted in more saturated red meat, with increased meat cooking shrinkage and cooking loss. The use of a portable 'electronic nose' as a screening tool was not successful in discriminating between treated and untreated meat. These results indicate that a multivariable approach using canonical discriminant analysis may be a complementary tool to identify meat from animals illegally treated with dexamethasone, based on several parameters (meat flavour, cooking and thawing loss, tenderness, colour and live weight gain), which are part of the normal analysis of meat quality.

Advanced techniques were required to determine geographical origins and production methods of aquatic food due to frequent fraudulent misdescription of food content on product labels in the market. In this study, the elemental profile of 96 salmonids samples were detected by inductively coupled plasma atomic emission spectrometry (ICP-AES) and used to identify production methods and geographical origins of salmonids. Moreover, effects of fish size and harvest time on the elemental compositions in salmonids were investigated. A total of 14 elements (Al, Ca, Co, Cr, Cu, Fe, Ga, K, Mg, Mn, Na, Ni, Sr, and Zn) were determined in salmonids. Of these, elements Fe, K, Na, Mn, and Zn, were varied in fish collected in different harvest times, and elements Al, Fe, Ga, Mn, and Zn were related to fish sizes, six elements (Ga, K, Mg, Na, Ni, and Sr) were significantly different between freshwater-cultured and seawater-cultured salmonids, 13 elements (Al, Ca, Co, Cr, Fe, Ga, K, Mg, Mn, Na, Ni, Sr, and Zn) were significantly different among different areas. Three elements (K, Mg, and Na) and 12 elements (Ca, Co, Cr, Fe, Ga, K, Mg, Mn, Na, Ni, Sr, and Zn) were selected by SDA for identifying production methods and geographical origins of salmonids, respectively. Canonical discriminant analysis (CDA) visualized the difference in salmonids cultured by different production methods or from different areas. Multivariate statistics, linear discrimination analysis (LDA), k-nearest neighbor (KNN), and random forest (RF) demonstrated the validity of the elemental profile in distinguishing production methods and geographical origins of salmonids. The results showed that production methods of salmonids were distinguished by LDA, KNN, and RF with an overall accuracy of >94.74%. Among these, the highest accuracy was achieved by KNN with an accuracy of 100%. For authenticating geographical origins of salmonids, the accuracy of KNN (> 94.74%) was highest. The element profile was effective to distinguish production methods and geographical origins of salmonids, which were less affected by harvest time and fish size.

The geochemical fractionation and potential mobilization of Co, Cu, Ni, and Zn were studied in thirteen soil profiles originating from Germany and Egypt to assess the potential mobilization of these potentially toxic metals. The German soils were classified as Eutric Fluvisols, Tidalic Fluvisols, Haplic Gleysols, and Calcic Luvisols, and the Egyptian soils as Eutric Fluvisols, Sodic Fluvisols, and Haplic Calcisols. The geochemical fractions (acid soluble (F1), reducible (F2), oxidizable (F3), and residual (F4) fraction) of the metals were sequentially extracted using the sequential extraction technique of the Commission of the European Communities Bureau of Reference (BCR). The maximal total concentrations (mg kg − 1 ) of Cu (3242), Ni (105), and Zn (1672) were in the German Eutric Fluvisols, while the maximal concentrations of Co (37) were in the Egyptian Eutric Fluvisols, and those values exceeded the international maximum allowable soil concentrations. The values of enrichment and contamination factors exhibit a clear indication of dramatic contamination by Cu and Zn at the Eutric Fluvisols along the Wupper River, Germany. The acid soluble fraction of all metals (except for Ni in the Calcic Luvisols) was higher in the German soils than the Egyptian soils. The reducible fraction of Co, Cu, Ni, and Zn was the dominant non-residual fraction (as precentages of total) in all Egyptian soils and in the German Eutric Fluvisols as well as for Zn in the Tidalic Fluvisol and Co in the Calcic Luvisols. The potential mobile fraction (PMF = ∑ F1 − F3) of Co, Cu, Ni, and Zn accounted (% of total) for 39–61, 15–60, 21–57, and 6–44, respectively in the Egyptian soils, while it accounted for 14–70, 11–92, 2–73, and 8–89, respectively in the German soils. The high PMF of the metals in the German Eutric Fluvisols, Haplic Gleysols, and Sodic Fluvisols might reflect that the sources of these metals are of anthropogenic origin here. However, the dominance of the metals residual fraction in the Egyptian soils supports the assumption of the geogenic origin of these metals in these soils. The canonical discriminant analysis as a multivariate statistical procedure was applied and differentiated the soils according to their geochemical behavior into four clusters i.e., 1) Eutric Fluvisols, Calcic Luvisols, and Haplic Calcisols; 2) Egyptian Fluvisols (Eutric and Sodic); 3) Haplic Calcisols; and 4) Tidalic Fluvisols. In conclusion, the potential risk of the metals in the anthropogenic polluted soils is higher than in the soils naturally enriched with these metals. Therefore, remediation approaches may be needed in the German Eutric Fluvisols, Haplic Gleysols, and Sodic Fluvisols.

Shrimp from three major exporting countries – India, Vietnam, and Thailand – were identified to country of origin by elemental profiling. Concentrations of 23 elements, including essential macro- and micro-nutrients and non-essential trace elements, in headless shell on shrimp (HLSO) samples were analyzed by ICP-AES. Elemental concentrations in shrimp showed high variation. Multivariate statistics including principal component analysis, stepwise discriminant analysis, Kernel method, and canonical discriminant analysis demonstrated the validity of elemental profiling in distinguishing aquacultured shrimp from different countries. However, it was not possible to reach definitive conclusions about which elements are the best descriptors for each region. The method was also tested as a means of differentiating shrimp produced to area of origin for two areas in Thailand, three provinces in Vietnam and India. All the multivariate statistical analysis demonstrated that the separation on a smaller scale was not as reliable as on the country scale.

The potential of diet-induced differences in the fatty acid profile of muscle to discriminate beef from different feeding systems and its potential use as an authentication tool was investigated. Three canonical discriminant models were built and validated using the fatty acid profile of beef from animals fed solely on pasture or cereal-based concentrates for 11 months or on various pasture/grass silage/concentrate combinations, including concentrates enriched with plant oils. Results indicated that models could successfully discriminate between grass-, partially grass- and concentrate-fed beef (accuracy = 99%) and between grass-fed beef and beef from animals supplemented with plant oils (accuracy = 96%). The approach also showed potential for distinguishing between beef from exclusively pasture-fed cattle and beef from cattle fed on pasture preceded by a period on ensiled grass (accuracy = 89%). Models were also applied to beef samples from 9 different countries. Of 97 international samples, including samples stated to be grass-fed, only 5% were incorrectly classified as Irish-grass-fed beef. These results suggested that the models captured traits in the fatty acid profile that are characteristic of Irish grass-fed beef and that this feature could be used for distinguishing Irish grass-fed beef from beef from other regions.

Phospholipid fatty acid (PLFA) profiles were studied for their potential to discriminate between freshwater-cultured and seawater-cultured salmonids. The effects of culture season and fish size on the PLFAs compositions in salmonids were investigated to assess their effects on the discrimination results. Totally 19 PLFAs of salmonids were determined via gas chromatography (GC). Among them, 12 PLFAs were significantly different between freshwater-cultured and seawater-cultured salmonids. But only four PLFAs in salmonids cultured in different seasons and two PLFAs in fish with different size were significantly different. The PLFAs, including 18:1n9, 24:1n9, 20:5n3, 20:3n6, ∑MUFA, and ∑n6PUFA, were selected via stepwise discriminant analysis (SDA) for further multivariate statistics analysis. Principal component analysis (PCA) and canonical discriminant analysis (CDA) visualized the differences of the PLFAs profiles in fish cultured in freshwater and seawater. The linear discrimination analysis (LDA) and random forest (RF) were used to create a discrimination model that can authenticate salmonids farmed in freshwater and seawater. An overall correct classification rate of 95.89%, a cross-validation rate of 93.15%, and a predictive classification rate of 100% were achieved by the LDA. The RF achieved an overall correct classification rate of 95.89%, a cross-validation rate of 95.89%, and a predictive classification rate of 100%. These results indicate that PLFAs profiles can be used to effectively distinguish samples cultured in freshwater and seawater while less affected by season and fish size. Therefore, PLFAs analysis is a promising method for the accurate identification of salmonids cultured in freshwater and seawater.

In this paper, population continuity and discontinuity in northern China are explored using craniometric analyses from two archaeological sites, Longxian (Warring States) and Qi Li Cun (Han Dynasty). Neither population has been previously studied. Artefactual evidence shows the individuals from Qi Li Cun were Xianbei, descendants from Mongolia. Longxian is from further south in the central plains at an earlier time, thus, we expect to observe variability between these groups. In total, 24 cranial measurements were obtained on 66 crania from these sites. Howells's cranial measurements on Anyang (42 crania) and Hainan (83 crania) Chinese samples were included for comparative purposes. Less variability is expected between Longxian and Howells's Chinese data due to geographic and temporal similarity. With closer geographic and temporal affinity with Anyang, the expectation is for Longxian and Anyang to be similar. Few statistical differences exist between Longxian and Qi Li Cun; this was supported by the similarity found through principal components analysis (PCA). Regardless of sex, canonical discriminant analysis shows clustering of Longxian and Qi Li Cun separate from those of Anyang and Hainan. Their similarity indicates the people from Longxian and Qi Li Cun likely share Mongolian ancestry. Our results, supported by other studies, suggest that despite temporal differences, Mongolians living in China during the Warring States and Han dynasty retained their cultural and genetic Mongolian identity. These data add valuable bioarchaeological information regarding the peopling of northern China during a crucial period of cultural and political change in the Early Bronze Age and Iron Age.

A study is presented of the real possibilities of glucosinolate content and chemometrics (canonical discriminant analysis) to differentiate bee pollen samples from four different apiaries (Fuentelahiguera, Monte, Pistacho, Tio Natalio) located in the same geographical area. Fifteen intact-glucosinolates were quantified by means of ultra-performance liquid chromatography coupled to a quadrupole time-of-flight mass detector in forty-nine bee pollen samples. Glucosinolate residues were detected in most of the samples, and these differed in number and concentration. It was possible to directly differentiate one of the apiaries (Fuentelahiguera) from the other three (Monte, Pistacho y Tio Natalio) by comparing glucosinolate content. These three apiaries were differentiated by means of the first two canonical variables obtained from a canonical discriminant analysis. Following this analysis, more than 88% of the samples could be assigned correctly to the Pistacho and Monte apiaries, and 100% to the Tio Natalio apiary.

The fatty acid (FA) profiles of lamb muscle and adipose tissue originating from ten different grazing areas in North Macedonia and an assessment of whether the meat origin could be distinguished on the basis of FA profile are presented. Muscle and adipose tissues of three-month-old male lambs (crossbreds of autochthonous Ovcepolian and Wurttemberg) reared on spring pastures were studied. Statistically significant differences in the individual FA contents, FA groups and FA ratios were observed between lamb tissues from the different geographic regions. Canonical discriminant analysis showed there was a significant linear divergence between tissues from almost all examined regions. The greatest weight in the differentiation of the different areas showed fatty acid ratios, C18:3n3, C18:1n9c and C20:5n3 for the muscle tissue, as well as C18:1n9c, C18:2n6c, C16:1 and C17:1 for the adipose tissue. This showed that the FA composition of muscle and adipose tissue obtained from lambs reared on pasture could serve as a useful indicator to aid differentiation of its geographic origin but it should be confirmed through further replicated studies.

Salmonid samples collected from two sites in different aquaculture areas (Yantai and Liujiaxia, China) in four seasons were subjected to multi-element analysis. The amounts of 18 elements in fish were measured by inductively coupled plasma atomic emission spectrometry (ICP-AES). The results showed that concentrations of elements in fish from Yantai were stable with seasonal alternation. However, the element concentrations and compositions of fish obtained from Liujiaxia were vulnerable to seasonal change. Principal component analysis (PCA) and canonical discriminant analysis (CDA) were used to visualize the regional and seasonal distribution of samples, and it was determined that CDA was more distinct than PCA. To determine if seasonal effects would influence the discrimination of the geographical origin of salmonid, multivariate statistics including linear discriminant analysis (LDA), k-nearest neighbor (KNN), and partial least squares discriminant analysis (PLS-DA) were used to discriminate fish samples from the two different areas. The results showed that all discrimination techniques could effectively distinguish samples while remaining unaffected by seasonal effects.

In this paper, we obtain the sufficient conditions to determine the consistency of a variable selection method based on a generalized information criterion in canonical discriminant analysis. To examine the consistency property, we use a high-dimensional asymptotic framework such that as the sample size n goes to infinity, then the ratio of the length of the observation vector p to the sample size, p ∕ n , converges to a constant that is less than one even if the dimension of the observation vector also goes to infinity. Using the derived conditions, we propose a consistent variable selection method. From numerical simulations, we show that the probability of selecting the true model by our proposed method is high even when p is large. Further, the advantage of the proposed method is demonstrated by a real data.

The administration of anabolic agents in farm animals to improve meat production has been prohibited in EU, due to the potential risks to human health. Meat quality was investigated to detect the effects of illegal administration of dexamethasone or prednisolone or 17β-estradiol on Charolais bulls. Three groups of 6 bulls were treated and 12 bulls were the control. Meat quality parameters were measured on live animals, carcasses and on samples of Longissimus thoracis and multivariate statistical data analysis was applied. In Charolais bulls, these parameters were affected by growth promoter administration and the multivariate canonical discriminant analysis was able to distinguish between treated and untreated animals mainly due to three electronic nose’s parameters, 24 h carcass temperature and drip loss. Therefore, meat quality control and the multivariate analysis could be useful as a first screening to address targeted controls on farms suspected of illicit use of growth promoters.

Espresso coffee beverages prepared from pure origin roasted ground coffees from the major world growing regions (Brazil, Ethiopia, Colombia, India, Mexico, Honduras, Guatemala, Papua New Guinea, Kenya, Cuba, Timor, Mussulo and China) were characterized and compared in terms of their mineral content. Regular consumption of one cup of espresso contributes to a daily mineral intake varying from 0.002% (sodium; Central America) to 8.73% (potassium; Asia). The mineral profiles of the espresso beverages revealed significant inter- and intra-continental differences. South American pure origin coffees are on average richer in the analyzed elements except for calcium, while samples from Central America have generally lower mineral amounts (except for manganese). Manganese displayed significant differences (p < 0.05) among the countries of each characterized continent. Intercontinental and inter-country discrimination between the major world coffee producers were achieved by applying canonical discriminant analysis. Manganese and calcium were found to be the best chemical descriptors for origin.

Elemental analysis (Al, Ca, Cr, Cu, Fe, K, Mg, Mn, Na, P, S, Se, and Zn) of fillets of channel catfish Ictalurus punctatus and hybrid catfish (♀ I. punctatus × ♂ blue catfish Ictalurus furcatus) from fertilized ponds and of hybrid catfish that received feed was performed using an inductively coupled plasma atomic emission spectrometry (ICP-AES). Fillets of samples of hybrid and channel catfish in fertilized ponds did not differ in composition for most of the elements analyzed. Multivariate statistical methods including principal component analysis (PCA), canonical discriminant analysis (CDA) and k-nearest-neighbor analysis were used to separate Ictalurid catfish to the two culture methods based on chemical composition. The three methods each demonstrated that fillets from fish that received feed could be differentiated from fillets of fish cultured in fertilized ponds. Fish from fertilized ponds rely on natural food organisms in the same manner as wild-caught fish. This study demonstrated the potential of chemical profiling combined with multivariate statistical methods for verifying method of production – aquaculture versus wild-caught.

5 pages, 2 figures, 1 table, The otoliths of John's snapper (Lutjanus johnii) from the Persian Gulf and the Oman Sea were studied to evaluate whether otolith shape can be used to differentiate populations. John's snapper is a relevant commercially exploited species in the Arabian Sea, and the identification of different stocks is a major issue for fishery management. Otolith weight was used to examine the growth rate of both populations and as an indicator of similar ambient water composition. Otolith contours were obtained using wavelet functions, from the finest (WLT 1) to coarsest (WLT 9) scales, and then compared by principal components (PCA) using a canonical discriminant analysis (CDA) for each scale. No significant differences were noted in the otolith weight between the two populations (ANCOVA, P>. 0.05). The variability of the finest scales (WLT 1-3) was very high and showed a low percentage of classification (61%). The intermediate scales (WLT 4-6), and WLT 8 provided the best results; whilst the highest classification percentage was found in WLT 4 and WLT 8 (76% and 77%, respectively). The results of this study enable us to conclude that both populations should be considered separate stocks. © 2014

Previously unaccounted cryptic speciation requires revaluating species identification, particularly for fisheries assessment purposes. We describe a rapid and reliable method for distinguishing between phenotypically similar species that utilizes simple otolith morphometry (length, width, thickness and weight) with or without fish length, within a traditional canonical discriminant analysis (CDA). Data were subject to CDA in order to differentiate between the cryptic Etelis carbunculus (ruby snapper) and E. marshi (pygmy ruby snapper). A very high allocation success rate was achieved using otolith morphometry and fork length (99.6% for E. carbunculus and 100% for E. marshi) or otolith morphometry only (98.8% for E. carbunculus and 100% for E. marshi), which indicated the high discriminatory power of this method. The CDA successfully grouped samples of the same species collected from different locations in the eastern central Indian and South Pacific Oceans, indicating the robustness of this technique to discriminate between species, irrespective of their geographic range. This technique can be applied to archived otolith collections to confirm teleost species identification, and likely has broader applications for species identification involving extractive, diet or video-based studies.

Methods that we can use to find out impending problems in the company are prediction models, i.e. models that are able to assess the financial health of the company and to warn owners of the company and company’ business partners before the threat of bankruptcy. Financial analysis can be ex-post and ex-ante. In the literature we can find several names used for the ex-ante financial analysis, such as financial health prediction, forecast financial health, early warning systems, etc. In the article is used the term prediction of financial health. There are many methods on which are based the construction of prediction models and in the article authors further specified discriminant analysis.

a b s t r a c t A nondestructive method based on visible and near infrared spectroscopy, was investigated for deter- mining the maturity of green tomatoes at harvest. The interactance spectrum of tomato fruit at the firm green stage were measured in less than 5 s with a handheld spectrometer (400-1000 nm) utilizing an optical design with a 0◦ angle between the incident illumination and the detection view. Results showed that the predominant change in the interactance spectra in green tomatoes useful for predicting chang- ing maturity levels occurred in the 600-750 nm portion of the 400-1000 nm region, typically associated with chlorophyll. Variety-specific Bayesian classification models and a joint variety 'global' classification model were developed to predict tomato maturity after 7 d of storage in a 20 ◦C ripening room using canonical discriminant analysis techniques applied to the interactance spectra from 600 nm to 750 nm. Variety specific models correctly identified 75-85% of immature tomatoes and 82-86% of mature green tomatoes in internal cross-validation, however external validation performance decreased when applied to predict maturities in a cultivar external to the training set. False positive rates of these models in identifying immature and mature green tomatoes varied from 3% to 40% and 0% to 31% respectively. A 'global' model, trained on two cultivars showed more stability and correctly predicted 71% of immature and 85% of mature green tomatoes, with false positive error rates of 13% and 22%, respectively, in internal cross-validation of both varieties. This handheld system showed good potential as a rapid, nondestructive technique to aid tomato production managers in the identification of immature green tomatoes at har- vest and could be a valuable tool in delivering more flavorful fruit to consumers by reducing the amount of immature fruit harvested by workers. © 2013 Published by Elsevier B.V.

'News and views' article discussing the implications of a new silcrete provenancing techique to Middle Stone Age archaeology in South Africa.

In order to verify the authenticity of organic products, multivariate data (δ15N values, key-metabolites and mineral content) were used to classify organic and conventional peppers and lettuce by means of canonical discriminant analysis. Different origins and types of fertilisers were considered. This is the first paper to look into the influence of biosolarisation, a soil disinfection technique widely used in organic cultivation, on the differentiation between organic and conventional crops. The use of pre-harvest parameters (plant and soil δ15N and plant weight) allowed 78.8% and 65.4% of pepper and lettuce samples, respectively, to be correctly classified. In pepper, this percentage was reduced (69.2%) when only post-harvest sampling parameters were used to build the classification model. In lettuce, the use of biomarkers significantly improved the model, allowing 90.4% of cases to be correctly classified. This methodology showed a high potential for use as an authenticity control tool for organic cultivation.

Fast recognition and characterization of preserved licorice apricot were studied by electronic tongue. The E-tongue signals were analyzed by pattern recognition techniques. Five brands of preserved licorice apricot were discriminated with strong convergence by pattern recognition techniques, Principal Component Analysis, Canonical discriminant Analysis and Cluster Analysis. The characterization of the samples obtained by Back-Propagation Neural Network (BPNN) and Partial Least Squares regression (PLSR) were 100% accurate both for training and test set, and the highest correlation between observed and predicted values was obtained for aerobic plate count, (0.9943, 0.9951) followed by total sugar content (0.9941, 0.9853), content of sodium chloride (0.9926, 0.9902), sulfur dioxide residues (0.9894, 0.9928) with BPNN method. All pattern recognition methods performed for the characterization and classification showed the potential of E-tongue as a rapid tool in the analysis and characterization of preserved fruits.

Bitter pit (BP) is a physiological disorder in apple commonly associated with high Mg/Ca ratio in fruit tissue. This work was carried out to identify the best fruit tissue sampling method for Ca and Mg assessment to discriminate ‘Fuji’ apples regarding the occurrence of BP. After six months under controlled atmosphere storage (2.0 kPa O2 + 0.5 kPa CO2, at 0.5 °C/90–95% RH), fruit without or with BP were submitted to Ca and Mg analysis (mg kg−1 of fresh weight) in the total fraction (TF) of peel + flesh, and in the TF and soluble fraction (SF) of flesh or peel tissues. For the peel + flesh, a wedge-shaped segment was cut longitudinally from the fruit (with 1 cm wide at the equatorial region), discarding the core tissue. For individual sampling of the peel (thickness of 0–2 mm) or flesh (thickness of 2–8 mm), the fruit were cut along the equatorial region, so that only the distal end was used. In this portion of the fruit, Ca and Mg contents were higher in the peel than in the flesh in the TF, and lower in the peel than in the flesh in the SF, while the Mg/Ca ratios in TF and SF fractions were higher in the flesh than in the peel, regardless the occurrence of BP. Calcium and Mg contents in the SF relative to the TF were very low in both peel and flesh tissues. Calcium in the SF represented 0.36% and 2.79% of its content in the TF for peel and flesh, respectively. Magnesium content in the SF represented 0.70% and 3.74% of that in the TF for peel and flesh, respectively. Fruit without BP showed higher Ca content and lower Mg/Ca ratio in the TF of peel + flesh, peel or flesh, and in the SF of peel or flesh, compared to fruit with BP. Fruit without BP also showed a higher percentage of Ca in the SF in relation to TF in the peel (0.42%) compared to fruit with BP (0.31%). Fruit without BP also showed lower Mg content in TF of peel + flesh and peel, and in the SF of the flesh. There was no difference between fruit with and without BP only for Mg contents in TF of the flesh and SF of the peel. The canonical discriminant analysis showed that the Mg/Ca ratio in the SF of the peel tissue at the distal end of the fruit provides the best method to discriminate fruit without and with BP, which can be potentially used as a tool to predict BP development in ‘Fuji’ apples.

The taxonomic histories of two genera, Acyrthosiphon and Aulacorthum, have been controversial because of the ambiguous morphology used as criteria to distinguish these genera. In this study, molecular and morphological characters were analyzed to determine whether the current classification of these genera is reasonable. Two phylogenetic trees based on five genes (COI, COII, srRNA, lrRNA, and EF1a) supported the distinctiveness of Acyrthosiphon and Aulacorthum, and a canonical discriminant analysis using 19 morphological characters showed that the two genera were separated by five morphological characters (HTB, C, Ant.III, HFM, and SIPH). Based on these results, we confirm that the current classification of Acyrthosiphon and Aulacorthum is supported by molecular and morphological characters.

International audience; In this paper, we use random subspace method to compare the classification and prediction of both canonical discriminant analysis and logistic regression models with and without misclassification costs. They have been applied to a large panel of US banks over the period 2008–2013. Results show that model’s accuracy have improved in case of more appropriate cut-off value C∗ROC that maximizes the overall correct classification rate under the ROC curve. We also have tested the newly H-measure of classification performance and provided results for different parameters of misclassification costs. Our main conclusions are: (1) The logit model outperforms the CDA one in terms of correct classification rate by using usual cut-off parameters, (2) C∗ROC improves the accuracy of classification in both CDA and logit regression, (3) H-measure and ROC curve validation improve the quality of the model by minimizing the error of misclassification of bankrupt banks. Moreover, it emphasizes better prediction of banks failure because it delivers in average the highest error type II.

Volatile compounds in the peel of calamansi (Citrus microcarpa) from Malaysia, the Philippines and Vietnam were extracted with dichloromethane and hexane, and then analysed by gas chromatography–mass spectroscopy/flame ionisation detector. Seventy-nine compounds representing >98% of the volatiles were identified. Across the three geographical sources, a relatively small proportion of potent oxygenated compounds was significantly different, exemplified by the highest amount of methyl N-methylanthranilate in Malaysian calamansi peel. Principal component analysis and canonical discriminant analysis were applied to interpret the complex volatile compounds in the calamansi peel extracts, and to verify the discrimination among the different origins. In addition, four common hydroxycinnamic acids (caffeic, p-coumaric, ferulic and sinapic acids) were determined in the methanolic extracts of calamansi peel using ultra-fast liquid chromatography coupled to photodiode array detector. The Philippines calamansi peel contained the highest amount of total phenolic acids. In addition, p-Coumaric acid was the dominant free phenolic acids, whereas ferulic acid was the main bound phenolic acid.

Effects of the Korean carcass-grading system on carcass traits and meat quality parameters for the longissimus dorsi (LD) and semimembranosus (SM) muscles were investigated for Hanwoo steer beef. High quality grade beef cuts had significantly higher intramuscular fat content than those of low quality grade beef cuts. To establish a guaranteed system of eating quality for Hanwoo steer beef, a palatability prediction model was developed. The model development approach used canonical discriminant analysis and multivariate regression to assess effects of muscle type, cooking method, and aging treatment on Hanwoo beef quality grade. The palatability prediction model can provide Korean consumers with detailed information about expected eating quality for an individual cut, as well as provide critical information to the industry for maintaining high-quality beef production. The model is a significant advance in grading compared with the traditional carcass grading system, which applies a single quality grade to an entire carcass.

The potential of using multi-spectral vision technology for quality control in a continuous frying process was investigated. Canonical discriminant analysis of the multi-spectral images of samples of fried minced meat and diced turkey could clearly visualise the effect of different heat treatments. The vision technology can also detect even slight increases in the agglutination of the fried minced meat during the process. This agglutination is undesirable, but very difficult to measure on-line. The results indicate that multi-spectral vision technology may partially or totally substitute visual inspection by an operator as a means of assessing product quality during processing.

0003-3472/$38.00 The Association for the Study of A doi:10.1016/j.anbehav.2008.12.011 An animal’s response to a given stimulus may be assessed by measuring more than one type of behaviour. For example, in studies of the chemosensory-based preferences of squamate reptiles for prey organisms, both the frequency of tongue flicking, a behaviour linked to vomerolfaction, and the attempted ingestion of prey-scented objects have been measured. Burghardt (1969; cf. Cooper & Burghardt 1990) proposed combining both tongue-flick counts and biting attacks on scent-laden swabs into a composite index, called the tongue flick–attack score, by which overall preferences for prey-derived chemicals could be compared. In Burghardt’s scheme, an attack, which presumably reflects greater interest in prey-derived cues, was arbitrarily accorded a value equal in weight to the highest number of tongue-flicks displayed by any nonattacking subject to any condition, plus the number of seconds in a trial minus the attack latency. If scores were log-transformed, a value of one was added prior to transformation.

Sensory characteristics of longissimus thoracis muscle from three local Spanish beef breed-production systems and their relationships with chemical and instrumental meat quality traits were studied. Young bulls of Bruna dels Pirineus (BP; n = 69), Avilena-Negra Iberica (A-NI; n = 70) and Morucha (MO; n = 70) breeds were reared in their own production systems. MO breed showed the highest water holding capacity and also the highest thawing loss and haem pigment content (P < 0.001). No differences in moisture and protein contents were found among breeds. A-NI showed the highest intramuscular fat (IMF, P < 0.05) and total collagen (P < 0.001) contents, whereas BP showed the lowest IMF content (P < 0.05) and the highest collagen solubility (P < 0.001). Beef flavour, tenderness and juiciness accounted for the eating quality differences among the three breed-production systems. Meat from A-NI was rated significantly higher (P < 0.01) for beef flavour and tenderness than that from BP and MO animals. Furthermore, MO showed the lowest juiciness (P < 0.001) which could be due to its higher thawing loss. Within the three breeds, thawing loss was negatively correlated with juiciness and, likewise cooking loss with juiciness and tenderness (P < 0.05). The canonical discriminant analysis showed that the three breeds were significantly different (P < 0.05) from each other according to sensory attributes, which justifies their involvement in different protected geographical indications (PGI).

The present paper is aimed at application of electronic tongue (ET) to the recognition of different apricot varieties and detecting taste changes during storage. Effect of 1-methylcyclopropene (1-MCP) treatment and controlled atmosphere (CA) storage on ripeness and taste of fruits was also investigated. Three apricot varieties and four different CA conditions were studied. The pH and Brix measurement were used as reference methods and sensory analysis was performed with three parameters. Classification of apricot samples was done by canonical discriminant analysis (CDA). Calibration models for determination of correlation between ET data and reference methods were made by partial least squares (PLS) regression. Results of sensory analysis were carried out by variance analysis (ANOVA). The electronic tongue system proved to be suitable for apricot juice measurements. Classification of apricot varieties and determination of correlations between ET, chemical properties and sensory analysis were performed.

The successful classification of Bryndza, a typical Slovak national sheep cheese, from nine different Slovak producing regions, was based on canonical discriminant analysis. Elemental markers of origin (Ba, Cr, Cu, Hg, Mg, Mn, Ni and V) were determined by graphite furnace (GF) and flame atomic absorption spectrometry (AAS). High correlations of elemental markers were found between pasture soil, grass, and Bryndza cheese originated from different regions. The concentration of these markers in pasture soils, grasses, as well as in all the milk and Bryndza cheese-making process was monitored. Their content in sheep milk, lumpy cheese, whey, boiled sheep whey and final Bryndza cheese was significantly correlated with the soil elemental markers. The final product was only slightly contaminated by the individual elements during the Bryndza production, without any significant influence on the Bryndza origin classification and/or traceability.

This project presents a material-centered instrumental neutron activation analysis (INAA) characterization of 120 geologic samples selected from four fine-grained basalt quarries on the Samoan Island of Tutuila. Previous attempts at definitive differentiation of these Tutuilan quarries have utilized x-ray fluorescence (XRF). In this study, clear differentiation of each analyzed quarry was achieved using INAA. Biplots of canonical discriminant analysis (CDA) scores for the INAA data illustrate clear separation based on the variation in chemical composition between each quarry. The samples analyzed not only define quarry separation, but also provide the “core group” for a preliminary baseline necessary for future artifact-centered provenance studies. Inclusion of these “core group” samples in the baseline was confirmed by stepwise discriminant analysis. These findings suggest the ability to determine artifact quarry of origin on the island of Tutuila, which can elucidate the importance of individual Tutuilan quarries in the production, distribution and consumption of fine-grained basalt artifacts in Polynesia.

Three numerical indexes, based on soil enzyme activities, which can discriminate between altered and unaltered soils, are presented and validated. Seven enzymes were measured at three different agricultural sites subjected to contamination by municipal and industrial wastes (site 1), intensive cultivation without either crop rotation or organic fertilization (site 2), and irrigation with brackish water (site 3). At each site neighbouring, unaltered soils were sampled and analysed as control soils. The three indexes were developed by means of canonical discriminant analysis (CDA) using data from two sites, while the third site was kept aside as an independent test. The first index is built up using all of the enzyme activities studied; the second, using the most discriminating enzyme activities only; and the third was developed for testing against data in published papers that deal with enzyme measurements in soils under different management regimes. The three indexes were able to discriminate between altered and control soils when applied to the data set from the third site, i.e., that not used for index development. When tested against published data, the third index was usually able to discriminate altered soils from controls by higher index scores. This index was successful in most cases: it was consistently able to classify soils according to their reported degree of alteration. Our results confirm that enzyme activities are suitable indicators of soil alteration and may be usefully integrated to develop soil alteration indexes suitable for monitoring soil status under different conditions.

This paper relates aroma compounds measured by means of an electronic nose and headspace fingerprint mass spectrometry (HFMS) to sensory analysis for tomato aroma evaluation. Eight tomato cultivars harvested at the red-ripe stage of maturity were selected and assessed on days 4, 7, 10 and 14 after harvest. Descriptive sensory analysis was performed by eight trained panellists. For instrumental analysis a quartz microbalance electronic nose (QMBE-nose), headspace fingerprint mass spectrometry and gas chromatography–mass spectrometry (GC–MS) as reference techniques were employed. Initially, canonical discriminant analysis (CDA) was performed separately on the instrumental and sensory data sets to explore the structure of each data set. The results showed that the sensory data contained information related to the cultivar but not to shelf life as was found with the instruments. Sensors of the QMBE-nose, GC aroma values and signals of the HFMS, were further studied to investigate their relationship with the sensory profile of tomato cultivars using generalized procrustes analysis (GPA). The results demonstrate the potential of the electronic nose and the headspace fingerprint MS to complement routine sensory analysis of tomatoes.

Rapid aroma profiling of food products is a first step towards at-line flavor quality control and off-flavor assessment. In this paper, the potential of the zNose™ was tested for the first time to address this application. Honey was chosen as the food product because of its characteristic aroma. Both a chromatogram and a spectral approach to the interpretation of the zNose™ signal were established. In the chromatogram approach, the signal was treated as a traditional chromatogram and relative peak areas were calculated and compared, while the whole aroma spectrum was considered in the spectral approach. Shifts in GC-column retention times initially led to misinterpretation of the results in the spectral approach. A data processing algorithm was, hence, developed to correct for these shifts. Data were analyzed with principal component analysis (PCA), and canonical discriminant analysis (CDA). With both relative peak areas and corrected spectra, the aroma of six different honey varieties and two types of sugar solutions were successfully discriminated. A classification model was built and validated externally, which resulted in a correct classification of 15 out of 16 honey aroma profiles (94%).

Visual (VIS) and near-infrared (NIR) spectroscopy was applied to discriminate bruises and non-bruised healthy spots on ‘Golden Delicious’ apples. Two types of bruises were examined; those created by controlled impact and those by compression. Reflectance spectra of apples were measured in the range from 400 to 1700 nm. The data were analysed with canonical discriminant analysis (CDA). The squared canonical correlation (CR 2 ) was 0.74 for discriminating impact bruises and non-bruised tissue, and a CR 2 of 0.68 was obtained for distinguishing compression bruises and sound tissue. Based on the linear discriminant functions, built with canonical components, the misclassification errors for non-bruised apples were mainly due to the presence of compression bruises. The classification accuracy was improved by taking the type of bruises into account in the model.

A numerical avalanche prediction scheme offering prediction rates greater than 70% is presented for the Bear Pass highway operation, British Columbia. One-way analysis of variance (ANOVA) and canonical discriminant analysis are used to identify the principal variables that allow discrimination between avalanche and non-avalanche time periods. The optimum variable set is then used in a discriminant analysis to classify each time period into an avalanche or a non-avalanche period. The analysis is performed for all areas in a combined analysis and also for individual sub-areas defined within the Pass. Improvements on classification rates to three out of the four sub-areas are observed compared to the analysis for the whole Pass.

Research on secondary succession in the Amazon basin has attracted great interest in recent years. However, methods used to classify successional stages are limited. This research explores a method that can be used to differentiate regrowth stages. The vegetation inventory data were collected in Altamira, Bragantina, Pedras, and Tome-Acu of the eastern Amazon basin. A nested sampling strategy, organized by region, site, plot, and subplot, was employed for field data collection. Above-ground biomass (AGB), forest stand volume (FSV), basal area, average stand height, average stand diameter (ASD), age, ratio of tree biomass to total biomass (RTB), ratio of tree volume to total volume, and ratio of tree basal area to total basal area were calculated at the site level. Canonical discriminant analysis (CDA) was used to differentiate successional stages and to identify the best forest stand parameters to distinguish these stages. This research indicates that the CDA approach can be used to classify successional forest stages, but using RTB or a combination of two stand parameters such as AGB and ASD are more feasible and recommended in practice. # 2003 Elsevier Science B.V. All rights reserved.

Characterization of 28 varieties of cowpea flour, based on Brabender pasting properties of flour slurry (12% w/w flour: water), was achieved by canonical discriminant analysis. Pasting viscosities at various points on the amyiogram, pasting temperature and paste viscosity ratios were obtained for each variety of flour. Significant varietal influence on pasting properties was indicated by ANOVA ( P

The diterpene alkaloid content was used to assess the chemical taxonomic diversity in three larkspur species. Samples (n=163) were collected from 18 different locations in five western states, extracted and analyzed for diterpene alkaloids using electrospray mass spectrometry. The data were statistically analyzed using canonical discriminant analysis and analysis of variance. Delphinium glaucum samples were easily grouped and were significantly different from all other groups (P

Nucleosides in human urine have been studied frequently as a possible biomedical marker for cancers, acquired immune deficiency syndrome (AIDS) and the whole-body turnover of RNAs. A capillary electrophoretic method that can quantitatively analyze urinary normal and modified nucleosides in less than 40 min with a good resolution and sufficient sensitivity has been developed. Twelve kinds of normal and modified nucleosides were determined in urine samples from 25 healthy persons and 25 cancer patients of 14 kinds of cancers. Artificial neural networks have been used as a powerful pattern recognition tool to distinguish cancer patients from healthy persons. The recognition rate for the training set reached to 100% and above 85% of the members in the predicting set were correctly classified. In addition, the neural network technique was compared with methods of the principal component analysis and the canonical discriminant analysis. The results demonstrate that the predictive ability of the artificial neural network is stronger than the others in this study.

Sinensetin has been quantified in authentic samples of Brazilian orange juice. In addition, six further polymethoxylated flavones (PMFs) have been determined in terms of their relative amounts. The PMFs were extracted into toluene and analysed using reversed phase HPLC with detection at 340 nm. Peak identification was based on the UV-visible spectra and the elution order described in the literature. Hand-squeezed orange juices contained a mean of 0.10 (SD 0.04) mg−1 sinensetin with the highest concentrations found in Pera and Natal varieties. Commercial samples of frozen concentrated orange juice (FCOJ), frozen concentrated pulp-wash (FCOPW), retail FCOJ and retail freshly squeezed orange juice (FSOJ) typically contained at least ten times more sinensetin than those found for samples squeezed by hand. The PMFs peak area ratios for these sample classes were examined further using canonical discriminant analysis. This procedure could distinguish the hand-squeezed juices of Pera and Hamlin varieties from those of Natal and Valencia. Similarly, hand-squeezed juices could be readily distinguished from the commercial samples of FCOJ, FCOPW, retail FCOJ and retail FSOJ.