Temat: component - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: Principal Component Analysis and Cluster Analysis In Multivariate Assessment of Water Quality
Autorzy:: Jankowska, J.
Radzka, E.
Rymuza, K.
Tematy:: principal component analysis
water quality
cluster analysis; Pokaż więcej
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Powiązania:: https://bibliotekanauki.pl/articles/124319.pdf Link otwiera się w nowym oknie
Opis:: This paper deals with the use of multivariate methods in drinking water analysis. During a five-year project, from 2008 to 2012, selected chemical parameters in 11 water supply networks of the Siedlce County were studied. Throughout that period drinking water was of satisfactory quality, with only iron and manganese ions exceeding the limits (21 times and 12 times, respectively). In accordance with the results of cluster analysis, all water networks were put into three groups of different water quality. A high concentration of chlorides, sulphates, and manganese and a low concentration of copper and sodium was found in the water of Group 1 supply networks. The water in Group 2 had a high concentration of copper and sodium, and a low concentration of iron and sulphates. The water from Group 3 had a low concentration of chlorides and manganese, but a high concentration of fluorides. Using principal component analysis and cluster analysis, multivariate correlation between the studied parameters was determined, helping to put water supply networks into groups according to similar water quality.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: The use of some morphological traits for the assessment of genetic diversity in spinach (Spinacia oleracea L.) landraces
Autorzy:: Ebadi-Segheloo, Asghar
Asadi-Gharneh, Hossein ali
Mohebodini, Mehdi
Janmohammadi, Mohsen
Nouraein, Mojtaba
Sabaghnia, Naser
Tematy:: breeding
cluster analysis
diversity
landraces
principal component analysis; Pokaż więcej
Wydawca:: Instytut Hodowli i Aklimatyzacji Roślin
Powiązania:: https://bibliotekanauki.pl/articles/2199739.pdf Link otwiera się w nowym oknie
Opis:: Investigation of native accessions of spinach (Spinacia oleracea L.) would be aid in the development of new genetically improved varieties, so in this research 121 spinach landraces, collected from the various spinach growing areas of Iran, were evaluated to determine their diversity using several agro-morphological traits. High coefficients of variation (CV) were recorded in fresh yield, leaf area and dry yield. Using principal component (PC) analysis, the first three PCs with eigenvalues more than 0.9 contributed 80.56% of the variability among accessions. The first PC was related to leaf yield performance (fresh and dry yields, leaf numbers at flowering and lateral branches) while the PC2 was related to leaf characteristic (leaf width, petiole length, petiole diameter and leaf area). The third PC was related to seed characteristic (seed yield and 1000-seed weight) and was named as seed property component. The 121 spinach landraces were grouped into six clusters using cluster analysis. Each cluster had some specific characteristics of its own and the clusters I and II were clearly separated from clusters III and V and also from clusters IV and VI. The studied accessions are an important resource for the generation of a core collection of spinach in the world. The results of present research will support tasks of conservation and utilization of landraces in spinach breeding programs.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: The use of some morphological traits for the assessment of genetic diversity in spinach (Spinacia oleracea L.) landraces
Autorzy:: Ebadi-Segheloo, Asghar
Asadi-Gharneh, Hossein ali
Mohebodini, Mehdi
Janmohammadi, Mohsen
Nouraein, Mojtaba
Sabaghnia, Naser
Tematy:: breeding
cluster analysis
diversity
landraces
principal component analysis; Pokaż więcej
Wydawca:: Instytut Hodowli i Aklimatyzacji Roślin
Powiązania:: https://bibliotekanauki.pl/articles/55928260.pdf Link otwiera się w nowym oknie
Opis:: Investigation of native accessions of spinach (Spinacia oleracea L.) would be aid in the development of new genetically improved varieties, so in this research 121 spinach landraces, collected from the various spinach growing areas of Iran, were evaluated to determine their diversity using several agro-morphological traits. High coefficients of variation (CV) were recorded in fresh yield, leaf area and dry yield. Using principal component (PC) analysis, the first three PCs with eigenvalues more than 0.9 contributed 80.56% of the variability among accessions. The first PC was related to leaf yield performance (fresh and dry yields, leaf numbers at flowering and lateral branches) while the PC2 was related to leaf characteristic (leaf width, petiole length, petiole diameter and leaf area). The third PC was related to seed characteristic (seed yield and 1000-seed weight) and was named as seed property component. The 121 spinach landraces were grouped into six clusters using cluster analysis. Each cluster had some specific characteristics of its own and the clusters I and II were clearly separated from clusters III and V and also from clusters IV and VI. The studied accessions are an important resource for the generation of a core collection of spinach in the world. The results of present research will support tasks of conservation and utilization of landraces in spinach breeding programs.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Multi-trait evaluation of value for cultivation and use of early maturing edible potato cultivars registered in Poland
Autorzy:: Rymuza, K.
Tematy:: edible potato
potato cultivar
principal component analysis
cluster analysis; Pokaż więcej
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Powiązania:: https://bibliotekanauki.pl/articles/123780.pdf Link otwiera się w nowym oknie
Opis:: The work presents an analysis of diversity and comparison of value for cultivation and use of early maturing potato cultivars registered with the Polish National Register of Cultivars. The comparison was based on 17 yield and appearance traits and quality attributes of tubers as well as their resistance to diseases. The analysis employed the following multi-dimensional statistical methods: principal component analysis and cluster analysis. The principal component analysis revealed that over 70% of the total variation was associated with the first 6 principal components. Cluster analysis yielded 4 groups of genotypes. The first group consisted of the cultivars which produced tubers with the most shallow eyes, the best flavour and the least severe darkening of raw flesh. The cultivars in the second group produced high yields and were low in starch, dry matter and glycoalkaloids. The tubers of cultivars which were classified into the third group had the highest starch, dry matter and vitamin C contents. However, they produced the lowest yields and were quite susceptible to most diseases. The fourth group was made up of high-yielding cultivars which tended to accumulate glycoalkaloids but were most resistant to hollow heart in tubers.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Using chemometrics to identify water quality in Daya Bay, China
Autorzy:: Wu, M.-L.
Wang, Y.-S.
Sun, C.-C.
Wang, H.
Lou, Z.-P.
Dong, J.-D.
Tematy:: robust principal component analysis
water quality
chemometrics
China
cluster analysis
Daya Bay; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Instytut Oceanologii PAN
Powiązania:: https://bibliotekanauki.pl/articles/49096.pdf Link otwiera się w nowym oknie
Opis:: In this paper, chemometric approaches based on cluster analysis, classical and robust principal component analysis were employed to identify water quality in Daya Bay (DYB), China. The results show that these approaches divided water quality in DYB into two groups: stations S3, S8, S10 and S11 belong to cluster A, which lie in Dapeng Cove, Aotou Harbor and the north-eastern part of DYB, where water quality is related mainly to anthropogenic activities. The other stations belong to cluster B, which lie in the southern, central and eastern parts of DYB, where the quality is related mainly to water exchange with the South China Sea. Cluster analysis yields good results as a first exploratory method for evaluating spatial difference, but it fails to demonstrate the relationship between variables and environmental quality on the one hand and the untreated data on the other. However, with the aid of suitable chemometric approaches, the relationship between samples or variables can be investigated. Classical and robust principal component analysis can provide a visual aid for identifying the water environment in DYB, and then extracting specific information about relationships between variables and spatial variation trends in water quality.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Principal component and cluster analysis for determining diversification of bottom morphology based on bathymetric profiles from Brepollen (Hornsund, Spitsbergen)
Autorzy:: Moskalik, T.
Tegowski, J.
Grabowiecki, P.
Zulichowska, M.
Tematy:: principal component
cluster analysis
bottom morphology
diversification
bathymetry
Hornsund
Spitsbergen
post-glacial region; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Instytut Oceanologii PAN
Powiązania:: https://bibliotekanauki.pl/articles/47566.pdf Link otwiera się w nowym oknie
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Multivariate diversity of Polish winter triticale cultivars for spike and other traits.
Autorzy:: Kociuba, Wanda
Mądry, Wiesław
Kramek, Aneta
Ukalski, Krzysztof
Studnicki, Marcin
Tematy:: canonical variate analysis
cluster analysis
cultivars
principal component analysis
spike traits
winter triticale; Pokaż więcej
Wydawca:: Instytut Hodowli i Aklimatyzacji Roślin
Powiązania:: https://bibliotekanauki.pl/articles/2199592.pdf Link otwiera się w nowym oknie
Opis:: The objective of the present study was to determine the extent and pattern of genotypic diversity for six spike quantitative characters and two other traits in 36 winter triticale cultivars released in Poland, to classify the cultivars into similarity groups (clusters) and to identify those traits, among the studied ones, which mostly discriminated distinguished groups of cultivars. The 36 cultivars, released in the period from 1982 to 1999, were evaluated across three years 2002-2004 at the Experimental Field Station in Czesławice near Nałęczów, Poland. The experiments were carried out on the brown soil with loess subsoil. In each year the one-replicated experimental design was used with 2 m2 plots, rows 20 cm apart, and dense sowing using about 2 cm spacing of seeds. Analyses of variance for each trait data according to the random model (both cultivars and years were assumed to be random factors) were done. To classify and characterize genotypic diversity of the cultivars for the eight traits, the pattern analysis was used. It involved both cluster analysis using Ward’s procedure with a measure of the multivariate similarity among cultivars being Squared Euclidean Distance and canonical variate analysis (CVA) on the basis of cultivar BLUPs for the original traits. Quite different groups of cultivars for the studied traits were found, specially one group was substantially distanced to the others. As it was shown by CVA, spike length and number of spikelets per spike as negatively correlated with number of grains per spikelet in the studied set of the cultivars relatively largest contributed to overall differentiation of the distinguished eight groups and then, these traits best discriminated among the eight cultivar groups in the term of Mahalanobis distance for the considered traits. The 1000 grain weight and grain protein content much less contributed to overall discrimination of the cultivar groups than the previous four traits. The most important agronomic traits characterizing productivity of the spike grain weight and its two components, e.g. number of grains per spikelet and number of grains per spike had least discriminating power for the groups of cultivars. Grain yield per unit area of cereals is a result of spike grain yield and the number of spikes per unit area. In these studies of winter triticale cultivar diversity only grain spike yield and its components were included. Thus, the presented study are a primary evaluating of phenotypic diversity in the cultivars. The further study on the cultivar diversity evaluation for grain yield per unit area and its components is necessary...
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 8.

Tytuł:: Multivariate diversity of Polish winter triticale cultivars for spike and other traits.
Autorzy:: Kociuba, Wanda
Mądry, Wiesław
Kramek, Aneta
Ukalski, Krzysztof
Studnicki, Marcin
Tematy:: canonical variate analysis
cluster analysis
cultivars
principal component analysis
spike traits
winter triticale; Pokaż więcej
Wydawca:: Instytut Hodowli i Aklimatyzacji Roślin
Powiązania:: https://bibliotekanauki.pl/articles/55928413.pdf Link otwiera się w nowym oknie
Opis:: The objective of the present study was to determine the extent and pattern of genotypic diversity for six spike quantitative characters and two other traits in 36 winter triticale cultivars released in Poland, to classify the cultivars into similarity groups (clusters) and to identify those traits, among the studied ones, which mostly discriminated distinguished groups of cultivars. The 36 cultivars, released in the period from 1982 to 1999, were evaluated across three years 2002-2004 at the Experimental Field Station in Czesławice near Nałęczów, Poland. The experiments were carried out on the brown soil with loess subsoil. In each year the one-replicated experimental design was used with 2 m2 plots, rows 20 cm apart, and dense sowing using about 2 cm spacing of seeds. Analyses of variance for each trait data according to the random model (both cultivars and years were assumed to be random factors) were done. To classify and characterize genotypic diversity of the cultivars for the eight traits, the pattern analysis was used. It involved both cluster analysis using Ward’s procedure with a measure of the multivariate similarity among cultivars being Squared Euclidean Distance and canonical variate analysis (CVA) on the basis of cultivar BLUPs for the original traits. Quite different groups of cultivars for the studied traits were found, specially one group was substantially distanced to the others. As it was shown by CVA, spike length and number of spikelets per spike as negatively correlated with number of grains per spikelet in the studied set of the cultivars relatively largest contributed to overall differentiation of the distinguished eight groups and then, these traits best discriminated among the eight cultivar groups in the term of Mahalanobis distance for the considered traits. The 1000 grain weight and grain protein content much less contributed to overall discrimination of the cultivar groups than the previous four traits. The most important agronomic traits characterizing productivity of the spike grain weight and its two components, e.g. number of grains per spikelet and number of grains per spike had least discriminating power for the groups of cultivars. Grain yield per unit area of cereals is a result of spike grain yield and the number of spikes per unit area. In these studies of winter triticale cultivar diversity only grain spike yield and its components were included. Thus, the presented study are a primary evaluating of phenotypic diversity in the cultivars. The further study on the cultivar diversity evaluation for grain yield per unit area and its components is necessary...
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Porównanie wybranych statystycznych metod analizy danych hydrogeochemicznych na przykładzie kenozoicznych poziomów wodonośnych w obszarze zlewni Gwdy
Comparison of selected statistical methods of hydrogeochemical data analysis exemplified by Cenozoic aquifers within the Gwda River basin
Autorzy:: Kotowski, T.
Tematy:: hydrogeochemia
analiza skupień
analiza składowych głównych
analiza czynnikowa
hydrogeochemistry
cluster analysis
principal component analysis
factor analysis; Pokaż więcej
Wydawca:: Państwowy Instytut Geologiczny – Państwowy Instytut Badawczy
Powiązania:: https://bibliotekanauki.pl/articles/2062952.pdf Link otwiera się w nowym oknie
Opis:: W pracy zaprezentowano porównanie wybranych metod wnioskowania statystycznego, stosowanych w badaniach hydrogeochemicznych. Metody statystyczne zostały zastosowane w celu wstępnej identyfikacji procesów formowania składu chemicznego wód poziomów mioceńskiego i głębokiego plejstoceńskiego na obszarze zlewni Gwdy. W rezultacie przeprowadzonej analizy skupień otrzymano trzy grupy (skupienia) czynników kształtujących skład chemiczny wód podziemnych. W wyniku analizy składowych głównych i analizy czynnikowej wyróżniono zbiory dwóch czynników kształtujących skład chemiczny wód podziemnych. Wszystkie zastosowane metody okazały się wrażliwe na występowanie anomalii hydrogeochemicznych. Z tego względu, w przypadku analizy skupień i analizy składowych głównych, niemożliwe było dokonanie w pełni poprawnego opisu chemizmu wód podziemnych w obszarze badań. Najlepsze rezultaty osiągnięto przy zastosowaniu analizy czynnikowej. Wyniki analiz statystycznych odniesiono do rezultatów dodatkowych badań: składu izotopowego wody, stężeń siarczanów, trytu oraz badań mikrobiologicznych. Zastosowane metody statystyczne okazały się pomocne, jednakże interpretacja uzyskanych, szczególnie zróżnicowanych danych, jest utrudniona.
Comparison of selected methods of hydrogeochemical statistical analysis is presented in the paper. Statistical methods were applied to initially identify the formation processes of groundwater chemical composition within the Gwda river basin. As a result of a cluster analysis, three cluster sets of factors forming the chemical composition of the groundwater were distinguished. A set of two factors forming the chemical composition of the groundwater was distinguished as a result of a principal component analysis and a factor analysis. All the statistical methods used were found out to be susceptible upon hydrogeochemical anomalies. The observed susceptibility of the cluster analysis and the principal component analysis allowed a fully correct description of the formation of the groundwater chemical composition in the study area. The best results were achieved using the factor analysis, but this method is also susceptible upon the anomaly cases. The results of the statistical analysis were compared with the research results of additional factors such as the isotopic composition of water and concentrations of sulfates and tritium. The statistical methods appeared to be helpful. However, the interpretation of research results without the additional factors is intractable, especially in the case of hydrogeochemical anomalies.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: Classifying railway passenger stations for use transport planning – application to Bulgarian railway network
Classification des gares de chemin de fer de passagers concernant l’emploi de planification des transports –application pour le réseau de fer de la Bulgarie
Autorzy:: Stoilova, S.
Nikolova, R.
Tematy:: principal component
cluster analysis
railway station
passengers
classification
główne składowe
analiza klasterów
stacja kolejowa
pasażerowie
klasyfikacja; Pokaż więcej
Wydawca:: Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
Powiązania:: https://bibliotekanauki.pl/articles/374397.pdf Link otwiera się w nowym oknie
Opis:: A methodology for the classification of railway passenger stations was developed in this study. Four groups of factors are defined to study the characteristics of the station: potential of the town, importance of the town, infrastructural factors, and characteristics of passengers. In the research we investigated 18 factors and studied 98 passenger stations of railway network in Bulgaria. The method of principal components has been applied for grouping the factors and cluster analysis has been applied to classify the stations. The factors have been classified into 4 components by the method of principal components. The stations have been classified into 6 groups using hierarchical cluster analysis. The methods, Average linkage between group and Within-groups linkage, and distance-type measures Euclidean distance and Squared Euclidean distance were compared to verify the results of cluster analysis. The grouping of the stations has been used for the determination of the stops for categories intercity passenger trains. The main groups of stations for servicing express trains are the first, second, third, fourth and fifth groups. In the sixth group are stations for servicing fast passenger trains. The methodology can be applied to the study of all stations and stops in the rail network.
Dans cette étude est élaborée la méthodologie de classification des gares de passagers. On a déterminé 4 groupes de facteurs pour l’étude des caractéristiques des gares: le potentiel de la ville, importance de la ville, facteurs infrastructurels et caractéristiques des passagers.18 facteurs sont étudiés au total. On a étudié 98 gares de passagers du réseau de fer de la Bulgarie. On a appliqué les méthodes des composantes générales pour le groupement des facteurs et une analyse de cluster pour le classement des gares. D’après la méthode des composantes générales les facteurs sont classifiés en 4 groupes. D’après la méthode de l’analyse hiérarchique les gares sont classifiées en 6 groupes. Les méthodes de liaison moyenne entre le groupe et les intra-groupes de liaison et la distance de type Euclidienne au carré ont été comparées à la verification des résultats de l’analyse de cluster. Le groupement des gares est utilize pour déterminer les arrêts des cathégories des trains de passagers interurbains. Les groups de gares essentiels concernant le service des trains express sont premier, deuxième, troisième, quatrième et cinquième groupe. Le sixième groupe comprend les gares pour le service des TGV. La méthodologie peut être appliquée pour l’étude de toutes les gares et stations dans le réseau de chemin de fer.
Dostawca treści:: Biblioteka Nauki

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