Zusammenfassung
Es werden die folgenden in der numerischen Taxonomie gebräuchlichen 11 Ähnlichkeitsmaße auf ihre Anwendbarkeit geprüft: Koeffizient vonJaccard (2 Varianten), simple matching-Koeffizient, Koeffizient vonRogers undTanimoto, Phi-Koeffizient, Koeffizient vonGower, mittlere Merkmalsdifferenz, mittlerer quadratischer Abstand, Canberra-Metrik, Divergenzkoeffizient vonClark und Produkt-Moment-Korrelationskoeffizient vonPearson.
Die Untersuchung erfolgte anhand von 312 Sippen der GattungPisum. Die an ihren bonitierten 71 Merkmale wurden zu vier Merkmalssätzen (Gesamtheit der Merkmale, alle quantitativen Merkmale, alle qualitativen Merkmale, 21 ausgewählte qualitative Merkmale) zusammengestellt. Für die Gruppenbildung wurde die unbewichtete Paar-Gruppen-Methode mit arithmetischen Mittelwerten (UPGMA) benutzt. Insgesamt ergaben sich 50 verschiedene Dendrogramme, aufgrund derer die Ähnlichkeitsmaße eingeschätzt wurden. Die Auswertung der Dendrogramme erfolgte durch die Informationsmaße Sumrat und Samrat, den F-Index und die Hauptkomponentenanalyse.
Die Hauptaussagen der Arbeit sind: (1) Alle Ähnlichkeitsmaße ergeben in Abhängigkeit von den Merkmalssätzen sowohl taxonomisch brauchbare als auch taxonomisch unbrauchbare Dendrogramme. (2) Von den geprüften 11 Koeffizienten erweisen sich bei Vorliegen von überwiegend vielstufigen Merkmalen die Canberra-Metrik und bei Berücksichtigung von ausschließlich zweistufigen Merkmalen der simple matching-Koeffizient als gut. (3) Während die Verwendung aller 71 Merkmale und der 28 quantitativen Merkmale zu taxonomisch ungeeigneten Dendrogrammen führt, resultieren bei Benutzung der qualitativen Merkmale, insbesondere der ausgewählten 21, taxonomisch brauchbare Dendrogramme. (4) Dendrogramme, basierend auf wenigen Merkmalen, haben höhere Informationsgehalte als vergleichbare Dendrogramme, die auf einer größeren Anzahl von Merkmalen beruhen. (5) Unter den analysierten Faktoren übt die Auswahl der Merkmale den größten Einfluß auf die Dendrogrammbildung aus, es folgt die Merkmalskodierung und danach der Ähnlichkeitskoeffizient. (6) Für die UnterartP. sativum L. s. l. ssp.sativum ergibt sich ein Vorschlag für eine Neuklassifikation, in der für die Hauptgruppen die Differentialmerkmale Blütenfarbe, Pergamentschicht und Samenform oder Zeichnung der Samenschale in der genannten Reihenfolge berücksichtigt werden müßten.
Summary
The following 11 similarity coefficients, which are often used in numerical taxonomy, are compared to test their applicability: coefficient ofJaccard (two different readings), simple matching coefficient, coefficient ofRogers andTanimoto, phi coefficient, general similarity coefficient ofGower, mean character difference, mean square distance, Canberra metric, coefficient of divergence, andPearson's product-moment correlation coefficient.
The studies were based on 312 taxa of the genusPisum for which 71 characters had been measured. Four character sets have been established: totality of the characters, all quantitative characters, all qualitative characters, and 21 carefully selected qualitative characters. The clustering method selected was the unweighted pair-group method using arithmetic averages (UPGMA). Thus 50 different dendrograms were elaborated. The dendrograms were analysed by the information-theoretic measures SUMRAT and SAMRAT, the F-index, and the principal component analysis.
The following main results were obtained: (1) Depending on the character sets every similarity coefficient yields taxonomic useful and taxonomic useless dendrograms. (2) The investigation shows that if the greater part of the characters are multistate characters the Canberra metric proves best, but if only two-state characters are used the simple matching coefficient is the best one. (3) Dendrograms based on all of the 71 characters or the 28 quantitative characters make no taxonomic sense; the choice of the qualitative characters, especially the selected 21 ones, yields taxonomic useful dendrograms. (4) Dendrogra msbased on few characters have greater information contents than comparable ones based on a greater number of characters. (5) Among the analysed factors the selection of characters had the most important influence upon the construction of the dendrograms; it is followed by the codification of the characters and finally by the kind of the used similarity coefficient. (6) ForP. sativum L. s. l. ssp.sativum guide-lines for a new classification could be proposed; flower colour, parchment-layer, and shape of seed or mottling of the seed-coat should be taken into account in this sequence as the taxonomically most important differential characters.
Краткое содержание
Исследуется возможн ость применения след ующих одинадцати коэффици ентов сходства, часто испол ьзуемых в нумерическ ой таксономии: коэффици енты Жакарда (в двух вариан тах), Роджерса и Танимо то, Гоуера, коэффициенты «фи» и «simple matching», средняя ра зница признаков, сред няя квадратическая дистанция, «Canberra metric», коэфф ициент дивергенции Клерка и корреляцион ный коэффициент Пирсона.
Исследования провод ились на 312 формах родаPisum. Бонитировался 71 признак; признаки обр абатывались как 4 разл ичных набора (все признаки, 28 количественных приз наков, 43 качественных и 21 отобранный качестве нный признак). Для группиро вки применялся метод невзвешенных парных групп с арифметическ ими средними. Всего бы ло составлено 50 различны х дендрограмм, на основ ании которых оценива лись коэффициенты сходст ва. Дендрограммы обраба тывались с помощью информационных мер, F-и ндекса и анализа главных ком понентов.
Работа позволяет сде лать следующие вывод ы. (1) В зависимости от набор а признаков все коэффи циенты сходства дают как приемлемые, так и непр иемлемые, с точки зрения таксон омии, дендрограммы. (2) И з 11 испытанных коэффици ентов хорошие результаты д али: при преобладании призна ков со многими состояниями — «Canberra metric», а при учёте толь ко признаков с двумя состояниями — « simple matching»-коэффициент. (3) В то время как использование всех п ризнаков (т. е. 71), или 28 количественных — при вело к таксономически непр игодным дендрограмм ам, использование качес твенных признаков, в особенно сти 21 отобранного — дал о таксономически прие млемые дендрограммы. (4) Дендро граммы, полученные пр и учёте малого количества признаков обладают б олее богатым информа ционным содержанием, чем сравнимые дендрогра ммы, построенные на бо льшем количестве признако в. (5) Самое сильное влияни е на образование денд рограмм, из анализированных факторов, оказывает в ыбор признаков, за ним следует кодирование признак ов и вслед за ним — коэффи циент сходства. (6) Для подвида ssp.sativum можно предложить нов ую классификацию, в ко торой для главных групп следовало бы учитыва ть как дифференциаль ные признаки: окраску цве тка, затем характер перга ментного слоя и затем форму семени или рисунок семенной кожуры.
Literatur
Akinola, J. O., andP. C. Whiteman, 1972: A numerical classification ofCajanus cajan (L.) Millsp. accessions based on morphological and agronomic attributes. - Aust. J. agric. Res.23, 995–1005.
Alefeld, F., 1866: Landwirtschaftliche Flora. - Wiegandt und Hempel, Berlin.
Barrett, H. C., S. G. Carmer, andA. M. Rhodes, 1969: A taximetric study of interspecific variation inVitis. - Vitis8, 177–187.
Baum, B. R., 1974: Classification of the oat species (Avena, Poaceae) using various taximetric methods and an information-theoretic model. - Canad. J. Bot.52, 2241–2262.
—, 1977: Oats: wild and cultivated. A monograph of the genusAvena L. (Poaceae). - Biosystematics Research Institute, Canada Department of Agriculture, Research Branch, Ottawa, Ontario, Canada. Monograph No. 14.
—, andL. P. Lefkovitch, 1972: A model for cultivar classification and identification with reference to oats (Avena). I. Establishment of the groupings by taximetric methods. - Canad. J. Bot.50, 121–130.
Bidault, M. etJ. M. Hubac, 1967: Application des méthodes numériques de la taxinomie sur une série de populations deFestuca ovina L. ssp.eu-ovina Hack. - C. R. Acad. Sci., Paris, Sér. D264, 1785–1788.
Bird, R. McK., andM. M. Goodman, 1977: The races of maize V: Grouping maize races on the basis of ear morphology. - Econ. Bot.31, 471–481.
Boyce, A. J., 1969: Mapping diversity: a comparative study of some numerical methods. In:A. J. Cole (ed.), Numerical taxonomy. Proc. of the Coll. in Numerical Taxonomy held in the University of St. Andrews, September 1968, pp. 1–31. - Academic Press, London and New York.
Burt, R. L., L. A. Edye, W. T. Williams, B. Grof, andC. H. L. Nicholson, 1971: Numerical analysis of variation patterns in the genusStylosanthes as an aid to plant introduction and assessment. - Aust. J. agric. Res.22, 737–757.
Cain, A. J., andG. A. Harrison, 1958: An analysis of the taxonomist's judgment of affinity. - Proc. zool. Soc. Lond.131, 85–98.
Clark, P. J., 1952: An extension of the coefficient of divergence for use with multiple characters. - Copeia2, 61–64.
Cubero, J. I., 1975: The research on the chickpea (Cicer arietinum) in Spain. In: International Workshop on Grain Legumes, January 13–16, 1975, pp. 117–122. - Internatl. Crops Res. Inst. for the Semi-Arid Tropics, Hyderabad, India.
Drury, D. G., andJ. M. Randal, 1969: A numerical study of the variation in the New ZealandErechtiles arguta-scaberula complex (Senecioneae-Compositae). - N. Z. J. Bot.7, 56–75.
Edye, L. A., W. T. Williams, andA. J. Pritchard, 1970: A numerical analysis of variation patterns in Australian introductions ofGlycine wightii (G. javanica). - Aust. J. agric. Res.21, 57–69.
Ernst, W. R., 1967: Floral morphology and systematics ofPlatystemon and its alliesHesperomecon andMeconella (Papaveraceae: Platystemonoideae). - Univ. Kansas Sci. Bull.47, 25–70.
Fanizza, G., andT. P. Bogyo, 1976: A cluster analysis of almond varieties in Apulia. - Riv. Ortoflorofrutt. It.60, 277–281.
Goodman, M. M., andR. McK. Bird, 1977: The races of maize IV: Tentative grouping of 219 Latin American races.- Econ. Bot.31, 202–221.
Govorov, L. I., 1937: Goroch. V.: N. I.Vavilov i. E. V.Vul'f (Red. izd.), Kul'turnaja flora SSSR.4, S. 229–336. - Gosudarstvennoe izdatel'stvo sovchoznoj i kolchoznoj literatury, Moskva i Leningrad.
Gower, J. C., 1966: Some distance properties of latent root and vector methods used in multivariate analysis. - Biometrika53, 325–338.
—, 1967a: A comparison of some methods of cluster analysis. - Biometrics23, 623–637.
—, 1967b: Multivariate analysis and multidimensional geometry. - Statistician17, 13–28.
—, 1971: A general coefficient of similarity and some of its properties. - Biometrics27, 857–871.
Hall, A. V., 1967: Studies in recently developed group-forming procedures in taxonomy and ecology. - J. South Afr. Bot.33, 185–196.
Ivimey-Cook, R. B., 1968: Investigations into the phenetic relationships between species ofOnonis L. - Watsonia7, 1–23.
—, 1969: The phenetic relationships between species ofOnonis. In:A. J. Cole (ed.). Numerical taxonomy. Proc. of the Coll. in Numerical Taxonomy held in the University of St. Andrews, September 1968, pp. 69–90. - Academic Press, London and New York.
Johnson, M. P., andR. W. Holm, 1968: Numerical taxonomic studies in the genusSarcostemma R. Br. (Asclepiadaceae). In:V. H. Heywood (ed.), Modern methods in plant taxonomy, pp. 199–217. - Academic Press, London and New York.
Kamijima, O., 1974: Characteristics and classification of so-called dwarf rice. II. Principal component analysis of the panicle and internode lengths in dwarf strains of rice and its implication in grouping the strains. - Jap. J. Breed.24, 261–268.
Körnicke, F., 1873: Systematische Uebersicht der Cerealien und monocarpischen Leguminosen in Aehren, Rispen, Frü chten und Samen. - Carl Georgi, Bonn.
Kuiper, F. K., andL. Fisher, 1975: A Monte Carlo comparison of six clustering procedures. - Biometrics31, 777–783.
Lamprecht, H., 1974: Monographie der GattungPisum. - Steiermärkische Landesdruckerei, Graz.
Lance, G. N., andW. T. Williams, 1966: Computer programs for hierarchical polythetic classification (“ similarity analyses”). - Computer J.9, 60–64.
—, and —, 1967a: A general theory of classificatory sorting strategies. I. Hierarchical systems. - Computer J.9, 373–380.
—, and —, 1967b: Mixed-data classificatory programs. I. Agglomerative systems. - Aust. Computer J.1, 15–20.
Legendre, P., andD. J. Rogers, 1972: Characters and clustering in taxonomy: a synthesis of two taximetric procedures. - Taxon21, 567–606.
Lehmann, Chr. O., 1954: Das morphologische System der Saaterbsen (Pisum sativum L. sens. lat. Gov. ssp.sativum). - Züchter24, 316–337.
Leuschner, D., 1974: Einführung in die numerische Taxonomie. - VEB Gustav Fischer Verlag, Jena.
Liang, G. H. L., andA. J. Casady, 1966: Quantitative presentation of the systematic relationships among twenty-oneSorghum species. - Crop Sci.6, 76–79.
Makaševa, R. Ch., 1973: Goroch. - Kolos, Leningrad.
Mannetje, L. 't, 1967: A comparison of eight numerical procedures applied to the classification of some AfricanTrifolium. taxa based onRhizobium affinities. - Aust. J. Bot.15, 521–528.
—, 1969:Rhizobium affinities and phenetic relationships within the genusStylosanthes. - Aust. J. Bot.17, 553–564.
Michener, C. D., andR. R. Sokal, 1957: A quantitative approach to a problem in classification. - Evolution11, 130–162.
Molina-Cano, J. L., 1976: A numerical classification of some European barley cultivars (Hordeum vulgare L. s. i.). - Z. Pflanzenz.76, 320–333.
Müller, P. H., P. Neumann undR. Storm, 1973: Tafeln der mathematischen Statistik. - VEB Fachbuchverlag, Leipzig.
Olson, E. C., 1964: Morphological integration and the meaning of characters in classification systems. In: V. H.Heywood, and J.McNeill (eds.), Phenetic and phylogenetic classification, pp. 123–156. - Syst. Ass. Pub.6, London.
Parker, W. H., 1976: Comparison of numerical taxonomic methods used to estimate flavonoid similarities in the Limnanthaceae. - Brittonia28, 390–399.
Pernes, J., D. Combes etR. Réné-Chaume, 1970: Différenciation des populations naturelles duPanicum maximum Jacq. en Côte-d'Ivoire par acquisition de modifications transmissibles, les unes par graines apomictiques, d'autres par multiplication végétative. - C. R. Acad. Sci., Paris, Sér. D270, 1992–1995.
Ramon, S., 1968: A numerical taxonomic study of certain taxa ofHaplopappus. sectionBlepharodon. - Univ. Kansas Sci. Bull.47, 863–900.
Rhodes, A. M., W. P. Bemis, T. W. Whitaker, andS. G. Carmer, 1968: A numerical taxonomic study ofCucurbita. - Brittonia20, 251–266.
—,C. Campbell, S. E. Malo, andS. G. Carmer, 1970: A numerical taxonomic study of the mangoMangifera indica L. - J. Amer. Soc. hort. Sci.95, 252–256.
—, andS. G. Carmer, 1966: Classification of sweet corn inbreds by methods of numerical taxonomy. - Proc. Amer. Soc. hort. Sci.88, 507–515.
—' —, andJ. W. Courter, 1969: Measurement and classification of genetic variability in horseradish.- J. Amer. Soc. hort. Sci.94, 98–102.
—,S. E. Malo, C. W., Campbell, andS. G. Carmer, 1971: A numerical taxonomic study of the avocado (Persea americana Mill.). - J. Amer. Soc. hort. Sci.96, 391–395.
—, andF. W. Martin, 1972: Multivariate studies of variations in yams (Dioscorea alata L.).- J. Amer. Soc. hort. Sci.97, 685–688.
Rogers, D. J., andT. T. Tanimoto, 1960: A computer program for classifying plants. - Science132, 1115–1118.
Rohlf, F. J., 1963: Classification ofAedes by numerical taxonomic methods (Diptera: Culicidae). - Ann. Entomol. Soc. Amer.56, 798–804.
—, 1968: Stereograms in numerical taxonomy. - Syst. Zool.17, 246–255.
—, 1970: Adaptive hierarchical clustering schemes. - Syst. Zool.19, 58–82.
Small, F., P. Y. Jui, andL. P. Lefkovitch, 1976: A numerical taxonomic analysis ofCannabis with special reference to species delimitation. - Syst. Bot.1, 67–84.
Sneath, P. H. A., 1969: Evaluation of clustering methods. In:A. J. Cole (ed.), Numerical taxonomy. Proc. of the Coll. in Numerical Taxonomy held in the University of St. Andrews, September 1968, pp. 257–271. - Academic Press, London and New York.
Sneath, P. A. H., andR. R. Sokal, 1973: Numerical taxonomy. The principles and practice of numerical classification. - W. H. Freeman and Company, San Francisco.
Sokal, R. R., 1960: Die Grundlagen der numerischen Taxonomie. - Verhandl. XI. Internat. Kong. Entomol.1, 7–12.
—, andC. D. Michener, 1958: A statistical method for evaluating systematic relationships. - Univ. Kansas Sci. Bull.38, 1409–1438.
—, and —, 1967: The effects of different numerical techniques on the phenetic classification of bees of theHoplitis complex (Megachilidae). - Proc. Linn. Soc. Lond.178, 59–74.
—, andF. J. Rohlf, 1962: The comparison of dendrograms by objective methods, - Taxon11, 33–40.
—, andP. H. A. Sneath, 1963: Principles of numerical taxonomy. - W. H. Freeman and Company, San Francisco and London.
Teräsvuori, K., 1915: Über in Finnland feldmäßig gebaute Erbsenformen. Experimentelle Vererbungsuntersuchungen mit besonderer Berücksichtigung der Anzahl der Samenanlagen und Samen in den Hülsen. - Acta Soc. Fauna Flora fenn.40 (9) Helsinki.
Yamada, T., andS. Suzuki, 1975: Classification of alfalfa cultivars by the clustering method based on quantitative characters: its significance in the introduction and conservation of genetic resources. - JIBP Synthesis5, 137–143, 145.
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Meyer, D. Numerisch-taxonomische Untersuchungen anPisum sativum L.. Die Kulturpflanze 28, 285–340 (1980). https://doi.org/10.1007/BF02014725
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DOI: https://doi.org/10.1007/BF02014725