Journal articles: 'Classiﬁcation and discrimination; cluster analysis'

1

Okuyama, Shuji, and Toshiyuki Mitsui. "Discrimination of Marihuana Using Cluster Analysis." Journal of Chemical Software 2, no. 4 (1995): 220–27. http://dx.doi.org/10.2477/jchemsoft.2.220.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Razak, Abdul, and Nirmala C. R. "A computing model for trend analysis in stock data stream classiﬁcation." Indonesian Journal of Electrical Engineering and Computer Science 19, no. 3 (September 1, 2020): 1602. http://dx.doi.org/10.11591/ijeecs.v19.i3.pp1602-1609.

Full text

Abstract:

For several decades, many statistical and scientiﬁc efforts took place for the better analysis or prediction of stock trading. But still it is open to offer new avenues for the scientists to rethink and discover new inferences by adopting latest technological scenarios. In this regard, this paper is trying to apply classiﬁcation techniques on stock data stream through feature extraction for the trend analysis. The proposed work is involving k-means for clustering samples into two clusters (the stocks in trend as one cluster and another on as stocks not in trend). The trend analysis is done based on density estimation of the stocks with respect to sectors. A well-known data representation method that is histogram is used to represent the sector which is in trend. This work has been implemented and experimented by considering live NSE (india) data using python and its related tools.

APA, Harvard, Vancouver, ISO, and other styles

3

Goncharenko, I. V. "DRSA: a non-hierarchical clustering algorithm using k-NN graph and its application in vegetation classification." Vegetation of Russia, no. 27 (2015): 125–38. http://dx.doi.org/10.31111/vegrus/2015.27.125.

Full text

Abstract:

In this article we proposed a new method of non-hierarchical cluster analysis using k-nearest-neighbor graph and discussed it with respect to vegetation classification. The method of k-nearest neighbor (k-NN) classiﬁcation was originally developed in 1951 (Fix, Hodges, 1951). Later a term “k-NN graph” and a few algorithms of k-NN clustering appeared (Cover, Hart, 1967; Brito et al., 1997). In biology k-NN is used in analysis of protein structures and genome sequences. Most of k-NN clustering algorithms build «excessive» graph firstly, so called hypergraph, and then truncate it to subgraphs, just partitioning and coarsening hypergraph. We developed other strategy, the “upward” clustering in forming (assembling consequentially) one cluster after the other. Until today graph-based cluster analysis has not been considered concerning classification of vegetation datasets.

APA, Harvard, Vancouver, ISO, and other styles

4

Yamamuro, Tadashi, Kenji Kuwayama, Kenji Tsujikawa, Tatsuyuki Kanamori, Yuko T. Iwata, and Hiroyuki Inoue. "Study of cannabis discrimination by hierarchical cluster analysis." Japanese Journal of Forensic Science and Technology 21, no. 2 (2016): 109–24. http://dx.doi.org/10.3408/jafst.709.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

ZHANG, JieJin, Hao WU, Liang ZHAO, YueYue LI, GuiChen ZHOU, ZhenYu ZHU, and GuoQing ZHANG. "Discrimination of Moutan Cortex by principal component analysis and cluster analysis." Pharmaceutical Care and Research 13, no. 6 (December 30, 2013): 449–51. http://dx.doi.org/10.5428/pcar20130617.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Steinhorst, R. Kirk, and Roy E. Williams. "Discrimination of Groundwater Sources Using Cluster Analysis, MANOVA, Canonical Analysis and Discriminant Analysis." Water Resources Research 21, no. 8 (August 1985): 1149–56. http://dx.doi.org/10.1029/wr021i008p01149.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Plichta, Anna. "Methods of Classiﬁcation of the Genera and Species of Bacteria Using Decision Tree." Journal of Telecommunications and Information Technology 4, no. 2019 (December 30, 2019): 74–82. http://dx.doi.org/10.26636/jtit.2019.137419.

Full text

Abstract:

This paper presents a computer-based method for recognizing digital images of bacterial cells. It covers automatic recognition of twenty genera and species of bacteria chosen by the author whose original contribution to the work consisted in the decision to conduct the process of recognizing bacteria using the simultaneous analysis of the following physical features of bacterial cells: color, size, shape, number of clusters, cluster shape, as well as density and distribution of the cells. The proposed method may be also used to recognize the microorganisms other than bacteria. In addition, it does not require the use of any specialized equipment. The lack of demand for high infrastructural standards and complementarity with the hardware and software widens the scope of the method’s application in diagnostics, including microbiological diagnostics. The proposed method may be used to identify new genera and species of bacteria, but also other microorganisms that exhibit similar morphological characteristics.

APA, Harvard, Vancouver, ISO, and other styles

8

Lin, Gwo-Fong, and Chun-Ming Wang. "Performing cluster analysis and discrimination analysis of hydrological factors in one step." Advances in Water Resources 29, no. 11 (November 2006): 1573–85. http://dx.doi.org/10.1016/j.advwatres.2005.11.008.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Gonzalez-Escalona, Narjol, Ruth Timme, Brian H. Raphael, Donald Zink, and Shashi K. Sharma. "Whole-Genome Single-Nucleotide-Polymorphism Analysis for Discrimination of Clostridium botulinum Group I Strains." Applied and Environmental Microbiology 80, no. 7 (January 24, 2014): 2125–32. http://dx.doi.org/10.1128/aem.03934-13.

Full text

Abstract:

ABSTRACTClostridium botulinumis a genetically diverse Gram-positive bacterium producing extremely potent neurotoxins (botulinum neurotoxins A through G [BoNT/A-G]). The complete genome sequences of three strains harboring only the BoNT/A1 nucleotide sequence are publicly available. Although these strains contain a toxin cluster (HA+OrfX−) associated with hemagglutinin genes, little is known about the genomes of subtype A1 strains (termed HA−OrfX+) that lack hemagglutinin genes in the toxin gene cluster. We sequenced the genomes of three BoNT/A1-producingC. botulinumstrains: two strains with the HA+OrfX−cluster (69A and 32A) and one strain with the HA−OrfX+cluster (CDC297). Whole-genome phylogenic single-nucleotide-polymorphism (SNP) analysis of these strains along with other publicly availableC. botulinumgroup I strains revealed five distinct lineages. Strains 69A and 32A clustered with theC. botulinumtype A1 Hall group, and strain CDC297 clustered with theC. botulinumtype Ba4 strain 657. This study reports the use of whole-genome SNP sequence analysis for discrimination ofC. botulinumgroup I strains and demonstrates the utility of this analysis in quickly differentiatingC. botulinumstrains harboring identical toxin gene subtypes. This analysis further supports previous work showing that strains CDC297 and 657 likely evolved from a common ancestor and independently acquired separate BoNT/A1 toxin gene clusters at distinct genomic locations.

APA, Harvard, Vancouver, ISO, and other styles

10

Crawford, I., S. Ruske, D. O. Topping, and M. W. Gallagher. "Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol." Atmospheric Measurement Techniques Discussions 8, no. 7 (July 16, 2015): 7303–33. http://dx.doi.org/10.5194/amtd-8-7303-2015.

Full text

Abstract:

Abstract. In this paper we present improved methods for discriminating and quantifying Primary Biological Aerosol Particles (PBAP) by applying hierarchical agglomerative cluster analysis to multi-parameter ultra violet-light induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1×106 points on a desktop computer, allowing for each fluorescent particle in a dataset to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient dataset. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best performing methods were applied to the BEACHON-RoMBAS ambient dataset where it was found that the z-score and range normalisation methods yield similar results with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misatrribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed yielding an explict cluster attribution for each particle, improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

APA, Harvard, Vancouver, ISO, and other styles

11

Crawford, I., S. Ruske, D. O. Topping, and M. W. Gallagher. "Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol." Atmospheric Measurement Techniques 8, no. 11 (November 27, 2015): 4979–91. http://dx.doi.org/10.5194/amt-8-4979-2015.

Full text

Abstract:

Abstract. In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs) by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio–hydro–atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen–Rocky Mountain Biogenic Aerosol Study) ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misattribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed, yielding an explicit cluster attribution for each particle and improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

APA, Harvard, Vancouver, ISO, and other styles

12

CHU, MEI-TAI, RAJIV KHOSLA, and KAH-HIN CHAI. "A CLUSTER ANALYSIS OF IC DESIGN INDUSTRY." International Journal of Innovation and Technology Management 11, no. 02 (March 25, 2014): 1450003. http://dx.doi.org/10.1142/s0219877014500035.

Full text

Abstract:

IC design is upstream and innovation-oriented in semiconductor industry. This industry is emerging rapidly due to severe competition and shorter product life cycle. In this context, maintaining the leading edge among global competitors as well as overcoming operational challenges is critical to pursue sustainability. In order to enhance the achievements and improve service quality, IC design firms often endeavor to comprehend, if the inputs/investments have led to effective outputs/achievements. A holistic discussion on how successful IC design companies prevail can facilitate how different IC design firms utilize their particular attributes associated with organizational goals. The purpose of this research is to conduct a cluster analysis for global top 30 IC design firms through 15 selected variables to understand their characteristics. These 15 variables include inputs/investments and outputs/achievements collected from financial indicators primarily to examine their characteristics in each cluster. The factor analysis, cluster analysis, and discriminant analysis are adopted to identify the attributes of these companies. The findings first show that the preliminary 15 variables can be refined into four significant factors by their factor loadings using factor analysis. Second, five groups among 30 companies have been categorized in terms of cluster analysis. Third, the accuracy is 94.7% by the validation of discrimination analysis. The strengths and weaknesses of each single cluster are also discussed. The results can help IC design companies to pursue a more suitable business model and tackle unique improvements, respectively.

APA, Harvard, Vancouver, ISO, and other styles

13

Kim, Hyung-Rae, Hyo-Jin Go, and Soo-Yong Kim. "Discrimination of Mild Alzheimer’s Disease Patients using Cluster Analysis of Information Transmission in EEG." Journal of the Korean Physical Society 73, no. 3 (August 2018): 377–87. http://dx.doi.org/10.3938/jkps.73.377.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Guzman, Nelson Gutierrez, Andres Felipe Bahamón Monje, and Lina Ximena Parrado Muñoz. "ATR-FTIR FOR DISCRIMINATION OF ESPRESSO AND AMERICANO COFFEE PODS." Coffee Science 13, no. 4 (December 19, 2018): 550. http://dx.doi.org/10.25186/cs.v13i4.1499.

Full text

Abstract:

Roasted and ground coffee for encapsulation in single-serve capsules compatible with keurig® and coffee powder obtained from Nespresso® commercial capsules were analyzed for pH value, titratable acidity, moisture content, water activity and color (lightness); a data matrix that contains the physicochemical properties and the absorbance measurements using a baseline of 1600 to 1800 cm–1 by FTIR-ATR technique, was evaluated through the combined methods of principal component analysis (PCA) and cluster analysis in order to discriminate between the types of capsules. In the PCA biplot two distinct groups can be identified and in the cluster analysis two groups are that correspond to the two types of capsules. The results showed that FTIR-ATR based methods seem to be a promising alternative for the discrimination of coffee samples for the pods industry or for the type of consumption.

APA, Harvard, Vancouver, ISO, and other styles

15

Ajayi, Alex A., and Moin Syed. "Links between patterns of racial socialization and discrimination experiences and psychological adjustment: A cluster analysis." Journal of Adolescence 37, no. 7 (October 2014): 1011–20. http://dx.doi.org/10.1016/j.adolescence.2014.07.006.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Ronchi, Andrea, Andrea Sterzi, Marco Gandolfi, Ali Belarouci, Claudio Giannetti, Natalia Del Fatti, Francesco Banfi, and Gabriele Ferrini. "Discrimination of nano-objects via cluster analysis techniques applied to time-resolved thermo-acoustic microscopy." Ultrasonics 114 (July 2021): 106403. http://dx.doi.org/10.1016/j.ultras.2021.106403.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

He, Hua-Feng, and Yang Ye. "Discrimination Based on Volatile Compounds and Differential Analysis of Chinese Dark Tea." Journal of Agricultural Science 8, no. 9 (August 5, 2016): 115. http://dx.doi.org/10.5539/jas.v8n9p115.

Full text

Abstract:

Simultaneous distillion and extraction (SDE)/gas chromatographymass spectrometry (Gc-Ms) detection coupled with partial least squares-discriminate analysis (PLS-DA) were used to discriminate Chinese dark teas (CDTs). A total of 84 volatile compounds were taken to conduct the cluster analysis. 9 kinds of CDTs could be divided into 3 groups in consistent with the manufacturing processes. Besides, ingredients that were related with the quality of CDT, such as free amino acid, soluble sugar and catechines were analyzed. Differential trends were disclosed between Pu-Er raw tea and Pu-Er ripe tea as well as raw dark green tea (RDGT).

APA, Harvard, Vancouver, ISO, and other styles

18

Holden, H., and E. LeDrew. "Spectral Discrimination of Healthy and Non-Healthy Corals Based on Cluster Analysis, Principal Components Analysis, and Derivative Spectroscopy." Remote Sensing of Environment 65, no. 2 (August 1998): 217–24. http://dx.doi.org/10.1016/s0034-4257(98)00029-7.

Full text

APA, Harvard, Vancouver, ISO, and other styles

19

Zhao, Qing Jiang, Qi Sun, and Wen Gang Che. "The Application of Bayesian Discrimination in the Analysis on Media Sector Stock." Applied Mechanics and Materials 488-489 (January 2014): 1310–13. http://dx.doi.org/10.4028/www.scientific.net/amm.488-489.1310.

Full text

Abstract:

With the rapid development of China's stock market, investment on the stock has become more rational and scientific and the analysis of the role of equity investments is also increasingly important. In this paper, we use 20 publishing and media companies' financial data from 2011 to analyze the profitability, solvency, growth and capital expansion capability with cluster analysis, and then use the Bayesian discrimination analysis to quantify the classification to inspect the results. According to the investment analysis of media section of stocks, we sum up the type and characteristics of the media section stock for the market to grasp each participant to provide effective long-term growth trend in the reference area.

APA, Harvard, Vancouver, ISO, and other styles

20

Mohamad Asri, Muhammad Naeim, Wan Nur Syuhaila Mat Desa, and Dzulkiflee Ismail. "Combined Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA): an efficient chemometric approach in aged gel inks discrimination." Australian Journal of Forensic Sciences 52, no. 1 (May 15, 2018): 38–59. http://dx.doi.org/10.1080/00450618.2018.1466913.

Full text

APA, Harvard, Vancouver, ISO, and other styles

21

Delpino-Rius, Antoni, Jordi Eras, Ferran Gatius, Mercè Balcells, and Ramon Canela-Garayoa. "Combined Analysis of Primary Metabolites and Phenolic Compounds to Authenticate Commercial Monovarietal Peach Purees and Pear Juices." Molecules 24, no. 18 (September 10, 2019): 3289. http://dx.doi.org/10.3390/molecules24183289.

Full text

Abstract:

Here we authenticated single-varietal peach purees and pear juices on the basis of primary metabolite and phenolic compound analysis by Proton Nuclear Magnetic Resonance (1H-NMR) and Ultra Performance Liquid Chromatography coupled to Photodiode Array and Tandem Mass Spectrometry (UPLC-PDA-MS/MS), respectively. After suitable preprocessing, the 1H-NMR and chromatographic data were evaluated by principal component analysis (PCA). The PCA combining data from primary metabolites and phenolic compounds allowed the separation of the clusters in all cases, allowing discrimination of processed and unprocessed peach purees, both separately and pooled. The PCA of primary metabolites allowed the cluster separation of purees of distinct peach varieties but not between processed and non-processed purees. The PCA of phenolic compounds allowed better cluster separation than of primary metabolites. For pear juices, both PCA approaches allowed satisfactory discrimination of Alejandrina, Conference, and Blanquilla cultivars. These approaches may help to better control cultivar authenticity in fruit products. It could therefore contribute to the development of a process to achieve products characterized by a quality characteristic of a given cultivar.

APA, Harvard, Vancouver, ISO, and other styles

22

Naumann, Annette, Gregor Heine, and Rolf Rauber. "Efficient discrimination of oat and pea roots by cluster analysis of Fourier transform infrared (FTIR) spectra." Field Crops Research 119, no. 1 (October 2010): 78–84. http://dx.doi.org/10.1016/j.fcr.2010.06.017.

Full text

APA, Harvard, Vancouver, ISO, and other styles

23

Hrušková, M., I. Švec, and H. Sekerová. "Colour analysis and discrimination of laboratory prepared pasta by means of spectroscopic methods." Czech Journal of Food Sciences 29, No. 4 (August 10, 2011): 346–23. http://dx.doi.org/10.17221/25/2011-cjfs.

Full text

Abstract:

For the CIE Lab colour profile determination of laboratory prepared pasta, two sample granulations and two spectral methods were tested. Pasta was manufactured progressively from semolina, common wheat, and corn flour. Sufficient colour spectra ranges were ensured by means of fortification with 9 non-traditional cereals in the first case, 8 natural colorants in the second one, and with 12 gluten-free pasta recipes in the last case. Both factors (i.e. granulation and spectral method) were proved as statistically significant by the cluster, variance and principal component analyses. In the comparison of the effects on the pasta composition and the spectral method, the latter demonstrated a stronger impact on the pasta colour profile measured.

APA, Harvard, Vancouver, ISO, and other styles

24

Liao, Chunxiao, Austin O. Rosner, Jill L. Maron, Dongli Song, and Steven M. Barlow. "Automatic Nonnutritive Suck Waveform Discrimination and Feature Extraction in Preterm Infants." Computational and Mathematical Methods in Medicine 2019 (February 4, 2019): 1–12. http://dx.doi.org/10.1155/2019/7496591.

Full text

Abstract:

Background and Objective: The emergence of the nonnutritive suck (NNS) pattern in preterm infants reflects the integrity of the brain and is used by clinicians in the neonatal intensive care unit (NICU) to assess feeding readiness and oromotor development. A critical need exists for an integrated software platform that provides NNS signal preprocessing, adaptive waveform discrimination, feature detection, and batch processing of big data sets across multiple NICU sites. Thus, the goal was to develop and describe a cross-platform graphical user interface (GUI) and terminal application known as NeoNNS for single and batch file time series and frequency-domain analyses of NNS compression pressure waveforms using analysis parameters derived from previous research on NNS dynamics. Methods. NeoNNS was implemented with Python and the Tkinter GUI package. The NNS signal-processing pipeline included a low-pass filter, asymmetric regression baseline correction, NNS peak detection, and NNS burst classification. Data visualizations and parametric analyses included time- and frequency-domain view, NNS spatiotemporal index view, and feature cluster analysis to model oral feeding readiness. Results. 568 suck assessment files sampled from 30 extremely preterm infants were processed in the batch mode (<50 minutes) to generate time- and frequency-domain analyses of infant NNS pressure waveform data. NNS cycle discrimination and NNS burst classification yield quantification of NNS waveform features as a function of postmenstrual age. Hierarchical cluster analysis (based on the Tsfresh python package and NeoNNS) revealed the capability to label NNS records for feeding readiness. Conclusions. NeoNNS provides a versatile software platform to rapidly quantify the dynamics of NNS development in time and frequency domains at cribside over repeated sessions for an individual baby or among large numbers of preterm infants at multiple hospital sites to support big data analytics. The hierarchical cluster feature analysis facilitates modeling of feeding readiness based on quantitative features of the NNS compression pressure waveform.

APA, Harvard, Vancouver, ISO, and other styles

25

Nomura, Masaki, Yoshio Sakurai, and Toshio Aoyagi. "Analysis of Multineuron Activity Using the Kernel Method." Journal of Robotics and Mechatronics 19, no. 4 (August 20, 2007): 364–68. http://dx.doi.org/10.20965/jrm.2007.p0364.

Full text

Abstract:

We recorded multineuron spike time-series data from rat hippocampus region CA1 during a conditional discrimination task. We separated out individual single-neuron activity from multineuron activity data and prepared spike count data and calculated a kernel matrix using a Spikernel function, then applied k-means clustering and principal component analysis (PCA). Comparing spike count data to an appropriate time, we divided data into clusters and found the correspondence between the obtained cluster and rat activity. We discuss information expression in nervous-system activity expected from the kernel function.

APA, Harvard, Vancouver, ISO, and other styles

26

Redden, R. J., I. H. DeLacy, D. G. Butler, and T. Usher. "Analysis of line x environment interactions for yield in navy beans. 2. Pattern analysis of lines and environment within years." Australian Journal of Agricultural Research 51, no. 5 (2000): 607. http://dx.doi.org/10.1071/ar97136.

Full text

Abstract:

Seven years of multi-environment yield trials of navy bean (Phaseolus vulgaris L.) grown in Queensland were examined. As is common with plant breeding evaluation trials, test entries and locations varied between years. Grain yield data were analysed for each year using cluster and ordination analyses (pattern analyses). These methods facilitate descriptions of genotype performance across environments and the discrimination among genotypes provided by the environments. The observed trends for genotypic yield performance across environments were partly consistent with agronomic and disease reactions at specific environments and also partly explainable by breeding and selection history. In some cases, similarities in discrimination among environments were related to geographic proximity, in others management practices, and in others similarities occurred between geographically widely separated environments which differed in management practices. One location was identified as having atypical line discrimination. The analysis indicated that the number of test locations was below requirements for adequate representation of line × environment interaction. The pattern analyses methods used were an effective aid in describing the patterns in data for each year and illustrated the variations in adaptive patterns from year to year. The study has implications for assessing the number and location of test sites for plant breeding multi-environment trials, and for the understanding of genetic traits contributing to line × environment interactions.

APA, Harvard, Vancouver, ISO, and other styles

27

Barlage, Stefan, Gregor Rothe, Ruth Knuechel, and Gerd Schmitz. "Flow Cytometric Immunophenotyping of Mature Lymphatic Neoplasias Using Knowledge Guided Cluster Analysis." Analytical Cellular Pathology 19, no. 2 (1999): 81–90. http://dx.doi.org/10.1155/1999/289820.

Full text

Abstract:

Flow cytometry is widely used for the immunological characterization of hematopoietic malignancies. Discrimination of normal and malignant cellular immunophenotypes is the most critical step in data analysis, especially if multi‐color analysis is performed on highly heterogenous cell suspensions. We therefore investigated, whether adaptive, simultaneous multiparameter gating allowed automated, operator independent analysis of data obtained from the immunophenotyping of blood or bone marrow samples with regard to the presence of non‐Hodgkin lymphoma cells. The identification of physiological and malignant cells was achieved by predefining population boundaries, based on the expectations of the population’s location in two‐dimensional dot plots. The prospective application of these predefined region boundaries in 52 blood and bone marrow samples enabled identification of lymphoma cells with regard to their presence and immunophenotype, based on the correlation of markers as defined in multiple tubes. Our data confirm that highly standardized data analysis methods can reduce the variability of analysis and support the expert in establishing a rapid classification of the sample.

APA, Harvard, Vancouver, ISO, and other styles

28

Cao, Zhen, Yongying Liu, and Jiancheng Zhao. "Efficient Discrimination of Some Moss Species by Fourier Transform Infrared Spectroscopy and Chemometrics." Journal of Spectroscopy 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/191796.

Full text

Abstract:

Fourier transform infrared spectroscopy (FTIR) technique was used to classify 16 species from three moss families (Mielichhoferiaceae, Bryaceae, and Mniaceae). The FTIR spectra ranging from 4000 cm−1to 400 cm−1of the 16 species were obtained. To group the spectra according to their spectral similarity in a dendrogram, cluster analysis and principal component analysis (PCA) were performed. Cluster analysis combined with PCA was used to give a rough result of classification among the moss samples. However, some species belonging to the same genus exhibited very similar chemical components and similar FTIR spectra. Fourier self-deconvolution (FSD) was used to enhance the differences of the spectra. Discrete wavelet transform (DWT) was used to decompose the FTIR spectra ofMnium laevinerveandM. spinosum. Three scales were selected as the feature extracting space in the DWT domain. Results showed that FTIR spectroscopy combined with DWT was suitable for distinguishing different species of the same genus.

APA, Harvard, Vancouver, ISO, and other styles

29

Kaliszewski, Miron, Elżbieta Anna Trafny, Maksymilian Włodarski, Rafał Lewandowski, Małgorzata Stępińska, Mirosław Kwaśny, Jerzy Kostecki, and Krzysztof Kopczyński. "Real-time analysis and classification of bioaerosols based on optical scattering properties." Bulletin of the Military University of Technology 66, no. 1 (March 31, 2017): 27–40. http://dx.doi.org/10.5604/01.3001.0009.9475.

Full text

Abstract:

The size and shape of biological particles are important parameters allowing discrimination between various species. We have studied several aerosols of biological origin such as pollens, bacterial spores and vegetative bacteria. All of them presented different morphology. Using optical size and shape analyser we found good correlation between light scattering properties and actual particle features determined by scanning electron and fluorescence microscopy. In this study, we demonstrated that HCA (Hierarchical Cluster Analysis) offers fast and continuous bioaerosol classification based on shape and size data matrices of aerosols. The HCA gives an unequivocal interpretation of particle size vs. asymmetry data. Therefore, it may provide high throughput and reliable screening and classification of bioaerosols using scattering characteristics. Keywords: bioaerosol classification, scattering, particle size and shape analysis, biological warfare agents’ detection, hierarchical cluster analysis (HCA)

APA, Harvard, Vancouver, ISO, and other styles

30

Troshchynska, Yana, Roman Bleha, Lenka Kumbarová, Marcela Sluková, Andrej Sinica, and Jiří Štětina. "Characterisation of flaxseed cultivars based on NIR diffusion reflectance spectra of whole seeds and derived samples." Czech Journal of Food Sciences 37, No. 5 (October 31, 2019): 374–82. http://dx.doi.org/10.17221/270/2018-cjfs.

Full text

Abstract:

Discrimination of yellow and brown flaxseed cultivars was made based on diffusion reflectance FT-NIR spectra of whole seeds. The spectra of flaxseed kernels, hulls, defatted flours, and oils were also measured for comparison. Hierarchy cluster analysis (HCA) and principal component analysis (PCA) were used for the discrimination. Multivariate analyses of FT-NIR spectra led to satisfactory discrimination of all flaxseed cultivars of this study mainly according to the nutritionally important fatty acid composition that was confirmed by comparison with the corresponding spectra of flaxseed kernel and oil. By contrast, spectral features of proteins, polysaccharides, and tannins predominated in the FT-NIR spectra of flaxseed hulls and defatted flours.

APA, Harvard, Vancouver, ISO, and other styles

31

Aran, Mehdi, Reza Fatahi, and Zabihollah Zamani. "Molecular and morphological discrimination of selected plum seedlings for rootstock breeding." Journal of Fruit and Ornamental Plant Research 20, no. 1 (October 1, 2012): 5–19. http://dx.doi.org/10.2478/v10290-012-0001-0.

Full text

Abstract:

ABSTRACT Plum seedlings are extensively used as rootstocks for stone fruits except P. cerasus. Genetic diversity in seedlings used for rootstocks might result in variation of scion performance and subsequently non-uniform orchards. This study aimed on investigating variation among several Iranian plum genotypes sampled from seedlings grown for grafting. Thirty-five 3- to 4-year-old seedlings were characterized using 28 quantitative and qualitative traits, as well as 22 RAPD markers. Results of the morphological study revealed remarkable variability in studied traits. Genotypes were separated into three different groups according to their height using cluster analysis performed by Ward’s clustering method based on morphological data. Twenty two RAPD primers from 120 screened produced 195 polymorphic reproducible bands (86.75% polymorphism). According to the similarity matrix, the lowest similarity was obtained between the genotype Tansgol (control) and S4-13 and the highest similarity between S11-25 and S11-26. According to the cluster analysis based on Jaccard's similarity coefficients and the UPGMA method at a similarity level of 0.56, the genotypes were divided into six sub-clusters. Significant association between eight morphological traits with RAPD markers was found by marker association analysis done using multiple linear regressions. The application of the methodology in screening elite genotypes is discussed.

APA, Harvard, Vancouver, ISO, and other styles

32

Ibáñez, A. L., and L. A. Jawad. "Morphometric variation of fish scales among some species of rattail fish from New Zealand waters." Journal of the Marine Biological Association of the United Kingdom 98, no. 8 (February 1, 2018): 1991–98. http://dx.doi.org/10.1017/s0025315418000024.

Full text

Abstract:

New Zealand rattail fish are of great interest both to biologists who study their phylogenetics and in fisheries. In contrast, their morphological evolution is little studied and poorly understood. Geometric morphometric methods based on scale shape were applied in this study to determine differences among species and genera. Scale shapes were described using seven landmarks, the coordinates of which were subjected to a generalized Procrustes analysis, followed by a principal components analysis. A cross-validated discriminant analysis was applied to assess and compare the size-shape (centroid size plus shape variables) efficacy in the species and the discrimination of the genera. Two main phenetic groups were identified: cluster no. 1 with eight species and cluster no. 2 with six species. Coelorhinchus aspercephalus and Mesovagus antipodum were more separated from the other species in the first cluster. The cross-validated canonical discriminant analysis correctly classified 74% at the genus level, with most misclassifications occurring between Coelorhinchus and Coryphaenoides, whereas the best classified genera were Mesovagus and Trachyrincus. The discrimination of correctly classified species ranged from 41.2 to 100%. The highest correct classification rates were recorded for Coryphaenoides armatus, Coelorhinchus innotabilis, Trachyrincus longirostris and Mesovagus antipodum.

APA, Harvard, Vancouver, ISO, and other styles

33

BUZZOLA, F. R., L. QUELLE, M. I. GOMEZ, M. CATALANO, L. STEELE-MOORE, D. BERG, E. GENTILINI, G. DENAMIEL, and D. O. SORDELLI. "Genotypic analysis of Staphylococcus aureus from milk of dairy cows with mastitis in Argentina." Epidemiology and Infection 126, no. 3 (June 2001): 445–52. http://dx.doi.org/10.1017/s0950268801005519.

Full text

Abstract:

Staphylococcus aureus is the most prevalent pathogen causing mastitis of dairy ruminants. This study was developed to ascertain the genotypes and genealogical relationship among strains isolated from milk of bovines with mastitis in Argentina. Molecular epidemiological analysis of S. aureus was performed on 112 isolates from 21 districts. Clonality was assessed by SmaI pulsed-field gel electrophoresis (PFGE) typing, automated EcoRI ribotyping and restriction enzyme analysis of plasmid (REAP) DNA profiles. A total of 22 band patterns distributed in four clusters were found by SmaI PFGE analysis. The similarity of clusters 2, 3 and 4 with cluster 1 was 0·73, 0·69 and 0·33, respectively, and 101 of 112 isolates belonged in cluster 1. PFGE band patterns from 42 isolates within cluster 1 were indistinguishable from each other (type A). The second largest group of isolates with indistinguishable PFGE band patterns was subtype A11, which was composed of 19 isolates. Automated ribotyping assigned the 112 isolates into 13 ribotypes. Among these, the most prevalent ribotypes I and VI were composed of 49 and 35 isolates respectively. Although there was certain correspondence between PFGE genotypes and ribotypes, further discrimination was achieved by combining both methods. REAP DNA profile analysis was useful to provide even further discrimination between isolates with identical PFGE genotype and ribotype. The most prevalent S. aureus strains A/I and A11/VI were widely distributed in the country and were not restricted to individual nearby locations. Prevalence of these two strains varied consecutively within a period of 8 years. Whether the shift in type prevalence was due to selection of a phenotypic trait remains undisclosed.

APA, Harvard, Vancouver, ISO, and other styles

34

Luo, Congpei, Tao He, and Ze Chun. "Discrimination and chemical phylogenetic study of seven species of Dendrobium using infrared spectroscopy combined with cluster analysis." Journal of Molecular Structure 1037 (April 2013): 40–48. http://dx.doi.org/10.1016/j.molstruc.2012.10.048.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Fletcher, John S., Alexander Henderson, Roger M. Jarvis, Nicholas P. Lockyer, John C. Vickerman, and Royston Goodacre. "Rapid discrimination of the causal agents of urinary tract infection using ToF-SIMS with chemometric cluster analysis." Applied Surface Science 252, no. 19 (July 2006): 6869–74. http://dx.doi.org/10.1016/j.apsusc.2006.02.153.

Full text

APA, Harvard, Vancouver, ISO, and other styles

36

Saeed, S., M. G. Fakih, K. Riederer, A. R. Shah, and R. Khatib. "Interinstitutional and Intrainstitutional Transmission of a Strain ofAcinetobacter baumanniiDetected by Molecular Analysis Comparison of Pulsed-Field Gel Electrophoresis and Repetitive Sequence–Based Polymerase Chain Reaction." Infection Control & Hospital Epidemiology 27, no. 9 (September 2006): 981–83. http://dx.doi.org/10.1086/507286.

Full text

Abstract:

Pulsed-field gel electrophoresis and repetitive sequence-based polymerase chain reaction provided comparable strain discrimination with minor discordance in typingAcinetobacter baumanniiclinical isolates from patients at our hospital and affiliated institutions. Typing revealed a cluster strain with intrainstitutional and interinstitutional spread during the study period. A long-term acute care facility may have been the reservoir.

APA, Harvard, Vancouver, ISO, and other styles

37

Voltas, J., I. Romagosa, A. Lafarga, A. P. Armesto, A. Sombrero, and J. L. Araus. "Genotype by environment interaction for grain yield and carbon isotope discrimination of barley in Mediterranean Spain." Australian Journal of Agricultural Research 50, no. 7 (1999): 1263. http://dx.doi.org/10.1071/ar98137.

Full text

Abstract:

Carbon isotope discrimination (Δ) has been found to be either positively or negatively related to grain yield of small grain cereals when grown in contrasting environments. In order to clarify a possible association between grain yield of barley (Hordeum vulgare L.) and Δ of mature kernels, five 6-rowed and five 2-rowed barley cultivars were evaluated in 22 rainfed environments of northern Mediterranean Spain. Analyses of variance suggested that the genotypic Δ values were more consistent across environments than the genotypic yields. Genotype×environment (G×E) interaction for grain yield was further explored by fitting an AMMI (additive main effects and multiplicative interaction) model. The first 2 multiplicative axes were found significant. The AMMI2 model provided more accurate estimates of genotypic yields within environments than the conventional unadjusted means across replicates. AMMI2 estimates were used for input into cluster analysis, grouping environments that ranked genotypic yields similarly. Three major groups were obtained, with average yields of 2.42 t/ha (cluster I), 3.06 t/ha (cluster II), and 5.16 t/ha (cluster III). The genotypic ranking for Δ did not vary substantially across clusters, but it changed for grain yield. The average genotypic yields in the low-yielding cluster I ranked opposite to those in the high-yielding cluster III, suggesting the existence of a crossover point at an intermediate yield level. The association between grain yield and Δ for genotypic means within clusters was variable. In cluster I, yield and Δ tended to be negatively related, whereas they were positively related in clusters II and III. Genotypes with lower Δ, i.e. with higher transpiration efficiency, performed better in low-yielding environments (mostly those grouped in cluster I). On the contrary, a high genotypic Δ was of advantage in medium (cluster II) and high-yielding environments (cluster III). This observation supports the assumption that drought tolerance and high yield potential under non-limiting growing conditions may be antagonistic concepts in barley. Genotypic means for kernel number per m 2 and Δ were consistently and positively related within clusters, suggesting that a constitutively high Δ may have been driven by a large genotypic reproductive sink. The convenience of using Δ as a selection criterion in areas exhibiting a considerable G×E interaction for grain yield is discussed.

APA, Harvard, Vancouver, ISO, and other styles

38

Shi, Shuang, Ying Guo, and Yu Ling Yang. "Simulating Discrimination for Quality Evaluation of Rubelite Red." Key Engineering Materials 680 (February 2016): 567–73. http://dx.doi.org/10.4028/www.scientific.net/kem.680.567.

Full text

Abstract:

To evaluate the quality and simulate the discrimination of rubelite red, 310 rubelite red samples are measured by color i5 colorimeter, based on CIE 1976 L*a*b* uniform color space. Conclusions show that the hue angle of rubelite red can be classified into four series, such as red, pink, purple and violet, and the chroma can be divided into light, medium and intense, vivid with increasing quality, then its lightness can be graded into five levels as dark, slightly dark, medium, slightly bright and bright under standard light source D65. Take the three parameters and the cluster analysis of color coordinates, the rubelite red can be grade into five levels, and it is supposed to predict unknown samples furthermore.

APA, Harvard, Vancouver, ISO, and other styles

39

Mehdipanah, Roshanak, Jessica Ramirez, Shanti Abedin, and Sherrill F. Brown. "Housing Discrimination and Health: Understanding Potential Linking Pathways Using a Mixed-Methods Approach." Social Sciences 7, no. 10 (October 12, 2018): 194. http://dx.doi.org/10.3390/socsci7100194.

Full text

Abstract:

Few studies have examined the impact of housing discrimination on health. This study explores potential pathways linking housing discrimination and health using concept mapping, a mixed-method approach. Participants included employees from twenty Fair Housing Organizations nationwide who participated in two online sessions, brainstorming, and structuring. Responses were generated representing biological, social, economic, and physical connections between housing discrimination and health. Using hierarchical cluster analysis, five clusters were identified: (1) Access and barriers; (2) Opportunities for growth; (3) Neighborhood and communities; (4) Physical effects of housing discrimination; and (5) Mental health. Clusters 1 (4.09) and 2 (4.08) were rated as most important for health, while clusters 2 (3.93) and 3 (3.90) were rated as most frequently occurring. These findings add to the limited evidence connecting housing discrimination to health and highlight the need for studies focusing on the long-term health effects of housing discrimination on individuals and neighborhoods.

APA, Harvard, Vancouver, ISO, and other styles

40

Yanguo, Chen, and Cai Shaohua. "APPLICATION OF CLUSTER ANALYSIS IN THE TYPICAL TROPHIC LEVEL CLASSIFICATION OF RESERVIOR AND 0—1 HIGHER INDEX DISCRIMINATION." Journal of Lake Sciences 5, no. 3 (1993): 269–77. http://dx.doi.org/10.18307/1993.0310.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

Fan, Han, Victor Hernandez Bennetts, Erik Schaffernicht, and Achim J. Lilienthal. "A cluster analysis approach based on exploiting density peaks for gas discrimination with electronic noses in open environments." Sensors and Actuators B: Chemical 259 (April 2018): 183–203. http://dx.doi.org/10.1016/j.snb.2017.10.063.

Full text

APA, Harvard, Vancouver, ISO, and other styles

42

Razic, Slavica, Djuro Cokesa, and Snezana Sremac. "Multivariate data visualization methods based on elemental analysis of wines by atomic absorption spectrometry." Journal of the Serbian Chemical Society 72, no. 12 (2007): 1487–92. http://dx.doi.org/10.2298/jsc0712487r.

Full text

Abstract:

The contents of five metals (Cu, Mn, Fe, Cd, and Pb) in several red and white wines originating from different regions of Serbia were determined by flame and graphite furnace atomic absorption spectrometry. The data were processed using chemometric techniques. Principal component and factor analysis were applied in order to highlight the relations between the elements and, after data reduction, three main factors controlling variability were identified. Application of hierarchical cluster analysis to the studied wines indicated differentiation of the samples belonging to different origins. No discrimination between red and white wines was found.

APA, Harvard, Vancouver, ISO, and other styles

43

Caruso, Giulia, and Stefano Antonio Gattone. "Waste Management Analysis in Developing Countries through Unsupervised Classification of Mixed Data." Social Sciences 8, no. 6 (June 13, 2019): 186. http://dx.doi.org/10.3390/socsci8060186.

Full text

Abstract:

The increase in global population and the improvement of living standards in developing countries has resulted in higher solid waste generation. Solid waste management increasingly represents a challenge, but it might also be an opportunity for the municipal authorities of these countries. To this end, the awareness of a variety of factors related to waste management and an efficacious in-depth analysis of them might prove to be particularly significant. For this purpose, and since data are both qualitative and quantitative, a cluster analysis specific for mixed data has been implemented on the dataset. The analysis allows us to distinguish two well-defined groups. The first one is poorer, less developed, and urbanized, with a consequent lower life expectancy of inhabitants. Consequently, it registers lower waste generation and lower C O 2 emissions. Surprisingly, it is more engaged in recycling and in awareness campaigns related to it. Since the cluster discrimination between the two groups is well defined, the second cluster registers the opposite tendency for all the analyzed variables. In conclusion, this kind of analysis offers a potential pathway for academics to work with policy-makers in moving toward the realization of waste management policies tailored to the local context.

APA, Harvard, Vancouver, ISO, and other styles

44

Fuster-Ruiz de Apodaca, Maria Jose, Fernando Molero, Eneko Sansinenea, Francisco-Pablo Holgado, Alejandro Magallares, and Arrate Agirrezabal. "Perceived discrimination, self-exclusion and well-being among people with HIV as a function of lipodystrophy symptoms." Anales de Psicología 34, no. 1 (December 15, 2017): 7. http://dx.doi.org/10.6018/analesps.34.1.278851.

Full text

Abstract:

This study examined the effects of perceived discrimination on the well-being of people with HIV and the mediating role of self-exclusion as a function of the participants' symptoms of lipodystrophy. An ex post facto study with a sample of 706 people with HIV was conducted. Self-perception of lipoatrophy and lipohypertrophy, perceived discrimination, self-exclusion and psychological well-being were measured. Results of hierarchical cluster analysis showed participants could be categorized into three groups: no lipodystrophy, mixed syndrome with predominant lipoaccumulation and lipoatrophy. Results of structural equation modeling revealed that the negative effects of perceived discrimination on well-being were mediated to a large extent by self-exclusion. Invariance analysis revealed that the mediating role of self-exclusion was not the same in the three clusters. Complete mediation of self-exclusion in the groups without lipodystrophy and with predominant lipoaccumulation was confirmed. Regarding lipoatrophy, the negative effects of perceived discrimination were greater and only partly mediated by self-exclusion. In conclusion, having lipodystrophy exposed people to more discrimination; lipoatrophy was the most stigmatizing condition.

APA, Harvard, Vancouver, ISO, and other styles

45

Lim, Dong Kyu, Nguyen Phuoc Long, Changyeun Mo, Ziyuan Dong, Jongguk Lim, and Sung Won Kwon. "Optimized Mass Spectrometry-Based Metabolite Extraction and Analysis for the Geographical Discrimination of White Rice (Oryza sativa L.): A Method Comparison Study." Journal of AOAC INTERNATIONAL 101, no. 2 (March 1, 2018): 498–506. http://dx.doi.org/10.5740/jaoacint.17-0158.

Full text

Abstract:

Abstract In this study, we examined the effects of different extraction methods for the GC-MS- and LC-MS-based metabolite profiling of white rice (Oryza sativa L.). In addition, the metabolite divergence of white rice cultivated in either Korea or China was also evaluated. The discrimination analysis of each extraction method for white rice from Korea and China and the corresponding discriminatory markers were estimated by unpaired t-test, principal component analysis, k-means cluster analysis, partial least-squares discriminant analysis (PLS-DA), and random forest (RF). According to the prediction parameters obtained from PLS-DA and RF classifiers as well as features that could be identified, the extraction method using 75% isopropanol heated at 100°C coupled with LC-MS analysis was confirmed to be superior to the other extraction methods. Noticeably, lysophospholipid concentrations were significantly different in white rice between Korea and China, and they are novel markers for geographical discrimination. In conclusion, our study suggests an optimized extraction and analysis method as well as novel markers for the geographical discrimination of white rice.

APA, Harvard, Vancouver, ISO, and other styles

46

Ma, Tianchen, Haoan Zhao, Caiyun Liu, Min Zhu, Hui Gao, Ni Cheng, and Wei Cao. "Discrimination of Natural Mature Acacia Honey Based on Multi-Physicochemical Parameters Combined with Chemometric Analysis." Molecules 24, no. 14 (July 23, 2019): 2674. http://dx.doi.org/10.3390/molecules24142674.

Full text

Abstract:

Honey maturity is an important factor in evaluating the quality of honey. We established a method for the identification of natural mature acacia honey with eighteen physicochemical parameters combined with chemometric analysis. The analysis of variance showed significant differences between mature and immature acacia honey in physicochemical parameters. The principal component analysis explained 82.64% of the variance among samples, and indicated that total phenolic content, total protein content, and total sugar (glucose, fructose, sucrose) were the major variables. The cluster analysis and orthogonal partial least squares-discriminant analysis demonstrated that samples were grouped in relation to the maturity coinciding with the results of the principal component analysis. Meanwhile, the 35 test samples were classified with 100% accuracy with the method of multi-physicochemical parameters combined with chemometric analysis. All the results presented above proved the possibility of identifying mature acacia honey and immature acacia honey according to the chemometric analysis based on the multi-physicochemical parameters.

APA, Harvard, Vancouver, ISO, and other styles

47

Troshchynska, Yana, Roman Bleha, Lenka Kumbarová, Marcela Sluková, Andrej Sinica, and Jiří Štětina. "Discrimination of flax cultivars based on visible diffusion reflectance spectra and colour parameters of whole seeds." Czech Journal of Food Sciences 37, No. 3 (July 3, 2019): 199–204. http://dx.doi.org/10.17221/202/2018-cjfs.

Full text

Abstract:

Discrimination of yellow and brown seeded flax cultivars was made based on visible (Vis) diffusion reflectance spectra of whole seeds. Hierarchy cluster analysis (HCA) and principal component analysis (PCA) were used for the discrimination. Multivariate analyses of Vis spectra led to satisfactory discrimination of all flax cultivars of this study. The CIE L*a*b* colour parameters were calculated from the diffusion reflectance Vis spectra. The values of L* were in the range of 48.8–53.6 and 62.6–66.0% for brown and yellow seeded cultivars, respectively. Chromatic parameters a* and b* were in the range of 2.8–4.9 and 7.9–16.4%, respectively. A strong linear correlation (R2 = 0.9712) was found between a* and b* parameters for all the flaxseed samples. The L* and a* parameters were sufficient for HCA clustering of the individual flax cultivars.

APA, Harvard, Vancouver, ISO, and other styles

48

Barbosa, Rafael Marani, Bruno Guilherme Torres Licursi Vieira, Antônio Sérgio Ferraudo, José Eduardo Corá, and Roberval Daiton Vieira. "Discrimination of soybean seed lots by multivariate exploratory techniques." Journal of Seed Science 35, no. 3 (2013): 302–10. http://dx.doi.org/10.1590/s2317-15372013000300005.

Full text

Abstract:

Physiological potential characterization of seed lots is usually performed by germination and vigor tests; however, the choice of a single test does not reflect such potential, once each test assesses seeds of differentiated mode. Multivariate techniques allow understanding structural dependence contained in each variable, as well as characterize groups of seed lots according to specific standards. The study aimed at evaluating variability among soybean seed lots and discriminate these lots by multivariate exploratory techniques as function of seed vigor. Experiment was performed with 20 soybean seed lots (10 lots cv. BRS Valiosa RR and 10 lots cv. M-SOY 7908 RR). Seed physiological potential was assessed by testing for: germination (standard, and under different water availability); vigor (accelerated aging and electrical conductivity); and field seedling emergence. Cluster analysis of seed lots, as well as Principal Component Analysis was performed using data obtained on all tests. Multivariate techniques allowed stratifying seed lots into two distinct groups. Principal Component Analysis showed that values obtained for variables: field seedling emergence, accelerated aging, and germination under different water availability were linked to BRS Valiosa RR; while to variables germination and electrical conductivity, were linked to M-SOY 7908 RR.

APA, Harvard, Vancouver, ISO, and other styles

49

Kupe, Muhammed, Bahadır Sayinci, Bünyamin Demir, Sezai Ercisli, Kürşat Alp Aslan, Muhammet Ali Gundesli, Mojmir Baron, and Jiri Sochor. "Multivariate Analysis Approaches for Dimension and Shape Discrimination of Vitis vinifera Varieties." Plants 10, no. 8 (July 26, 2021): 1528. http://dx.doi.org/10.3390/plants10081528.

Full text

Abstract:

In this study, berry dimensions and shape traits, which are important for the design of the grape processing system and the classification of 10 different grape varieties grown in same ecological conditions (‘Ata Sarısı’, ‘Barış’, ‘Dımışkı’, ‘Hatun Parmağı’, ‘Helvani’, ‘Horoz Karası’, ‘Hönüsü’, ‘İtalia’, ‘Mevlana Sarısı’, and ‘Red Globe’) were determined; differences between the varieties were identified with the use of discriminant analysis. The largest grape varieties were identified as ‘Ata Sarısı’ and ‘Red Globe’. The ‘Red Globe’ and ‘Helvani’ varieties had geometrically sphere-like shape. The ‘Barış’ variety had the lowest size averages. According to elliptic Fourier analysis, the primary source of shape variation was ellipse and sphere-looking varieties. However, shape variation was seen due to the existence of a small number of drop-like varieties. According to discriminant analysis, shape differences of the varieties were defined by two discriminant functions. Based on these discriminant functions, the greatest classification performance was achieved for ‘Mevlana Sarısı’ and ‘Dımışkı’. In scatter plots, three shape definitions (sphere, ellipse, and drop) were made for grape varieties. Cluster analysis revealed 4 sub-groups. The first sub-group included the ‘Mevlana Sarısı’ variety; the second sub-group included the ‘Hönüsü’, ‘Hatun Parmağı’, ‘Dımışkı’, and ‘Horoz Karası’ varieties; the third sub-group included the ‘Ata Sarısı’ variety; the fourth sub-group included the ‘Barış’, ‘Helvani’, ‘İtalia’, and ‘Red Globe’ varieties. The variety in the first group had a geometrically ellipse-like shape, the largest length, and the smallest width. The size data were the smallest for the second sub-group. The third sub-group, with the ellipse-like shape, had the large size data. The grape varieties the closest to the sphere were classified in the fourth group, and these varieties had the large sizes.

APA, Harvard, Vancouver, ISO, and other styles

50

Jin, Miao-Miao, Wen-Dan Zhang, Geng-Shen Song, Yan-Mei Xu, Ying-Feng Du, Wei Guo, Liang Cao, and Hui-Jun Xu. "Discrimination and Chemical Phylogenetic Study of Four Pulsatilla Herbs Using UPLC–ESI–MS/MS Combined with Hierarchical Cluster Analysis." Journal of Chromatographic Science 56, no. 3 (December 11, 2017): 216–24. http://dx.doi.org/10.1093/chromsci/bmx102.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Journal articles on the topic 'Classiﬁcation and discrimination; cluster analysis'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles