‘10; MSU RETURNING MATERIALS: P1ace in book drop to LJBRARJES remove this checkout from ” your record. FINES Ni” be charged if book is returned after the date stamped below. NOV182001 um, A MULTIVARIATE ANALYSIS OF A SOUR CHERRY GERMPLASM COLLECTION BY Karl William Hillig A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Department of Horticulture Plant Breeding and Genetics 1988 ABSTRACT A MULTIVARIATE ANALYSIS OF A SOUR CHERRY GERMPLASM COLLECTION BY Karl William Hillig Morphological traits of 16 sour cherry (Erungg ggxggug L.) cultivars, and of hybrid and open-pollinated seedlings of germplasm collected in eastern Europe were evaluated with principal component (PC) and cluster analysis. Due to the character loadings of the first three PCs in each analysis, some of the PCs can be interpreted as representing gradations between morphol- ogies characteristic of the two presumed progenitor species, sweet cherry (2‘ gxigm L.) and ground cherry (2L frutiggsg Pall.). Genetically related cultivars and families tend to cluster, indicating that there is a significant genetic component to the underlying patterns of morphological variation. Families of cold-hardy Russian cultivars generally show a greater morphological resemblence to ground cherry than do families of less cold-hardy cultivars, suggesting that selective forces may also have contributed to the patterns of morphological variation detected. ACKNOWLEDGEMENTS I am grateful for the advice and support I have received from Dr. Amy Iezzoni, my major professor. I thank my other committee members, Dr. Thomas Isleib and Dr. James Hancock Jr., for sharing with me their enthusiasm in their work. ‘ I appreciate the efforts of Ann Hancock and Karen Redding in collecting the set of cultivar data which I have included in this thesis. Finally, I express my sincerest regards to my parents, Drs. Beth and William Hillig, for the love and encouragement they have given me through the years. iii TABLE OF CONTENTS LIST OF TABLES . . . . . . . . . . . . . . . . . . . LIST OF FIGURES . . . . . . . . . . . . . . . . . . INTRODUCTION . . . . . . . . . . . . . . . . . . . . LITERATURE REVIEW . . . . . . . . . . . . . . . . . Geneaology . . . . . . . . . . . . . . . . . . . . Applications of Multivariate Analysis . . . . . . MATERIALS AND METHODS . . . . . . . . . . . . . . . Plant Material . . . . . . . . . . . . . . . . . . Characters Measured . . . . . . . . . . . . . . . Data Analysis . . . . . . . . . . . . . . . . . . RESULTS . . . . . . . . . . . . . . . . . . . . . . Cultivar Analysis . . . . . . . . . . . . . . . . 1985 Seedling Analysis . . . . . . . . . . . . . . 1986 Seedling Analysis . . . . . . . . . . . . . . DISCUSSION . . . . . . . . . . . . . . . . . . . . . Morphology . . . . . . . . . . . . . . . . . . . . Character Variation . . . . . . . . . . . . . . . Genetic Implications . . . . . . . . . . . . . . . LIST OF REFERENCES . . . . . . . . . . . . . . . . . APPENDIX A: Means and Ranges of Morphological Traits APPENDIX B: Computer Programs . . . . . . . . . . . iv Page vii 14 14 20 28 30 30 37 41 51 51 57 65 70 76 81 LIST OF TABLES Table 1. 2. 10. 11. Number of clones evaluated, with names and abbreviations of 16 sour cherry cultivars. . . . Number of progenies evaluated in the 'English Morello' half-sib family, with names and abbreviations of the paternal parents. . . . . . Number of progenies evaluated in the 'Rheinische Schattenmorelle' half-sib family, with names and abbreviations of the paternal parents. . . . Number of progenies evaluated in the 'Wolynska' half-sib family, with names and abbreviations of the paternal parents. . . . . . . . . . . . . Number of progenies evaluated in the 'Montmorency' half-sib family, with names and abbreviations of the paternal parents. . . . . . . . . . . . . . . Number of progenies evaluated in the open- pollinated families, with names and abbreviations of the maternal parents. . . . . . . . . . . . . Pedigrees of cultivars and of parents of seed- lings evaluated in the sour cherry germplasm collection. . . . . . . . . . . . . . . . . . . . Character codes and units for characters and character ratios employed in numerical analyses 0 O O O O O O O O O O O O O O O O O O O O Eigenvalues of the first seven PC axes from PC analysis of 16 sour cherry cultivars, with pro- portion of total variance accounted for by each aXis. O O O O O O O O O O O O O O O O O O O O 0 O Eigenvectors of the first seven PC axes from PC analysis of 16 sour cherry cultivars. . . . . Pearson correlation coefficients between traits for 16 sour cherry cultivars. . . . . . . . . . . Page 15 16 17 17 18 19 21 26 31 35 36 Table Page 12. Eigenvalues of the first seven PC axes from PC analysis of the 'English Morello', 'Rheinische Schattenmorelle', and 'Wolynska' half—sib families, with proportion of total variance accounted for by each axis. . . . . . . . . . . . . . . . . . . . 37 13. Eigenvectors of the first seven PC axes from PC analysis of the 'English Morello', 'Rheinische Schattenmorelle', and 'Wolynska' half-sib families. 40 14. Eigenvalues of the first seven PC axes from PC analysis of the open-pollinated and 'Montmorency' half-sib families, with proportion of total vari- ance accounted for by each axis. . . . . . . . . 44 15. Eigenvectors of the first seven PC axes from PC analysis of the open-pollinated and 'Montmorency' half-sib families. . . . . . . . . . . . . . . . 48 16. Sign and number for the 15 open-pollinated families in which there were significant Pearson correlation coefficients between traits. . . . . 50 A1. Means of the flower, fruit, and vegetative char- acters measured on 16 sour cherry cultivars. . . 76 A2. Full-sib family means and ranges of morphological characters measured on the 'English Morello', 'Rheinische Schattenmorelle', and 'Wolynska' half-sib families. . . . . . . . . . . . . . . . 77 A3. Full-sib family means and ranges of morphological characters measured on the 'Montmorency' half-sib family. 0 O O O O O O O O O O O O O O 0 0 O O O 0 79 A4. Means and ranges of morphological characters measured on the open-pollinated families. . . . . 80 B1. SAS program for computing means and ranges. . . . 81 82. SAS program for computing Pearson correlation coefficients. . . . . . . . . . . . . . . . . . . 82 B3. SAS program for analysis of variance. . . . . . . 83 B4. SAS program for principal component analysis. . . 84 B5. Clustan program for cluster analysis. . . . . . . 85 vi LIST OF FIGURES Figure Page 1. Positions of PC scores of 16 sour cherry cultivars on the first three PC axes. . . . . . . 32 2. Dendrogram representing cluster analysis of 16 sour cherry cultivars. . . . . . . . . . . . . . 34 3. Positions of PC scores of family means on the first three PC axes for the 'English Morello', 'Rheinische Schattenmorelle', and 'Wolynska' half-sib families. . . . . . . . . . . . . . . . 39 4. Dendrogram representing cluster analysis of the 'English Morello' half-sib family. . . . . . . . 42 5. Dendrogram representing cluster analysis of the 'Rheinische Schattenmorelle' half-sib family. . . 43 6. Dendrogram representing cluster analysis of the 'Wolynska' half-sib family. . . . . . . . . . . . 43 7. Positions of PC scores of family means on the first three PC axes for the 'Montmorency' half- sib family and open-pollinated families. . . . . 45 8. Dendrogram representing cluster analysis of the 'Montmorency' half-sib family. . . . . . . . . . 47 9. Dendrogram representing cluster analysis of the open-pollinated families. . . . . . . . . . . . . 47 10. Leaf samples of 2‘ axing, 2‘ cg;§_u§, and ,2; frutigggg. . . . . . . . . . . . . . . . . . 53 11. Serrations on edges of leaves of E; Qyigm, Limtigqsa.andhgs_te_ssi§.-----..--.53 12. Leaf veination of 2‘ ayium and 2; frutiggga. . . . 55 vii Figure Page 13. 14. 15. Swollen glands on leaves and petioles of Lw.£igstasus.and£ifruti29sa- - - . - . 55 Pits ofhaxium.£ifmti§9§_e. andhgerasus- - 56 A typical leaf from each open-pollinated sour cherry family. . . . . . . . . . . . . . . . . . 61 viii INTRODUCTION Sour cherry (Egunug ggzagus L.) has been cultivated in its native habitats of Europe and the Soviet Union for many centuries. In these areas, sour cherry trees are still planted along rural roadways and in home gardens; although, large orchards now account for most of the sour cherry production. The Soviet Union is the world leader in sour cherry production, followed by the United States, West Germany, Yugoslavia, and Hungary. In the U.S., sour cherries, which have been grown since colonial times, may have been introduced by French settlers. It is only in this century that large commer- cial plantings have been made, which is attributed to the development of the canning and freezing industries, as well as mechanical harvesters. In the U.S., fresh market demand for sour cherries is very limited, although the fresh fruit are popular in Europe. The primary produc- tion sites in the U.S. are along the shores of the Great Lakes in Michigan, New York, and Wisconsin, where spring temperatures are moderated by the large bodies of water. Nearly the entire U.S. acreage is planted to a sin- gle cultivar, Montmorency, that originated in France some 400 years ago (Hedrick, 1915). Although 'Montmorency' is a profitable cultivar for growers, it is not without its shortcomings. These deficiencies include a low percentage of fruit set, susceptibility of the flower buds to spring frosts, muCh non-bearing wood, and susceptibility to several diseases. Additionally, this monoculture is vulnerable to new strains of disease organisms. New cultivars available to growers could potentially alleviate many of the problems growers encounter with 'Montmorency', thereby increasing grower profits. Other advantages offered by new cultivars would be an ability to extend both the harvest season and the range of environments under which the trees could be profitably grown. To date, breeding efforts in the U.S. have produced just a few new commercial cultivars, such as Meteor and North Star, which are of primary interest to backyard gardeners. The recently initiated sour cherry breeding program at Michigan State University has cultivar development as the ultimate goal. The initial objectives of this program have been to acquire and characterize a diversity of germplasm from eastern Europe and the Soviet Union, where well established breeding programs have produced several valuable cultivars. Because a lengthy quarantine period is required for clonal material brought into the U.S., the sour cherry germplasm collection at Michigan State University consists primarily of hybrid and open-pollinated (o.p.) seedlings. An understanding of morphological variation in sour cherry is critical to cultivar development, future germ- plasm collection, and eventual setting of priorities for germplasm maintenance. The purpose of the research reported herein was to employ techniques of multivariate analysis to characterize relationships in morphological variability in the sour cherry germplasm collection at Michigan State University. LITERATURE REVIEW Geneaology Sour cherry (Exgnus cerasus L.) has 32 chromosomes (2n=4x=32). Working independently, Kobel (1927), Darlington (1927, 1928), and Okabe (1928) concluded that the species is most likely an allotetraploid, with sweet cherry (Ezungg ayinm L.), (2n=2x=16) as one of the progen- itor species. Kobel (1927) suggested ground cherry (B; firntiggga Pallas), (2n=4x=32) or bush cherry (2; W Schneid.) = (P... mm: Bungle.) (Bailey. et al., 1976), as the most likely candidates for the other progenitor species. Darlington (1928) speculated that 2‘ geragug may have resulted from hybridization between 2; ayigm and 2; firutiggsa in the Caucasian region. Since 1936, more detailed cytological studies of meiosis in sour cherry and related hybrids have been conducted (Prywer, 1936; Hruby, 1939, 1950, 1962; Raptopoulos, 1941; Blasse, 1957; Barg, 1958). Only Raptopoulos (1941) Contends that sour cherry is an auto- tetraploid, which he believes may have arisen through spontaneous chromosome doubling of a diploid ancestor of sweet cherry. Hruby (1939, 1950, 1962) performed the most extensive cytological investigations by examining numerous pollen mother cells of various specimens of sour cherry, both triploid and tetraploid Duke cherry (sour cherry x sweet cherry, or vice versa), and backcrosses of tetraploid Duke cherry with both sweet cherry and sour cherry. For sour cherry, Hruby found that the mean numbers of univalents, bivalents, trivalents, and quadrivalents were 1.33, 14.75, 0.13, and 0.19 respectively, and for tetraploid Duke cherry, the respective means were 0.27, 3.77, 0.07, and 5.99. Hruby (1950, 1962) reached a similar conclusion regarding the origin of sour cherry as did Kobel (1927) and Prywer (1936) in their own investigations; i.e., that sour cherry is most likely an amphidiploid resulting from hybridization between two related diploid species, fol- lowed by spontaneous chromosome doubling. However, Hruby contends that neither sweet cherry nor ground cherry in their present forms were the progenitor species of sour cherry. Rather, Hruby hypothesized that sweet cherry arose through hybridization between two ancient diploid species with similar genomes. Sour cherry, Hruby sug- gests, may have arisen through hybridization between one of the progenitor species of sweet cherry and a third ancient diploid species (possibly an ancestor of ground cherry), followed by spontaneous chromosome doubling. Taking a different approach in investigating the origin of sour cherry, Oldén and Nybom (1968) "resynthe- sized" sour cherry by hybridizing ground cherry with autotetraploid wild sweet cherry. Morphological comparisons were made between naturally occurring sour cherry, diploid and autotetraploid sweet cherry, and the hybrids. Chemotaxonomic analyses of various phenolic, flavonoid, and anthocyanin compounds contained in the leaves and fruits were performed by means of thin-layer chromatography. The "biochemical distances" between the various species and interspecific hybrids were then calculated. The authors established that the tetraploid hybrids (ground cherry x autotetraploid sweet cherry) and naturally occurring sour cherry are intermediate both morphologically and chemotaxonomically to sweet cherry and ground cherry. These data support the theory that sweet cherry and ground cherry are the progenitors of sour cherry. Sour cherry is believed to have arisen in the Near East center of origin, which includes Asia Minor, Trans- caucasia, Iran, and the highlands of Turkmenistan (Vavilov, 1951), and perhaps as far west as Switzerland and the Adriatic Sea (Hedrick, 1915). In these regions the ranges of the ancestral forms of sweet cherry and ground cherry are thought to have overlapped. Cultivated forms of sour cherry were spread throughout the Roman Empire, extending the western range to England. Sour cherry grows wild in a diversity of habitats in Scandanavia, across Europe, and into the western Soviet Union. The range is primarily limited by low winter temperatures in northern latitudes, and by summer heat in southern regions. A great deal of genetic variation is found in eastern Europe and the western regions of the Soviet Union. There, a number of unique landraces have arisen through both natural selection and the regional preferences of peasants, who for several centuries have grown seeds or clones propagated from the best wild germ- plasm in their localities. Breeders in eastern Europe have gathered many of the best local cultivars from the various landraces, resulting in a diverse collection of elite germplasm. Most of the work regarding genetic variation in sour cherry has focused on eStablished cultivars, rather than on wild germplasm. Nevertheless, these cultivars exhibit a wide range of genetic diversity for such traits as spring floral bud development (Iezzoni and Hamilton, 1985), growth habit (Stancevic, Janda, and Gavrilovic, 1976), fertility (Redalen, 1984), disease resistance (Enikeev, 1975), cold-hardiness (Kolesnikova, 1975), drought resistance (Khalin, 1977), and ripening date (Gozob, Bodi, and Ivan, 1978). Additionally, Hedrick (1915), Michurin (1949), and others have made qualitative descriptions of morphological traits of various cultivars. French (1943) described and illustrated many taxonomic traits which can aid in the field identification of various sweet cherry and sour cherry cultivars. 8 Yushev (1975, 1977) focused on the morphological traits of the fruits and leaves of a wide range of cultivars. He examined 119 sour cherry and Duke cherry cultivars in the Soviet Union, after initially dividing the cultivars into two groups: eastern and western European. The eastern European cultivars were subdivided into northern, central, and southern zones of origin. Compared to the fruits of the eastern European cultivars, the fruits of the western cultivars generally had lighter colored juice and larger pits. 0f the western European cultivars, 71.4% had long (>50 mm) leaves. Obovate form, large glandules, coarse serrations, and pubescence were typical of the leaves of the western group. The eastern European cultivars, the majority (56.5%) of which had medium sized (30 to 50 mm), typically ovate leaves, exhibited a greater diversity in leaf morphology than the western European group. Considering the traits examined, Yushev concluded that the eastern European cultivars from the southern zone more closely resembled sweet cherry and the western European cultivars than did those eastern European cultivars from the central and northern zones. Yushev suggests that the resemblence of the leaves and fruit of eastern and western European cultivars to those of ground cherry and sweet cherry, respectively, may indicate the relative importance of these two presumed progenitor species in the origins of the eastern and western groups. WWW Although both principal component and cluster analy- sis are especially useful tools of research in social sciences, these methodologies are also applicable to botanical and plant breeding research. Several books regarding applications of multivariate analysis to botanical research have been published (Blackith and Reyment, 1971: Sneath and Sokal, 1973; Orlaci, 1978). Additionally, Crovello (1970) reviewed numerous publi- cations concerning the analysis of character variation in systematics and ecology. Brief descriptions of the techniques of principal component (PC) and cluster analysis are as follows. Multivariate observations consisting of sets of quanti- tative measurements of a number (n) of traits can be represented by the positions they occupy in n-dimensional space (hyperspace). Such a scatter diagram is composed of individual orthogonal axes for each trait on which the standardized values of the traits for each observation are plotted. The relative magnitudes of the Euclidean dis- tances between the points in hyperspace will indicate the similarity between corresponding observations. If some of the traits are linearly correlated (and assuming they are normally distributed), then the cluster of points in hyperspace will resemble an n-dimensional ellipsoidal cloud. Through PC analysis, the major axis (PC1) and subsequent orthogonal axes (PC2, PC3, ..., PCn) of this 10 ellipsoid are found. The first PC (PC1) will account for the maximum variance among all character values that can be attributed to a single axis, i.e., it represents the major axis of the ellipsoid. Each succeeding PC will account for a progressively smaller percentage of the remaining variance.. Each PC is defined by a linear combination of the original character scores. These combinations are the eigenvectors of the PCs._ The percentage of the total variance accounted for by each PC is obtained from the eigenvalues. A scatter diagram of the PC scores of the observations on all of the PC axes will retain the same relative distances between observa- tions as the original (untransformed) plot. However, the first two or three PCs often account for a major portion of the variance for most traits. Thus, PC analysis simplifies the original n-dimensional scatter plot by enabling the observations to be plotted on a reduced number of orthogonal axes while minimizing the loss of information. A scatter diagram of the PC scores of the original observations on these few axes provides a visually discernible indication of the similarities among observations (Adams, 1977). Cluster analysis is sometimes used in conjunction with principal component analysis to provide additional insight into the relationships among observations. Through this technique, a group of observations is parti- tioned into homogeneous clusters, based on a measure of 11 similarity between each observation or group of observa- tions and each other observation or group. The resulting classification is often represented as a dendrogram, that depicts the similarity among observations in a hierarchi- cal fashion. In contrast to PC analysis, cluster analysis does not control all types of correlations between traits (Small, 1979). The method of PC analysis has been modified to calculate "genetic distance", which is a measure of the geometrical (Euclidean) distance between genotypes represented as points in PC space (Adams and Wiersma, 1978). Adams (1977) applied this method to the study of cultivars of dry bean (Engfigglgs ynlggzig L.), and found that the "genetic distances" between cultivars, based upon chemical and agronomic traits, were highly inversely correlated to estimates of genetic relationships based upon breeding pedigrees. Both PC and cluster analysis have been used to relate character variation within a species to area of origin (Morishima, 1969; Rhodes, 1971; Hussaini, Goodman, and Timothy, 1977; Isleib and Wynne, 1983). Martin (1984) performed a PC analysis of morphological and phenological traits of dry bean (Ehasgglgs yglgggis). He examined the population structure and genetic diversity among 25 inbred lines grown from seeds collected at each of 15 sites in northern Malawi. A combined analysis of the data from the various sites revealed a north-south clinal pattern, which 12 Martin hypothesized may be a result of environmental adaptation or agricultural practices. Within sites (each with its own landrace), PC analysis provided evidence that. genetic variability is being maintained as a result of low levels of natural outcrossing between lines of this nor- mally inbreeding species. In another study, Murphy, Cox, and Rodgers (1986) used the pairwise coefficients of parentage between 110 red winter wheat (Tritigum aggtiyum L.) cultivars as input in a cluster analysis. The cultivars were found to cluster by class (soft vs hard), and by the geographical origin of the predominant parents within classes. Carter, Cech, and-DeHayes (1983) performed a cluster analysis on leaf traits of black cherry (£33335 gergtina Ehrh. subsp. gergtina) trees, that are grown for lumber. These trees, that were raised from seed collected throughout the eastern United States, were examined to determine whether patterns of variation in leaf mor- phology could be interpreted with respect to geographic origin. The primary split of the dendrogram separated trees of southern origin from those from northern and central regions. The authors suggest that gene flow from subspecies hirsute may account for the morphological differences in the southern specimens. In addition to uncovering underlying patterns of genetic diversity within a species, PC and cluster 13 analyses have been used to study species overlap to help explain evolutionary questions (Heiser, Soria, and Burton, 1965: Prance, Rogers, and White, 1969; Bemis, Rhodes, Whitaker, and Carmer, 1970: Small, Jui, and Lefkovitch, 1976). For example, Jensen and Eshbaugh (1976) examined the phenetic relationships between individual oak trees (Qggrgug) within different populations by means of PC and cluster analysis. The authors concluded that both forms of analysis are useful in identifying specimens of hybrid origin and their putative parental species, particularly in populations with narrow areal distributions and low taxonomic diversity. Yet another use of multivariate analysis has been to relate ecotypes and species habitats to specific environ- mental variables (Nevo, Zohary, Brown, and Haber, 1979). Jensen and Hancock (1982) evaluated three species of strawberry (Ezagazia) from several populations collected from a diversity of environments. PC and cluster analyses were used to detect patterns among individual plants, while discriminant analysis was used to examine relation- ships among populations and communities. Discriminant analysis provided a highly accurate differentiation of populations at the species level. Within each species, discriminant analysis indicated that combinations of morphological traits have evolved which are associated with the various community environments. MATERIALS AND METHODS ElQDL_M§§§Ii§l Sixteen cultivars, planted in a completely random- ized pattern at the Clarksville Horticultural Experiment Station, Clarksville, Mich., were evaluated (Table 1). The trees, propagated on mahaleb rootstock (2; mahalgh L.) and trained to a modified central leader system, were nine years old in 1985. Pollen was collected in Spring 1983 from the fol- lowing locations in eastern Europe: Fruit Research Institute, Cacak, Yugoslavia; Fruit Growing Research Institute, Plovdiv, Bulgaria: Research Institute for Pomology, Pitesti, Romania; Enterprise in Extension in Fruit Growing and Ornamentals, Budapest, Hungary; and Research Institute of Pomology, Skierniewice, Poland. The pollen was brought back to Michigan and used in crosses with the sour cherry cultivars English Morello, Rheinische Schattenmorelle, Wolynska, and Montmorency, generating four half-sib families (Tables 2, 3, 4, and 5). Open- pollinated (o.p.) seeds were collected in Hungary and Romania in 1984 (Table 6). The resulting seedlings were planted in a completely randomized pattern, also at the Clarksville Station, and were two years old when evaluated. 14 15 Table 1. Number of clones evaluated, with names and abbreviations of 16 sour cherry cultivars. Number clones Cultivar Abbreviation evaluated Bartozek Bt 3 Coronation Cn 2 4 English EM 3 Morello Fruchtbare von FM 2 Michurin George Glass SC 1 Griotte du Pays GP 1 Montearly Me 4 Meteor Mr 3 Montmorency Mt 4 Nefris . Nf 1 North Star NS 2 0stheim Os 4 Suda Hardy SH 2 Ukrainische US 2 Griotte Vladimirskaya V1 2 Wolynska W1 4 16 Table 2. Number of progenies evaluated in the 'English Morello' half-sib family, with names and abbreviations of the paternal parents. Number Paternal progenies parent Abbreviation evaluated Erdi Botermo EB 35 English EM 28 Morello Galaxy Gl 11 M 71 H1 8 M 172 H2 7 Hungarian Meteor HM 71 Karessova Kr 15 Meteor Korai MK 6 Meteor Mr 43 Nefris Nf 5 North Star NS 26 Oblacinska 0b 33 H 18/21 R1 5 Rexelle Rx 8 Sumadinka Su 49 17 Table 3. Number of progenies evaluated in the 'Rheinische Schattenmorelle' half-sib family, with names and abbreviations of the paternal parents. Number Paternal progenies parent Abbreviation evaluated Crisana 1/8 Cr 18 Erdi Botermd EB 32 M 112 H3 56 Mocanesti 16 Mo 16 Sumadinka Su 7 Table 4. Number of progenies evaluated in the 'Wolynska' half-sib family, with names and abbreviations of the paternal parents. Number Paternal progenies parent Abbreviation evaluated M 172 H2 13 Kelleris 16 K1 13 Oblacinska 0b 16 Sumadinka Su 46 Umbra Um 6 18 Table 5. Number of progenies evaluated in the 'Montmorency' half-sib family, with names and abbreviations of the paternal parents. Number Paternal progenies parent Abbreviation evaluated Amnestic Visin AV 8 M 63 H4 18 Meteor Korai MK 15 Nefris Nf 9 H 18/21 R1 22 H 17/39 R2 7 Tschatschakov TR 6 Rubin 19 Table 6. Number of progenies evaluated in the open-pollinated families, with names and abbreviations of the maternal parents. Number Maternal progenies parent Abbreviation evaluated Csengodi Csokras CC 23 Cigany Meggy CM 30 DO76 D0 10 Dobraya Db 15 Erdi Jubileum EJ 17 Kantorjanosi Kn 8 Korai Pipacs KP 25 Meggy (M 152) Lyubskaya Lb 30 Montmorency Mt 30 Nefris Nf 30 Pitic de Iasi PI 23 Pandy 114 Pn 26 Rheinische RS 5 Schattenmorelle Stark Montmorency SM 30 Wolynska W1 30 20 Table 7 lists the known pedigrees and putative origins of the cultivars and of the parents of the seedlings that were examined in this study. §D§£§££§I§_M£§§BI§Q Representative_samples of flowers, fruits, and leaves were collected from the nine year old cultivars for evalu- ation and analysis in 1985. Because of their juvenile state, only leaf samples were collected from the seed- lings. Quantitative measurements were made of various traits of the collected samples to enable numerical analysis of the data. The average value for each trait (averaged over both samples and replicates) is termed the "family (or culti- var) mean". The term "half-sib family" refers to all full-sib families with a common (maternal) parent. The terms "character" and "trait" are used interchangeably. Examples of traits are leaf length, and vein angle. A "character value" refers to an actual quantitative meas- urement, or an average of such measurements. Examples of character values are a leaf length of 80 millimeters, and a vein angle with a family mean of 59 degrees. A "char- acter state" indicates a qualitative distinction in character values. Examples of character states are long (vs short) leaves, and wide (vs narrow) vein angles. In 1985, the cultivars and the 'English Morello', 'Rheinische Schattenmorelle', and 'Wolynska' half-sib 21 Table 7. Pedigrees of cultivars and of parents of seedlings evaluated in the sour cherry germplasm collection. Cultivar Pedigree Garments References Amnestic Visin unknown Rananian cultivar 7 Bartozek mikmwn Cigény Meggy ----- Hungarian landrace 7 , 14 Coronation o.p. seedling of Canadian cultivar. 3, 8 Shubianka (sic) Shubinka is an old Russian cultivar Crisana 1/8 —---- Rananian clonal 2, 7, 12 selectim of the Crisana landrace Csengodi (Sokras \mkmwn Hungarian cultivar 7 D076 ---- Hungarian clonal 7 selection of the Pandy landraoe (see Pandy) Dobraya Vladimirskaya Russian cultivar 8 x Lyubskaya English Morello unknown an old cultivar, 6 presmnably German Erdi Botermo Pandy 38 x Nagy Angol Hungarian cultivar 1, 13, 14 Erdi Jubileum Pandy 38 x Eugenia Hungarian cultivar. 1, 2, 13 Eugenia is presumably a Duke Fruchtbare von uncertain presumbly Russian, 2, 10 Michurin probably the same as Plodorodnaya Michurina (see Pitic de Iasi) Galaxy (HID 405) Imknom an irradiated clone 7 ( see Mcmtmorency) of minnorercy George Glass unknown presumably fran mrthern 6 Gernany,possiblya mkexsmrcherry 22 Table 7 (corrt'd.) . antivar Pedigree Garments References Griotte du Pays mikncwn H 17/39 Vladimirskaya Rananian hybrid. 2, 4, x Polevka Polevka is an o.p. 10, 11 progeny of Ideal. Ideal is ground diarry (Stepnaya Dikaya) x E. W. H 18/21 English Tinpurii Rananian hybrid. 4, 12 x Visin Tufa English Tinpn'ii is presumbly a [lake Hungarian mknown Hungarian cultivar 7 Meteor KAntorjénosi Hungarian clanl 7 selection of the Pandy landrace (see Pandy) Kamsova clonal selectim of the 7 Pandy landrace, pollen obtained frcm mlgaria Kelleris 16 (Ostheim x Primate Danish cultivar. 3, 6,‘ 12 (Morellen- der Mark) o.p. Frfil'mte der Mark feuer) (paternal parent is a sweet cherry. is possibly Reine Hortense is a Reine HorterBe) Duke. (see Ostheim) Korai Pipacs Pandy x Csaszar Htmgarian cultivar. 1 Meggy (M 152) Lyubslaya unknown old Russian cultivar 8 M 63 Pardy x Nagy Gobet Hungarian hybrid. 2, 7 Nagy Gobet is also called Gros Gobet. M 71 unkmwn Hungarian 7 M 112 mflmom Hungarian 7 M 172 urflcrmn Hungarian 7 23 Table 7 (oorrt'd.) . oJltivar Pedigree (laments References Meteor Montmorency x a Russia USA cultivar 3 seedling tracing back ' two or more generations to Vladimirskaya and Shubianka (sic) Meteor Korai Pandy 29 x Nagy Angol mn'xgarian cultivar 1, 13 Mocanesti 16 —--—-- Runnian clonal 2, 7, 12 selection of the Mocanesti landrace Montmorency unknown old Frerdi cultivar 6 (possibly a pm of Cerise Hative or Cerise Gamma) Montearly unknown USA cultivar 3 Nefris umcnown preambly Polish 7, 12 , 14 North Star English Morello USA cultivar. Serbian 3 x Serbian Pie No.1 Pie No.1 is fran seed obtained in Yugoslavia Oblacinska --——--- Carpathian landraoe, 7, 12, 14 mostly in Yugoslth 0stheim mknown old Spanish wltivar 6, 8, 10 Pandy 114 ---- Htmgarian clonal 2, 7, 12 selection of the Pandy lamirace. Pandy is the Hngarian name for Crisana Pitic de Iasi o.p. seedling Moldavian cultivar. 2, 10, of Plodorodnaya "Plodorodnaya Michurina 11 , 12 Michurina is ground doerry x sour cheny (Stepnaya Sanarskaya x Michurina Karlikovaya) Rexelle unknown Danish mltivar 14 24 Table 7 (cont'd.) . Cultivar Pedigree Garments References1 Hieinisdae mflcmwn an old cultivar, 8 , 9 , Schattenmorelle presumably Germn or 12 , 14 Dutch, sanetimes equated to English Morello, Lyubsky. or WY?! Stark miknown a USA clonal selection 6 Montmorency (see Wency) of Montmorency Suda Hardy urflcmwn USA cultivar 6 (possibly a progeny ‘ of English Morello) Smuadixflca mternal parent Yugoslavian cultivar. 7 is Fanal Fanal (syn. Heimam's Conserve) is very similar to Nefris Tschatschakov 'Htmgarian' x (syn. Ytagoslavian 14 Rubin Schattemnorelle Cadak) , pollen dutained from Bulgaria Ukrainisdie unknown presumably Russian 15 Griotte Unbra unknown Vladimirskaya ---—--- old Russian landrace 6 , 8 Wolyrska mflmn Polish cultivar 5 , 7 JNLmeriqal code for references: 1. Apostol, J. (pers. cammm. 8. Kolesnikova, 1975 to A. Iezzoni) 9. Kramer, 1985 2. Bordeianu, et al., 1965 10. Michurin, 1949 3. Brooks and 01m, 1972 11. Michurin, 1955 4. Oociu and Gozob, 1985 12. Parnia, et al., 1985 5. Dzieciol, et al., 1983 13. Scortidfini, 1985 6. Hedrick, 1915 14. Vasilov, et al., 1982 7. Iezzoni, A. (pers. oamun.) 15. Yushev, 1975 25 families were evaluated. In 1986, the 'Montmorency' half- sib family and the o.p. families were evaluated. Seven- teen seedlings evaluated in 1985 were randomly selected for re-evaluation in 1986. An analysis of variance indi- cated significant variation between years for most traits, so data between years were not combined. Thirteen flower and fruit characters and seven leaf characters were measured for the 16 cultivars (Table 8). The seedlings, which had not yet flowered, were only evaluated for vegetative characters (Table 8). Samples were collected row by row to randomize the error intro- duced by sampling over time. Flower and fruit traits of the cultivars were eval- uated as follows. Ten mature fruit were randomly collect- ed from each tree. Five of these cherries (which had their pedicels removed) were oven dried, and weighed. The remaining five fruit were measured for the following traits: pedicel length, measured from the "skirt" to the abcission zone; fruit and pit length and width, measured at their largest dimensions; pit weight, measured after oven drying; and flesh color, which was visually rated on a qualitative scale of 0 to 9, with 0=c1ear and 9=dark red. Fruit dry weight without pits was calculated by subtract- ing the mean dry weight of the five pit samples from the mean dry weight of the fruits. The length:width ratios of both fruits and pits were calculated. The pit:fruit dry 26 Table 8. Character codes and units for characters and character ratios employed in numerical analyses. Code Character Cultivars Seedlings w n ‘ a e F1 Stigma length (mm) x F2 Pedicel length (mm) x F3 Fruit length (mm) x F4 Fruit width (mm) x F5 Fruit length/width x F6 Fruit dry weight w/o pit (g) x F7 Fruit flesh color x (0=light, to 9=dark red) F8 Pit length (mm) x F9 Pit width (mm) x F10 Pit length/width x F11 Pit dry weight (g) x F12 Pit/fruit length x F13 Pit/fruit dry weight x Vegetative Characters V1 Internode length (mm) x V2 Petiole length (mm) x x V3 Petiole width (mm) x V4 Petiole width/length x V5 Petiole glands x V6 Leaf length (mm) x x V7 Leaf width (mm) x x V8 Leaf thickness (mm) x V9 Leaf width/length x x V10 Petiole/leaf length x x V11 Swollen leaf glands x V12 Vein angle (deg.) x x V13 Serrations per centimeter x x V14 Pubescence (0=max. of three x trichomes, to 4=many trichomes) 27 weight ratios were calculated using the means of the dry pit weights and dry fruit weights (with pit weight sub- tracted out). Both the pit:fruit length and weight ratios were also included in the analysis. Vegetative traits of the cultivars and seedlings were evaluated following terminal bud set in July. Internode length was measured in the mid-shoot portion of five ran- domly selected shoots of the current year's growth. Five random leaf samples per tree, also collected from the mid- shoot portion of the current year's growth, were evaluated for all other traits. Leaf samples were placed in plastic bags, packed in ice, and evaluated in the laboratory. Leaf blade length was measured from the apex to the point of attachment to the petiole, while the distance from this point to the abcission zone was recorded as the petiole length. Leaf blade and petiole widths were measured at their mid-lengths. Leaf blade thickness was measured with a micrometer in an area relatively free of secondary veins. Both the number of petiole glands and swollen glands on the basal leaf edge (near the point of petiole attachment) were counted with the aid of a dissecting microscope. Two types of swollen leaf glands are common. One type is usually green and often has a depression in the center, while the other type is typically smaller and darker, resembling those glands found at the tip of each serration. Although both types of gland were counted, 28 only the first type was used in the analysis since the second type had a very high variance, even between clones of the same cultivar. Vein angles were measured between the midvein and the secondary vein closest to the leaf blade mid-length, on a line near the point of intersec- tion of the two veins and tangent to the secondary vein (which is often curved). The number of serrations per centimeter on the leaf edge near the mid-length of the leaf blade was counted. Pubescence on the abaxial (lower) leaf surface between the secondary veins was subjectively rated (with the aid of a dissecting microscope) on a qualitative scale of 0 to 4, with 0=a maximum of three trichomes per leaf, and 4=very pubescent. The width: length ratios of both the leaves and petioles, as well as the petiole:leaf length ratio, were calculated. We Principal component analysis was performed using the PRINCOMP procedure of the SAS statistical package (SAS Institute, 1985a). Family means were used to create a correlation matrix from which standardized principal component scores were extracted. Scatter plots of the first three PCs were created with SAS/GRAPH (SAS Insti- tute, 1985b). To determine which of the first three PCs accounted for the greatest amount of variation for each trait, the eigenvectors (Tables 10, 13, and 15) of the three PCs were compared for each trait, and the trait 29 being considered was ascribed to the PC having the eigen- vector with the largest absolute value. Cluster analysis was performed using version 1C of the Clustan statistical package (Wishart, 1975). Sepa- rate analyses were performed on the cultivars, on each of the half-sib families, and on the set of o.p. families. After standardizing the data means, a dissimilarity matrix of distance coefficients was created using squared Euclid- ean distance as the dissimilarity criterion. A fusion hierarchy was then produced using 'Ward's mimimum variance method' to optimize the error sum of squares (Ward, 1963). Dendrograms were plotted with the Plink procedure of Clustan (Wishart, 1975). Analysis of variance followed a General Linear Models procedure capable of analyzing unbalanced designs (SAS Institute, 1985a). Pearson's correlation coefficients were calculated between each pair of traits for the cultivars and for each of the o.p. families. The means of all samples from all replicates (clones) were used to compute the cultivar correlations, while the sample means of each replicate (progeny) were used for the o.p. families. All correla- tions were tested for significance at the 95% level. Examples of the computer programs used in data analy- sis are presented in Appendix B. RESULTS A measure of the morphological similarities among cultivars or families can be inferred from the spatial proximity of the PC1, PC2, and PC3 values that character- ize each cultivar or family mean in PC1-PC2-PC3 space. The values of the PC coordinates were generated by the PRINCOMP procedure of the SAS statistical package. Such a mapping of the data is given in Figures 1, 3, and 7. A computer generated cluster analysis provides another means of showing the degree of morphological similarity among observations. Dendrograms illustrating such cluster analyses are given in Figures 2, 4, 5, 6, 8, and 9. Appendix A lists the average character values obtained for each cultivar, and for each full-sib and open-pollinated family. Tables A2 and A3 also list the ranges in charac- ter values (averaged over samples) among trees within each seedling family. We The first three PCs of the cultivar data account for 71% of the total variance among cultivar means; i.e., for 30%, 21%, and 20% of the variance, respectively (Table 9). 30 31 Table 9. Eigenvalues of the first seven PC axes from PC analysis of 16 sour cherry cultivars, with propor- tion of total variance accounted for by each axis. Principal Proportion Cumulative Component Eigenvalue of variance variance 1 5.940 0.297 0.297 2 4.267 0.213 0.510 3 3.948 0.197 0.708 4 2.295 0.115 0.822 5 1.236 0.062 0.884 6 0.691 0.035 0.919 7 0.551 0.028 0.946 Coronation (Cn), a cultivar with a Russian maternal parent, is an outlier (Figure 1). The other Russian cultivars, Fruchtbare von Michurin (FM), Ukrainische Griotte (UG), and Vladimirskaya (Vl), are morphologically diverse; i.e., situated at or near the extremes of both PC1 and PC2. 'George Glass' (GG), which may have a sweet cherry grandparent, groups with 'Griotte du Pays' (GP) and 'Montearly' (Me), both of unknown origin. 'Montearly's' distance from 'Montmorency' (Mt) was not unexpected, since they are not believed to be clonal variants of the same cultivar. 'North Star' (NS) groups with its maternal parent, 'English Morello', (EM) and with 'Suda Hardy' (SH), which Hedrick (1915) believed may also be a progeny of 'English Morello'. 'Meteor' (Mr), a hybrid between 'Montmorency' (Mt) and a Russian seedling, is situated with its maternal parent on both PC2 and PC3. The two Polish cultivars Wolynska (W1) and Nefris (Nf) are 32 >0HQQ< ima G's 'I. I ‘0 IOQI . 8... . 00% 005 33 similar, as are 'Montmorency' (Mt) and 'Bartozek' (Bt). Proceeding from negative to positive values of PC1, the cultivar means generally show an increase in the lengths and length:width ratios of both fruits and pits, as well as in fruit dry weight, while leaf length, width, and the widthzlength ratio tend to decreasel. From negative to positive values of PC2, the trend is toward increasing stigma and petiole lengths, fruit width, and the petiole:leaf length ratio, while flesh color and the number of serrations per centimeter generally decrease. From negative to positive values of PC3, pit width and weight, pedicel length, and the pit:fruit length and weight ratios tend to increase, while vein angle tends to decrease. The cluster analysis of the 16 cultivars illus- trates relationships similar to those indicated by the PC analysis (Figure 2). However, the cluster analysis does suggest that 'Fruchtbare von Michurin' (FM) is more similar to the other Russian cultivars than the PC analysis indicates. Also, 'Meteor' (Mr) clusters with 'Montmorency' (Mt), its maternal parent. There are numerous statistically significant correl- ations between the traits of the 16 cultivars (Table 11). 1Summarized from the eigenvectors of the first three PCs (Table 10). 34 6.263 r 5.622 ‘- 4.981 -* 4.340 + 3.699 r 3.058 ~~ 2.417 * r 1.776 T 1.135 *- 0.494 r __ m m 3! Mt Mr SH EM NS GP 66 M0 0: WI NI FM UG VI Cn Figure 2. Dendrogram representing cluster analysis of 16 sour cherry cultivars. Abbreviations as in Table 1. 35 Table 10. Eigenvectors of the first seven PC axes from PC analysis of 16 sour cherry cultivars. Char- Eigenvectors acter Code PC1 PC2 PC3 PC4 PC5 PC6 PC7 F1 -0.21 0.31 0.17 -0.10 -0.11 0.23 0.42 F2 0.14 -0.14 0.23 -0.25 0.46 -0.46 -0.02 F3 0.36 0.20 -0.01 0.15 0.03 0.14 -0.03 F4 0.09 0.43 -0.02 0.12 -0.11 0.19 -0.06 F5 0.39 0.05 0.00 0.11 0.10 0.05 0.01 F6 0.26 0.20 0.13 0.25 -0.26 -0.35 -0.04 F7 0.10 -0.28 0.26 0.02 -0.27 0.16 0.54 F8 0.37 0.15 0.12 0.10 0.03 0.04 -0.02 F9 -0.01 0.21 0.42 0.03 -0.11 -0.18 0.15 F10 0.36 -0.02 -0.15 0.12 0.13 0.26 -0.07 F11 0.10 0.14 0.44 0.06 0.10 0.11 -0.05 F12 0.17 -0.21 0.33 0.03 0.15 0.01 -0.23 F13 -0.13 -0.08 0.34 -0.22 0.34 0.46 -0.06 V2 -0.15 0.38 -0.10 0.02 0.37 -0.03 0.15 V6 -0.27 0.11 0.26 0.27 0.11 -0.19 -0.02 V7 -0.27 0.02 0.19 0.41 0.07 -0.03 -0.14 V9 -0.22 -0.10 -0.00 0.45 0.04 0.30 -0.32 V10 -0.00 0.36 -0.22 -0.09 0.37 0.01 0.13 V12 -0.08 -0.16 -0.19 0.47 0.24 -0.21 0.38 V13 0.17 -0.27 -0.05 0.24 0.28 0.16 0.36 1 See Table 8 for a description of character codes. 36 Table 11. Pearson correlation coefficients between traits for 16 sour cherry cultivars. CharacterCode1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11 F12 F13 F1 |-.30|-.19|.44 |-.44 |-.06 |-.14|-.19 |.58*|-.56*| .34 |-.31| .34| F2 |-—-—| .06|-.34| .26 | .06 | .27| .26 |.22 | .10 | .42 |.57*| .43| F3 |--|--|.61*|.93**|.77**|-.03|.95**|.14 |.82**| .34 | .19|-.37| F4 |-—-|-—-| | .27 |.54* |-.46| .48 |.37 | .20 | .29 |-.39|-.28| F5 |--|--|--|---|.68**| .19|.93**|.01 |.9o**| .29 | .41|-.31| F6 |--|--—|-—-|---| | .13|.79**|.46 | .42 |.51* | .20|-.44| F7 |-—-—|-—-|--|---|- —-|- -| .17 |.21 | .07 | .33 |.60*| .28| F8 |--|——-—|--|---|--—|--|-—-|.33 |.74**|.51* | .43|-.20| F9 |-'-|""|""l""'|“"'|""l""-l-'-l'-36 I-31**| .29| ~38| F10 l""|""""'l"‘""|""""'l"""'|""'|"""l""'l"""l"’-02 | ~26l'o38l F11 I'ml—‘lmlwlnlmlml-“lwl—“l~51*|-54*| F12 l-'“|"'-l""|""'l""'l""l""'l‘-'-l-'-'|""‘l'-'-| .42| Table 11 (cont'd.). CharacterOode V2 V6 V7 V9 V10 V12 V13 | .60* | .56* | .36 |-.02 | .34 |-.32|-.60* |-.24 |-.10 |-.25 |-.43 |-.l6 |-.22| .24 | .04 |-.4o |-.42 |-.38 | .30 |-.15| .22 | .54* | .10 |-.02 |-.15 | .55* |-.28|-.27 |—.21 |-.53* |-.5o*|-.41 | .11 |-.O6| .40 |-.06 |-.05 |-.08 |-.22 | .04 |-.12| .01 |-.7o**|-.11 |-.03 |-.03 |-.7o**| .02| .31 |-.12 |-.32 |-.38 |-.43 | .12 |-.24| .23 | .14 | .56* | .36 |-.11 |-.08 |—.4o|-.28 |-.23 |-.63**|-.55*|-.30 | .10 | .09| .49 PC | .00 .38 | .26 |-.06 |-.13 |-.4l|-.06 |-.55* .02 .03 |-.08 |-.54* |-.10| .29 |-.02 l | l | .36 | .27 | .09 |-.2o |-.35|-.07 | .37 | I I I ggssasggaaoamaaeama | .22 | .03 | .89**| .06|-.45 | |.92**| .49 |-.09 | .20|-.26 |--- | |.78**|-.20 | .41|-.12 |-—-—- ---|-—-—-|-—--|-.21 |.56*| .11 I |"'""|"'"l""'l"""l‘-04|‘~33 l lmlwlmlmlul ~45 18ee Table 8 for a description of character codes. * r values significantly different fran zero at the 0.05 level. ** r values significantly different fran zero at the 0.01 level. 37 The correlations of most interest are those between vege- tative and fruit characters. For example, fruit flesh color is negatively correlated with petiole length (r= -0.70), and the pit length:width ratio is negatively correlated with leaf length (r=-0.63). W In a similar analysis of the 1985 seedling data, the first three PCs of the full-sib family means for the 'English Morello', 'Rheinische Schattenmorelle', and 'Wolynska' half-sib families account for 71% of the total variance; i.e., for 43%, 18%, and 10% of the variance, respectively (Table 12). The families with maternal Table 12. Eigenvalues of the first seven PC axes from PC analysis of the 'English Morello', 'Rheinische Schattenmorelle', and 'Wolynska' half-sib families, with proportion of total variance accounted for by each axis. Principal Proportion Cumulative Component Eigenvalue of variance variance 1 5.967 0.426 0.426 2 2.526 0.180 0.607 3 1.428 0.102 0.709 4 1.175 0.084 0.793 5 1.001 0.072 0.864 6 0.574 0.041 0.905 7 0.435 0.031 0.936 38 parent 'Rheinische Schattenmorelle' group together, with 'Rheinische Schattenmorelle' x Crisana 1/8 (Cr) as the most distant (Figure 3). Three of the families with maternal parent 'Wolynska' are in close proximity, although the families with paternal parents 'Umbra' (Um) and Oblacinska (0b) are dissimilar. Families with maternal parent 'English Morello' are morphologically diverse; i.e., located at the extremes of each of the first three PCs. The families of self-pollinated 'English Morello' (EM), 'North Star' (NS) backcrossed to 'English Morello', and 'Wolynska' x Oblacinska (0b) are proximate and separate from the other families. The 'English Morello' families with paternal parents 'Sumadinka' (Su) and 'Nefris' (Nf) are closely situated. The two families with paternal parent 'Erdi Botermd' (EB) are also closely situated to one another. Located near the center of the figure are the families with paternal parents Crisana 1/8 (Cr) (Crisana is the Romanian name for Pandy), 'Karessova' (Kr) (also a clonal selection of Pandy), and 'Meteor Korai' (MK) (a progeny of Pandy). Proceeding from negative to positive values of PC1, the family means generally increase in leaf and petiole lengths and widths, the number of petiole glands, and vein anglel. From negative to positive values of PC2, 1Summarized from the eigenvectors of the first three PCs (Table 13). 39 ounna .moeafiamu .n coucm ccumucm oumofiocfi e can .n .m modems as no macaucfi> newuudmn maxmcsdos. 6:6 ..oaaouoecmuuanom anomscsmsm. ..oaamuoz cosmocm. may you muxc om mousu umnwm on» :0 needs >HflEcu no mouoou on no mcofiufimom n on: we Qn.NI QM.P no.9! VN.N . @—.OI r On.p .cxe:>.03.D G @ ® 2 .0:o..oEco:ugom.¢.o m9 mmv 1.UN.N 901 .2350: £2.95. 0 “2:03.. .6503: 40 internode length and the petiole width:length ratio generally increase, while the petiole:leaf length ratio tends to decrease. Movement from negative to positive values of PC3 is characterized by an increase in the leaf width:length ratio and the amount of pubescence, while the number of serrations per centimeter and swollen glands on the basal leaf edge generally decrease. Table 13. Eigenvectors of the first seven PC axes from PC analysis of the 'English Morello', 'Rheinische Schattenmorelle', and 'Wolynska' half-sib families. Char- Eigenvectors acter Code PC1 PC2 PC3 PC4 PC5 PC6 PC7 V1 0.09 0.44 0.14 -0.33 -0.07 0.44 -0.11 V2 0.36 -0.24 0.22 -0.04 -0.04 0.05 -0.14 V3 0.38 0.12 0.07 -0.08 -0.16 -0.05 -0.24 V4 -0.10 0.56 -0.20 0.03 -0.09 -0.15 -0.1l V5 0.35 -0.09 -0.24 -0.02 0.12 -0.15 -0.12 V6 0.38 0.07 0.21 -0.07 0.07 -0.04 -0.30 V7 0.36 0.13 0.30 0.09 -0.05 -0.05 -0.1l V8 0.32 0.01 -0.33 -0.28 0.05 -0.03 0.40 V9 0.07 0.25 0.40 0.53 -0.38 -0.04 0.43 V10 0.16 -0.52 0.12 -0.02 -0.21 0.15 0.21 V11 0.28 0.08 -0.33 0.26 -0.02 -0.55 0.06 V12 0.28 0.15 -0.32 -0.10 -0.18 0.38 0.43 V13 0.12 -0.04 -0.33 0.65 0.22 0.53 -0.27 V14 0.12 0.14 0.30 0.04 0.82 -0.01 0.36 1 See Table 8 for a description of character codes. 41 In the cluster analysis of the 'English Morello' half-sib family (Figure 4), the clustering of the families with paternal parents 'Sumadinka' (Su), 'Karessova' (Kr), and Oblacinska (0b), and with paternal parents 'Nefris' (Nf), 'Rexelle' (Rx), and 'Galaxy' (G1) was unexpected, since the families within these two groups are not closely situated on the PC figure. Cluster analyses of the half-sib families with maternal parents 'Rheinische Schattenmorelle' (Figure 5) and 'Wolynska' (Figure 6) generally suggest that the phenotypic relationships among full-sib families are similar to those indicated by the PC analysis. However, the dendrogram of the 'Rheinische Schattenmorelle' half- sib family suggests that the family with Mocanesti 16 (M0) is more similar to the family with Crisana 1/8 (Cr) than to the family with 'Sumadinka' (Su). Additionally, the dendrogram of the 'Wolynska' half-sib family indicates a greater morphological similarity between the families with paternal parents 'Sumadinka' (Su) and 'Umbra' (Um) than is indicated by the PC analysis. 12§§_§eedling_enalx§is In a combined analysis of the full-sib families with maternal parent 'Montmorency' and of the 15 o.p. families, the first three PCs account for 71% of the total variance among the family means; i.e., for 37%, 21%, and 13% of the variance, respectively (Table 14). 42 .639 n .757 u .875 w .993 “ .111 " .229 ,u .347 w .465 " .583 " .701 r “[731 m FF? ["1 fl Mr HM MK H1 RI GI Rx Nf Su Ob Kr H2 EB EM NS Or—‘NUJAO'IUIO’JQCD Figure 4. Dendrogram representing cluster analysis of the 'English Morello' half-sib family. Abbreviations as in Table 2 indicate paternal parents. 43 2.675 1' 2.527 “r 2.378 -- 2.229 -~ 2.080 ~- 1.931 -- 1.782 ~- 1.633 -- 1.484 -- 1.335 1' 1- F_—_—1 50 EB H3 Mo Cr Figure 5. Dendrogram representing cluster analysis of the 'Rheinische Schattenmorelle' half-sib family. Abbrevia- tions as in Table 3 indicate paternal parents. 3.335 3- 3-100 -r 2.865 “- 2.829. -- 2.393 -r 2.157 ‘- 1.922 '- 1.688 ~- l.450 -- 1.215 -~ -_ F—"—7 Su Um Kl H2 Ob Figure 6. Dendrogram representing cluster analysis of the 'Wolynska' half-sib family. Abbreviations as in Table 4 indicate paternal parents. 44 Table 14. Eigenvalues of the first seven PC axes from PC analysis of the open-pollinated and 'Montmorency' half-sib families, with proportion of total variance accounted for by each axis. Principal Proportion Cumulative Component Eigenvalue of variance variance 1 5.239 0.374 0.374 2 2.897 0.207 0.581 3 1.766 0.126 0.707 4 1.169 0.083 0.791 5 0.804 0.057 0.848 6 0.749 0.054 0.902 7 0.507 0.036 0.938 The 'Montmorency' half-sib family groups together, although the family with paternal parent H 18/21 (R1) (a hybrid between a Duke and a sour cherry) is an outlier (Figure 7). The o.p. families with maternal parents 'Montmorency' (Mt) and 'Stark Montmorency' (SM) are in fairly close proximity to one another and to the o.p. family with maternal parent 'Meteor Korai' (MK). The three o.p. families with cold-hardy maternal parents 'Pitic de Iasi' (PI), 'Lyubskaya' (Lb), and 'Rheinische Schattenmorelle' (RS) are closely situated and separate from the central grouping. The three o.p. families with maternal parents 'Dobraya' (Db), 'Wolynska' (W1), and D076 (D0) form a compact group situated near the assem- blage of cold-hardy types. The o.p. 'Cigany Meggy' (CM) family is an outlier. The closely situated families of 'Montmorency' x H 18/21 (R1) and o.p. 'Csengodi Csokras' (CC) are also outliers, situated farthest from the .5 ounces .mosafiecm couccfiaaomncomo may no mucoucm accumucfi can ammo can >Hfiacm newsman: .>ocouosucoz. on» .mowafiaou .Socmuosucoz. on» no museums accuoucm oucoficcfi m can m nuance cw mo m:OHUMw>0unn< .mmwawacm couccflaaoms you mmxc om moan» pubs“ on» :0 mccme aafiacu mo mouoom om mo mCOwuwmom an.—: .01 8...? 1F 3.? m 3.6 ._ a... 4.. ~44 Gm ..1 s s s K. mO.¢I .. .ofi.9. «ca 5 . 4 «a... 4 «a o .«6.« on; non 30:03:29.0}. a. 2.02:. 35.362 be.c:_..od-codo O 46 assemblage of families with cold-hardy maternal parents. As in the PC figure of the 1985 seedling data (Figure 3), families related to Pandy are located near the center of the plot: Pandy 114 (Pm), D076 (00), and 'Kantorjanosi' (Kn) are clonal selections of the Pandy landrace, while M 63 (H4), 'Erdi Jubileum' (EJ), 'Meteor Korai' (MK), and 'Korai Pipacs Meggy' (KP) are progenies of Pandy. The character loadings of the first three PCs are generally similar to those of the 1985 seedling analysis. Proceeding from negative to positive values of PC1, the lengths and widths of the leaves and petioles, as well as the leaf width:length ratio and vein angle, generally increase, while the number of serrations per centimeter tends to decreasel. Proceeding from negative to positive values of PC2, leaf thickness, the petiole width:length ratio, and the number of swollen glands on the basal leaf edge generally increase, while the petiole:leaf length ratio tends to decrease. Proceeding from negative to positive values of PC3 is characterized by an increase in the number of petiole glands and a decrease in both internode length and pubescence. Cluster analyses of the 'Montmorency' half-sib family (Figure 8) and the o.p. families (Figure 9) revealed rela- tionships similar to the PC analysis. 1Summarized from the eigenvectors of the first three PCs (Table 15). 47 4.636 r 4.180 “ 3.724 ‘- 3.288 “ 2.812 " 2.356 r 1.900 r 1.444 r 0.988 r 0.532 r __ r‘”‘1 MK H4 AV R1 NI HZ TH Figure 8. Dendrogram representing cluster analysis of the 'Montmorency' half-sib family. Abbreviations as in Table 5 indicate paternal parents. .500 r .843 '- .085 ‘- .329 ‘— .572 ‘- .815 “ .058 “ .301 ‘7 .544 ‘7 -787 w Or—‘Nwwsmmms _ l— m S» KP cc w: 00 on as Lb Pl m Kn cu EJ Pn Figure 9. Dendrogram representing cluster analysis of the open-pollinated families. Abbreviations as in Table 6 indicate maternal parents. 48 Table 15. Eigenvectors of the first seven PC axes from PC analysis of the open-pollinated and 'Montmorency' half-sib families. Char- Eigenvectors acter Code PC1 PC2 PC3 PC4 PCS PC6 PC7 V1 0.14 0.15 -0.40 0.37 0.46 -0.52 0.06 V2 0.39 -0.22 -0.07 -0.04 0.16 0.06 0.15 V3 0.37 0.25 0.12 0.15 0.10 -0.13 0.08 V4 -0.17 0.49 0.14 0.15 -0.06 -0.10 -0.06 V5 0.13 -0.23 0.57 0.27 0.21 0.02 0.06 V6 0.37 0.16 -0.07 0.17 -0.05 0.23 -0.26 V7 0.40 0.17 -0.06 -0.06 -0.01 0.28 -0.17 V8 0.13 0.37 0.24 -0.16 -0.32 -0.23 0.68 V9 0.32 0.15 -0.01 -0.39 0.03 0.28 0.03 V10 0.20 -0.46 -0.02 -0.22 0.23 -0.11 0.36 V11 -0.16 0.33 -0.07 0.08 0.54 0.51 0.32 V12 0.22 -0.16 0.13 0.63 -0.33 0.16 0.10 V13 -0.32 -0.09 0.30 0.15 0.22 0.25 0.13 V14 -0.12 -0.12 -0.55 0.24 -0.31 0.28 0.38 1 See Table 8 for a description of character codes. 49 Table 16 lists the number of o.p. families having a significant correlation for each pair of traits, along with the sign (positive or negative) of the correlation. As with the cultivar data, many of the correlations were predictable. A few notable exceptions include the posi- tive correlations found in several families between petiole length and the number of petiole glands, between internode length and leaf width, and between petiole width and leaf thickness. In most cases, when a statistically significant correlation was found between a pair of traits in more than one family, the correlations had the same sign. However, in a few cases opposing signs were found. The o.p. family with 'Dobraya' shows a negative correla- tion between pubescence and leaf length (r=-0.61), while the o.p. family with 'Csengodi Csokras' shows a negative correlation between the number of petiole glands and both leaf length (r=-0.45), and leaf width (r=-0.52). Only positive correlations were found between these traits among the other o.p. families. 50 Table 16. Sign and timber for the 15 open-pollinated families in which there were significant Pearson correlation coefficients between traits. <3un2xxzm-cndez ‘V1 V2 V3 V4 ‘V5 ‘V6 V7 V8 V9 V10 ‘V11'V12 V13 V1 |--I--I--I--l--I--I--l--I--I--l---l--I--| V2 I+3 I-—-I-—-I--I--I-—I-—-I--I-—I-I—-I-I--I V3 |+2 |+11 I--I--l--I--I--I--I--I--I-—l--I--I V4 |+2-1| -14I+3 l--|--|--I--I-—l-—I—-I--l-I--l V5 I l+8 l+3 I -4I--I--I--l--I--l--I--I--I-l V6 |+3 |+13 |+14 | -2|+3—1|--|--—-|—-|—-|-—I--|--|—-| V7 |+8 |+10 [+14 |+1-3|+3-1|+14 |-—-|---|--|-—|--|—-|—-| V8 | |+1 |+11|+1-1|+3 |+4 |+4 |---|---|-—-|--|--|--| V9 l+3 |+1 |+2 |+1-1|+1 I I+6 I l—-I--l--I--I--I V10 |+1-2|+12 |+1 |-14|+6 |+1-1|+1-1|+1 |+2 |---|--|---|---| V11 |+1-1|+l-2|+2-l|+3-1|+1 |+1 |+2 | |+2-1| -2|--|--|--| V12 |+2 |+1 |+1 |+2 |+2-1|+3 |+3 | -1| -1| -2|+1-2|--|-—-| V13 |-2 | -1| -3|+1-1|+3 | -4| -2| -1| -1|+2| | |--| V14| |+3 |+4-1| -1| -1|+3-1|+2-1|+1-1|+1 |+1|+1 | |+2| gr values significantly different from zero at the 0.05 level. See Table 8 for a description of character codes. Legend: +2-1, for example, means two families had positive correlations and one family had a negative correlation. Blank spaces indicate that no significant correlations were found. DISCUSSION 13222119193! A major point of interest in this study has been to relate the character variation of leaves and fruit observed in the sour cherry germplasm collection to the character states which typify the putative progenitors; i.e., ground cherry and sweet cherry. Ground cherry and sweet cherry are morphologically distinct (Hedrick, 1915; Rehder, 1958; Oldén and Nybom, 1968; Kolesnikova, 1975; Bailey, et al., 1976). Ground cherry, considered the most winter hardy of the cherry species (Kolesnikova, 1975), reaches a height of about one meter, with a spreading form. The leaves (Figure 10) are generally short (20 to 50 mm), thick, glabrous, finely serrated (Figure 11), and have somewhat narrower vein angles than leaves of sweet cherry (Figure 12). The basal leaf edge typically has two to four swollen glands (Figure 13). The petioles are short (5 to 12 mm) and without glands. The fruits are usually small (about 10 mm across), with small pits (Figure 14), and 15- to 25-mm pedicels. In contrast, sweet cherry trees are tall (to 18 m), with a pyramidal form. The leaves (Figure 10) are generally long (60 to 150 mm), thin, variably pubescent beneath, coarsely serrated (Figure 11), with wider vein 51 52 Figure 10. Leaf samples of £1 gyigm, 2‘ geragus, and 2; frutigosa. Figure 11. Serrations on edges of leaves of E; ayium, P; frutiggsa, and 2‘ gerasug. Abbreviations as in Table 6 indicate maternal parents of open-pollinated 2; gezasus specimens, except Mc='Montmorency'. P awum Wmdso' 53 Pcerasus PIruIICOSa Montmorency IR~ 5874 \ Figure 10. P.fruticosa .avnum p L O m U .E .3 Figure 11. 54 Figure 12. Leaf veination of 2; gyium and 2* firutiggsg. Figure 13. Swollen glands on leaves and petioles of 2; avium, 2; cera s, and E; fruticgsa. Abbreviations as in Table 6 indicate maternal parents of open-pollinated £1 cerasgs specimens. 55 Pamum P.fruticosa ‘Windsor IR-587-1 Figure 12. Figure 13. 56 angles than leaves of ground cherry (Figure 12). The petioles are relatively long, and frequently have two or more swollen glands. Swollen glands are usually lacking on the basal leaf edge (Figure 13). The wild fruits are generally small, although cultivated fruits can be large (about 25 mm across), with larger pits than those of ground cherry (Figure 14), and 20— to 50-mm pedicels. U “ ng- 5y mm \ A 5" W ‘7 Q1 «I Figure 14. Pits of 2; avium, 2; fruticosa, and 2; cerasus. (2; avium: 1='Schmidt', 2='Napoleon'; 21 fruticosg: 1=IR 883-1, 2=IR 587-1, 3=IR 323-2; 2; cerasus: ='English Morello' x 'Hungarian Meteor', 2='Montmorency', 3='North Star', 4='Montmorency' o.p., 5='Rheinische Schattenmorelle' o.p.). Soviet investigators have divided cultivated sour cherry into two ecotypes based on morphological differ- ences and winter hardiness: western European and middle- 57 Russian (Kolesnikova, 1975). The western European group, in which Kolesnikova (1975) and Yushev (1975, 1977) include examples of Duke cherry (hybrids between sour cherry and sweet cherry), is characterized by lower winter hardiness than the middle-Russian group. The western European cultivars generally have larger leaves and fruit than the middle-Russian types, the fruit having better eating quality and nearly colorless juice. The middle- Russian group, comprised of eastern European cultivars, is adapted to harsh winter conditions under which only those individuals which have a high degree of winter hardiness can survive. Additionally, human selection pressure has probably contributed to the differences between the two groups (Kolesnikova, 1975). In southern and western Europe, clear- or pink-juiced cultivars are preferred, while in eastern and northern Europe and the Soviet Union, red-juiced selections are preferred. :1 ! V . !' For all of the morphological traits of the sour cherry trees that were examined, there is a gradation in the character values. These values generally encompass a wide range, intermediate to the character values that typify the present-day forms of the two presumed pro- genitor species. For instance, the range in the mean leaf length of the progenies in the largest full-sib seedling family (71 progenies) is 42 to 114 mm (Table A2). 58 These values are intermediate and approximate to the typical leaf lengths of ground cherry and sweet cherry, respectively. However, for certain specimens, character values were measured which may exceed the character value range demarcated by ground cherry and sweet cherry. For example, a sample mean of 20 leaf serrations per centi- meter was calculated for one of the 'English Morello' x M 71 progenies. However, a survey of the ground cherry specimens in our collection indicated a value near 10 serrations per centimeter may be more characteristic of the species. It is of particular interest that character states associated with sweet cherry and ground cherry generally fall at opposite ends of some of the PCs. Therefore, the values of these PCs may be interpreted as representing gradations between ground cherry- and sweet cherry-like morphology. For example, movement from negative to positive values of PC1 in Figure 7 tends to result in increasingly sweet cherry-like characteristics: i.e., longer, wider, more coarsely serrated leaves with longer petioles and wider vein angles. A similar gradation of ground cherry- vs sweet cherry-like traits occurs in each figure, with the progression toward increasingly sweet cherry-like traits toward negative for PC1 and positive for PC2 in Figure 1, toward positive for both PC1 and PC3 in Figure 3, and 59 toward positive for PC1 and negative for PC2 in Figure 7. The gradation in morphological resemblance to the two presumed progenitor species is most evident along PC2 in Figure 1, and along PC1 in Figure 7. In both cases, for all of the traits measured for which a distinction between ground cherry- and sweet cherry-like morphology was made, the direction of the progression along the PC axes toward increasingly ground cherry— or sweet cherry-like morphol— ogy is the same. Traits having eigenvectors with an absolute value less than 0.15 were not considered on the corresponding PCs because of their minimal loading. This value was chosen because it is relatively small; also, there tends to be a gap near this value in the magnitude of the eigenvectors for the majority of the PCs. PC2 in Figure 3, and PC3 in both Figures 1 and 7 have combina- tions of sweet cherry and ground cherry character states, so no directionality was ascribed to these axes. It should be kept in mind that the ascription of particular traits to individual PC axes (which facilitates the interpretation of the figures) is a simplification: only a portion of the variance of each trait is accounted for by any individual PC. Also, the progressive increase or decrease of the cultivar or family means of each trait along a given PC represents a general trend that may not precisely follow a monotonic progression. 60 In general, the sign and magnitude of the statisti- cally significant correlation coefficients between traits are consistent across the cultivar and seedling data. The signs and magnitudes of some of the r values (correlation coefficients), that were shown to be significant across the large majority of families, were expected. Examples of large, positive r values include those between leaf length and leaf width, and between pit length and pit weight. However, a number of less predictable correlations were also found. Within the cultivar data (Table 10), significant correlations were found between petiole length and fruit flesh color (r=-0.70), and between leaf length and the pit length:width ratio (r= -0.63). The pit ratio has economic importance, since long, narrow pits chip during mechanical pitting. Cor- relations between vegetative and fruit characters are of particular interest, since they could be an aid in indirect selection for fruit traits at the seedling stage. Since the correlations listed in Table 11 are based on a small number (16) of cultivars, it would be desirable to sample a much larger population to improve the reliability of such correlations before these values are used as selection tools or criteria. Since the statistical significance of a correlation with a trait rated on a subjective scale is questionable, a truly objective method of rating fruit flesh color and pubescence is needed. 61 The location of the o.p. families of the cold-hardy cultivars Pitic de Iasi, Lyubskaya, and Rheinische Schattenmorelle near the "ground cherry" ends of the first two PCs in Figure 7 may indicate a positive correlation between ground cherry-like leaf morphology (Figure 15) and cold-hardiness. Figure 15. A typical leaf from each open-pollinated sour cherry family. Abbreviations as in Table 6 indicate maternal parents, except Mc='Montmorency'. The results of the cluster analyses generally suggest morphological relationships among cultivars and families similar to those indicated by PC analysis. However, a discrepency was found between a few of the interfamily (full-sib) relationships, as indicated by the PC and cluster 62 analyses. In the cluster analysis of the 'English Morello' half-sib family (Figure 4), (as well as in a combined analysis of the 'English Morello', 'Rheinische Schattenmorelle', and 'Wolynska' half-sib families), the families with paternal parents 'Karessova' (Kr), Oblacinska (0b), and 'Sumadinka' (Su) cluster together, as do the families with paternal parents 'Nefris' (Nf), 'Rexelle' (Rx), and 'Galaxy' (G1). However, the PC analysis of the 1985 seedling data (Figure 3) indicates that the families with paternal parents 'Nefris', 'Rexelle', and 'Sumadinka' are morphologically similar, while those families with paternal parents 'Galaxy', 'Karessova', and Oblacinska are dissimilar. The morpho- logical patterns indicated by the PC analysis seem to reflect the origins and known genetic relationships among the paternal parents of these families more accurately than does the cluster analysis of the same data. The disparity in the results of the two types of analysis may be a result of the variance unaccounted for by the first three PC axes. The interpretation of the PC analyses of the seedling data is complicated by the fact that the genetic effects of the maternal parents of the half-sib families are confounded with those of the paternal parents. To simplify the interpretation of the seedling analyses, it was assumed that each full-sib family received a random sampling of the maternal alleles, so that the maternal 63 contribution to the morphological variation among full-sib families could be considered constant. However, it is recognized that such effects as dominance and heterosis will result in an arrangement of the seedlings in PC1-PC2- PC3 space with respect to the paternal parents that will differ from the spatial arrangement that would be obtained if the PC values of the paternal cultivars themselves were plotted (all else being equal). It is likely that the po- sitions on the PC figures of the families with relatively few individuals are less accurate than the positions of the larger families, due to error resulting from the restricted genetic sampling of the parental cultivars. A similarly complicated situation occurs in the analysis of the o.p. seedling data, since the pollinators may not have been random. Thus, it is possible that a single cultivar may be the paternal parent of an o.p. family. It is quite probable that the progenies in some o.p. families are grown from seed obtained through self- pollination of the maternal parent. It is well estab- lished that sour cherry cultivars vary widely in their degree of self-compatibility, from highly self-fertile to completely self-sterile (Kolesnikova, 1975; Redalen, 1984). An additional concern results from the confusion in the literature as to the names and origins of a number of the cultivars and seedling parents examined in this study. 64 Thus, an interpretation of the analyses with respect to geographic origins is somewhat tenuous. Furthermore, there is speculation in the literature that certain cultivars are interspecific hybrids (eg. George Glass), while other cultivars may be unrecognized as such (eg. Coronation). The tendency of the three PC analyses to differen- tiate the sour cherry germplasm with respect to its morphological resemblence to ground cherry and sweet cherry may have been enhanced by the inclusion in each analysis of interspecific hybrids (both known and sus- pected) between sour cherry and either of its presumed progenitor species. Such hybrids and their progenies tend to be outliers on the PC figures. The gradation in the morphological resemblence of the "sour cherry" germplasm to ground cherry and sweet cherry, as indicated by some of the PCs, may have been less clearly defined had these hybrids been excluded from the analyses. It is noted that the gradation in the morphological resemblence of the full-sib families to the presumed progenitor species is not as well defined in the PC analysis of the seedlings evaluated in 1985 as it is in both the cultivar and 1986 seedling analyses. The 1985 seedling analysis included a smaller proportion of families with (known) interspecific hybrid parents, which may have effectively diminished the influence of such hybrids on the loading of the traits on the PCs. 65 In the analysis of the seedlings evaluated in 1985 (Figure 3), the families of self-pollinated 'English Morello', and 'North Star' backcrossed to 'English Morello', are outliers. One possible explanation is inbreeding depression. However, inbreeding depression is expected to be less severe in tetraploids (such as sour cherry) than in diploids, particularly if there is tetra- somic inheritance. An alternate hypothesis is that 'English Morello' has ground cherry in its recent ances- try, and its self-pollinated progenies are segregating for unequal genetic contributions by sweet cherry and ground cherry. genegie Implications Since the germplasm examined in the present study does not represent a random sampling of the wild sour cherry gene pool, and since a narrow range of traits was examined, the data are inadequate to substantiate the view that there are two distinct ecotypes. Hybridization between sweet and ground cherry may have occurred many times, and gene flow between sour cherry and its putative progenitor species may be a significant evolutionary factor. The tetraploid Duke cherry, presumed to arise through pollination of sour cherry by an unreduced gamete of sweet cherry (Hruby, 1950), occurs naturally. Unreduced pollen occurs in a number of sweet cherry cultivars (Galletta, 1959; Iezzoni 66 and Hancock, 1984). Interspecific hybrids between sour cherry and ground cherry have been reported growing wild in regions where these species coexist (Karpati, 1944). Evidence accumulated through historical (Hedrick, 1915), anatomical (Yushev, 1970), cytogenetic (Hruby, 1962; Hancock and Iezzoni, 1988), and taxonomic (Yushev, 1975, 1977) investigations, including the present study, suggests that cultivated "sour cherry" may represent an intergradation between ground cherry and sweet cherry. Since the ancestries of most (if not all) "sour cherry" cultivars are unknown, the extent to which ground cherry and sweet cherry may have participated in the origins of the various "sour cherry" cultivars is conjectural. Pos- sibly, cultivated "sour cherry" represents all degrees of hybridization between sour cherry and its two progenitor species; i.e., primary hybrids of sour cherry with sweet cherry or ground cherry, secondary hybrids (backcrosses) of primary hybrids with one of the three species, tertiary hybrids, and so on. Such hybrids may have been selected from the wild, or arisen under cultivation. The pedigrees of many of the new "sour cherry" cultivars being intro- duced by European breeders (including some of the parental cultivars included in this study) include cultivars of Duke cherry, and to a lesser extent, ground cherry. All of the cultivars and many of the o.p. families evaluated in the present investigation were previously 67 surveyed for their malate dehydrogenase (MDH) isozyme banding patterns (Hancock and Iezzoni, 1988). Although Cigany Meggy, a Hungarian landrace, has the MDH banding pattern associated with sour cherry, two out of 34 o.p. progenies of Cigany Meggy segregated for a unique MDH pattern not found for any of the other grunge specimens evaluated. The o.p. Cigany Meggy family is an outlier, located at the "sweet cherry" end of PC2 (Figure 7). On PC1, however, this family is intermediate. All but one of the 16 cultivars (Table 1) have the MDH banding pattern associated with sour cherry. The exception, 'Coronation', has the MDH pattern associated with ground cherry (A. Hancock, personal communication). This cultivar (Cn) is an outlier, located at the "ground cherry" end of PC1 in Figure 1. 'Coronation' is an o.p. progeny of the cold-hardy Russian cultivar Shubinka, which Kolesnikova (1975) classifies as sour cherry. Morpho- logically, 'Coronation' resembles ground cherry, although the fruit are relatively large. Also, the leaf and canopy size of 'Coronation' are larger than those of the ground cherry specimens in our collection. Located near the "ground cherry" ends of the first two PCs in Figure 7 is a separate cluster of o.p. families of the cold-hardy cultivars Pitic de Iasi (PI), Lyubskaya (Lb), and Rheinische Schattenmorelle (RS). Although 'Pitic de Iasi' has the MDH banding pattern 68 typical of sour cherry, four out of 22 o.p. progenies of 'Pitic de Iasi' segregated for the MDH pattern associated with ground cherry (Hancock and Iezzoni, 1988). 'Pitic de Iasi' is an o.p. seedling of the very cold-hardy, late- blooming, self-fertile Russian cultivar Plodorodnaya Michurina, an interspecific hybrid between ground cherry and sour cherry (Michurin, 1955). 'Pitic de Iasi' is a self-fertile, highly productive cultivar grown in the Moldavia region of Romania, where winter temperatures frequently reach -32'C. Both 'Coronation' and 'Pitic de Iasi' appear to combine the fruit quality of sour cherry with the cold-hardiness of ground cherry. Temperature is probably the most significant environ- mental variable in delimiting the natural habitat of sour cherry (Kolesnikova, 1975), which includes the region extending from the Mediterranean coast to northern Europe, Scandanavia, and the western Soviet Union (Hedrick, 1915; Oldén and Nybom, 1968; Kolesnikova, 1975). In regions of the Soviet Union where middle-Russian type sour cherry cultivars are grown, winter temperatures can reach -35‘C with little yield reduction. In such a harsh environment, natural selection will presumably be for those alleles contributed by ground cherry that impart cold-hardiness. The milder climates of southern and western Europe result in decreased selection pressure toward extreme cold- hardiness. In this environment, alleles contributed by 69 sweet cherry that impart vigor may have an adaptive advantage. 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The drought and heat resistance of sweet and sour cherry cultivars in the Crimea (in Russian). Trudy po Prikladnoi Botanike, Genetike i Selektsii. 59(2):118-124. [Hort. Abstr. 48:8883; 1978]. Kobel, F. 1927. Cytological studies on Prunoideae and Pomoideae (in German). Arch. Jul. Klaus-Stift. 3:1-84. 73 Kolesnikova, A. F. 1975. Selektsiya i nekotrie biologicheskie osobennosti vishni v srednei polose RSFSR. Priokskogo Izd-vo, Orel, U.S.S.R. [Plant Breed. Abstr. 47:10743: 1977]. Kramer, S. 1985. Production of cherries in the European socialist countries. In: International Workshop on Improvement of Sweet and Sour Cherry Varieties and Rootstocks. Ed. W. Gruppe. Acta Horticulturae. No. 169, pp.27-34. Martin, G. B. 1984. Genetic diversity of bean landraces in northern Malawi. MS Thesis. Michigan State Univ., East Lansing. Michurin, I. V. 1949. Selected works. Foreign Languages Publ. House, Moscow. Michurin, I. V. 1955. Izbrannie sochineniya. Gosudarst- vennoe Izd-vo, Moskow. 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A taximetric study of an angiosperm family: generic delimitation in the Chrysobalanaceae. New Phytol. 68:1203-1234. Prywer, C. 1936. Cytological studies of some species of the genus Rxggge (in Polish). Acta Soc. Bot. Polon. 13:51-83. [Plant Breed. Abstr. 8:634; 1937-1938]. Raptopoulos, T. 1941. Chromosomes and fertility of cherries and their hybrids. J. Genet. 42:91-113. Redalen, G. 1984. Fertility in sour cherries. Gartenbauwiss. 49(5/6):212-217. Rehder, A. 1958. Manual of cultivated trees and shrubs, 2nd ed. Macmillan, New York. Rhodes, A. M., S. E. Malo, C. W. Campbell, and S. G. Carmer. 1971. A numerical taxonomic study of the avacado (Bereee emegieege Mill.). J. Amer. Soc. Hort. Sci. 96(3):391-395. SAS Institute, Inc. 1985a. SAS user's guide: Statistics, version 5 ed. SAS Institute, Inc., Cary, N.C. SAS Institute, Inc. 1985b. SAS/GRAPH user's guide, version 5 ed. SAS Institute, Inc., Cary, N.C. Scortichini, M. 1985. Hungarian selections of sweet cherry and sour cherry (in Italian). Frutticoltura 47(6/7): 43-49. Small, E., P. Y. Jui, and L. P. Lefkovitch. 1976. A numerical taxonomic analysis of Qegnehie with special reference to species delimitation. Syst. Bot. 1(1):67- 84. Sneath, P. H. A. and R. R. Sokal. 1973. Numerical taxonomy. Freeman, San Francisco. Stancevic, A. S., L. Janda, and J. Gavrilovic. 1976. A comparative investigation of technical and pomological characteristics of selected local forms of sour cherry (in Croatian). Jugosl. Vocarstvo 10(37/38):381-389. [Plant Breed. Abstr. 48:6899: 1978]. Vasilov, V., V. Georgiev, and V. Belyakov. 1982. Cheresha i vishnya. Izd-vo Khristo G. Danov, Plovdiv. 75 Vavilov, N. I. 1951. The origin, variation, immunity and breeding of cultivated plants. Ronald Press, New York. Ward, J. H. 1963. Hierarchical grouping to optimize an objective function. J. Amer. Stat. Assoc. 58:236-244. Wishart, D. 1975. Clustan 1C user manual, 2nd ed. University College, London. Yushev, A. A. 1970. Some anatomical characteristics of the leaves of cherry varieties of differing origin (in Russian). Sborn. Trud. Aspirant. Molod. Nauc. Sotrud. 15:515-519. [Plant Breed. Abstr. 41:1618, 1971]. Yushev, A. A. 1975. Morphological characters of the leaf in sour cherry and their use in the classification of varieties (in Russian). Byull. Vses. Ordena Lenina 54:34-40. [Plant Breed. Abstr. 47:3633; 1977]. Yushev, A. A. 1977. Morphological characters of the fruit in sour cherry and their use in the classification of varieties (in Russian). Byull. Vses. Ordena Lenina 75:27-31. [Plant Breed. Abstr. 49:7429: 1979]. APPENDICES “L APPENDIX A Means and Ranges of Morphological Traits APPENDIX A: Means and Ranges of Morphological Traits. Table A1. Means of the flower, fruit, and vegetative characters measured on 16 sour cherry ailtivars. Character Code? Ollti ivar F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11 F12 F13 BI: 11 32 17 19 .90 .70 2 9.4 7.9 1.19 .17 .55 .31 0‘1 10 35 23 211.121.08 7 13.5 9.1 1.47 .25 .58 .26 EM 9 29 18 19 .93 .67 6 9.7 7.6 1.28 .18 .55 .37 PM 9 43 19 20 .96 .81 3 11.2 8.9 1.25 .24 .60 .44 a; 12 29 15 20 .77 .79 0 8.1 8.9 .90 .21 .52 .36 GP 11' 26 16 20 .81 .69 0 8.9 8.1 1.08 .17 .55 .33 m 13 23 18 21 .84 .71 4 9.7 9.1 1.04 .20 .55 .40 m 9 25 20 20 .99 .78 2 10.4 7.4 1.47 .17 .57 .29 Mt 10 30 17 19 .88 .60 0 9.1 7.9 1.15 .15 .54 .34 Nf 12 29 19 20 .92 .92 7 10.7 9.1 1.18 .30 .58 .49 NS 9 30 16 19 .87 .70 8 8.9 7.6 1.16 .14 .56 .26 w 12 28 16 19 .84 .72 7 9.1 8.9 1.05 .20 .56 .38 SH 9 30 17 19 .89 .72 5 9.4 7.9 1.19 .17 .55 .32 UG 10 36 14 17 .82 .56 9 8.1 8.1 1.00 .19 .60 .51 Vl 10 32 16 19 .87 .93 7 9.7 9.4 1.01 .25 .59 .36 W 17 19 .89 .78 6 9.7 8.6 1.12 .25 .57 .48 CharacterOode" Ollti ivar V2 V6 V7 V9 V10V12V13 31: 28 70 39 .56 .40 52 8 Cn 20 53 24 .46 .37 41 7 EN 17 58 35 .60 .29 49 9 PM 17 68 34 .51 .27 41 9 (I; 30 76 42 .57 .40 41 6 GP 24 73 42 .58 .33 44 5 11b 30 78 46 .60 .39 49 7 Mr 24 66 40 .60 .36 53 8 MI: 29 69 38 .55 .42 55 8 Nf 21 77 46 .60 .28 44 8 NS 14 61 34 .56 .23 56 9 OS 18 77 40 .50 .23 43 7 SH 15 62 38 .60 .25 49 8 UG 15 64 37 .57 .24 44 7 V1 19 93 62 .67 .21 58 8 W1 27 76 41 .54 .36 49 7 1 2 76 See Table l for a description of cultivar abbreviations . See Table 8 for a description of character codes. 77 1° Tabl A2. Full-sib famil meansand fmorpho ical chargctersneasuredmthe ymeans 'EnglishMo lo',0'131'1e1nisi'heog Schattenmorelle', and 'Wolynska' half-sib families. Character Oode3 Crossz V1V2V3 V4V5V6V7 V8 V9VlOV11V12V13V14 EMXEB Mean 19 14 2.2 .16 1.7 75 45 .29 .61 .19 2.5 59 11 1.1 M111. 10 8 1.5 .09 0.0 49 28 .23 .52 .13 0.8 53 8 0.0 Max. 34 22 2.6 .23 4.6 94 58 .35 .92 .31 4.8 67 17 3.6 M Mean 17 9 1.5 .17 0.3 56 36 .21 .65 .17 1.4 54 11 1.0 M111. 10 5 1.1 .12 0.0 37 26 .16 .52 .11 0.0 39 7 0.0 Max. 25 16 2.1 .24 0.6 78 47 .28 .77 .23 3.0 66 16 2.0 Ml 19311 17 13 1.8 .15 0.3 67 37 .25 .56 .19 1.4 56 10 1.2 M111. 10 8 1.3 .11 0.0 43 24 .21 .46 .14 0.6 50 6 0.0 Max. 23 19 2.5 .20 2.0 96 47 .29 .66 .22 2.4 67 11 2.2 EMXH]. 21 14 2.2 .17 1.5 84 51 .29 .61 .16 2.0 64 12 2.0 . 15 7 1.6 .13 0.0 57 37 .24 .53 .12 1.2 56 8 0.8 Max. 33 19 2.8 .23 4.0 118 66 .32 .70 .21 2.4 69 20 3.2 EMXHZ Mean 17 14 2.1 .16 1.6 78 45 .29 .57 .18 2.5 62 11 1.2 Mn. 11 10 1.9 .11 0.2 68 38 .26 .51 .14 1.4 58 8 0.6 Max. 29 22 2.3 .20 3.2 87 54 .31 .69 .27 3.4 68 15 2.6 EMXHM Mean 20 13 2.2 .18 1.2 80 49 .27 .62 .16 2.2 62 10 1.2 M111. 10 7 1.5 .11 0.0 42 27 .19 .46 .10 0.2 49 7 0.0 Max. 37 20 3.0 .28 4.0 114 65 .33 .79 .26 4.4 75 17 3.8 mm: 16 12 1.9 .17 1.2 73 43 .25 .60 .17 2.2 61 11 1.4 . 9 8 1.3 .13 0.0 44 24 .20 .55 .12 0.8 53 10 0.2 Max. 22 16 2.4 .21 2.2 88 55 .29 .67 .21 3.8 67 14 2.6 EMXMK Mean 18 13 2.2 .18 1.0 82 50 .26 .61 .17 2.1 60 11 1.4 M111. 9 6 1.5 .12 0.0 48 32 .24 .53 .12 1.2 57 8 0.2 Max. 28 19 2.7 .25 2.6 108 67 .28 .68 .24 3.2 66 14 3.4 mm- 19 12 2.2 .19 1.2 77 50 .27 .64 .15 2.3 62 10 1.1 . 11 7 1.5 .13 0.0 50 27 .23 .51 .11 0.8 50 7 0.0 Max. 26 15 2.9 .38 3.2 105 66 .31 .83 .22 4.8 73 13 3.4 EMXNf 16 12 1.8 .15 1.4 66 38 .27 .59 .19 1.6 64 11 0.8 . 10 10 1.5 .13 0.4 49 30 .22 .54 .15 0.4 59 10 0.4 Max. 25 15 2.1 .18 2.4 79 46 .36 .62 .24 2.2 67 16 1.0 m Mean 19 9 1.5 .17 0.4 61 34 .23 .57 .15 1.4 57 11 1.0 M111. 13 4 1.0 .10 0.0 41 20 .16 .36 .09 0.0 35 8 0.0 Max. 25 15 2.0 .30 0.8 83 46 .31 .70 .23 5.2 67 15 2.6 m 18 11 1.8 .18 0.7 68 42 .26 .62 .16 2.5 59 11 1.4 . 14 5 1.4 .11 0.0 43 30 .20 .54 .10 0.4 48 9 0.0 DEX. 28 17 2.3 .33 1.8 93 55 .33 .72 .22 4.0 71 14 3.6 mm 16 17 2.1 .13 1.0 86 55 .26 .64 .20 1.8 60 11 1.7 . 12 11 1.8 .11 0.0 69 45 .21 .59 .13 1.0 54 9 1.2 Max. 23 19 2.3 .19 2.0 102 67 .29 .66 .25 3.0 67 16 2.0 EMxRx Mean 16 12 1.9 .16 1.0 67 40 .28 .59 .18 2.0 61 11 0.8 M111. 11 9 1.6 .13 0.0 52 29 .24 .56 .14 0.6 57 7 0.0 DEX. 25 16 2.2 .21 1.8 89 55 .31 .63 .20 4.0 68 18 1.8 m 15 12 1.8 .16 1.6 73 43 .27 .59 .17 2.7 59 13 1.4 . 7 5 1.4 .11 0.0 40 30 .21 .52 .11 1.2 47 8 0.0 Max. 26 19 2.6 .27 5.6 117 65 .34 .73 .24 4.2 69 19 2.2 78 Table A2 (cont'd.) . é MOP MOP EUOH NOH pom- NOH “OH “OH Character Code3 Crossz V1V2V3 V4V5V6V7 V8 V9v10v11v12V13 RSxCr Mean 18 13 2.1 .17 1.0 79 47 .27 .60 .17 2.5 62 11 Min. 14 9 1.8 .13 0.0 62 37 .22 .54 .12 1.4 54 8 Max. 23 16 2.6 .25 2.8 99 58 .33 .76 .22 4.2 71 15 RSxEB Mean 17 15 2.2 .16 1.6 81 48 .27 .60 .18 2.5 61 11 Min. 8 8 1.8 .11 0.0 55 35 .23 .47 .13 1.2 51 7 Max. 25 22 3.0 .22 3.2 113 64 .30 .72 .23 5.6 72 16 R8368 Mean 18 14 2.1 .15 1.6 7948 .26 .62 .18 2.4 59 11 Min. 10 7 1.3 .09 0.0 42 26 .20 .52 .12 0.2 48 7 Max. 29 22 2.8 .22 4.8 118 76 .31 .78 .29 4.4 68 16 RSxMo Mean 18 15 2.0 .14 1.3 75 45 .27 .60 .20 2.7 62 11 Min. 14 9 1.4 .11 0.0 55 34 .23 .52 .15 1.2 51 9 Max. 24 20 2.5 .20 4.0 100 56 .29 .76 .25 4.6 69 14 RSxSuMean 17 15 2.1 .15 2.1 80 47 .27 .59 .19 2.3 58 12 Min. 13 12 1.8 .13 0.4 65 36 .24 .56 .14 0.6 55 9 Max. 24 17 2.2 .17 4.8 86 50 .29 .63 .20 4.0 64 14 mm Mean 19 13 2.0 .16 1.4 75 43 .27 .57 .18 1.8 58 10 Min. 8 9 1.4 .11 0.0 61 33 .25 .50 .12 0.0 52 7 Max. 29 16 2.4 .20 3.2 92 49 .30 .62 .23 2.6 66 13 WlxICL Mean 17 13 1.7 .14 0.7 68 41 .26 .61 .19 2.0 59 10 Min. 12 10 1.4 .10 0.0 50 33 .22 .53 .14 1.0 53 7 Max. 23 20 2.0 .17 1.8 92 57 .31 .69 .26 3.4 65 14 mm 17 9 1.5 .18 0.6 57 33 .26 .59 .16 1.9 58 10 Min. 10 5 1.2 .10 0.0 41 26 .19 .49 .11 0.4 55 7 Max. 24 13 2.1 .27 2.4 74 41 .33 .69 .24 4.4 68 14 mm 17 12 1.8 .15 1.3 74 41 .26 .56 .17 2.0 58 10 Min. 9 8 1.2 .11 0.0 48 25 .19 .47 .11 0.2 50 6 Max. 27 19 2.3 .23 3.4 98 55 .33 .69 .23 5.6 69 14 WlemMean 17 12 1.8 .16 1.0 71 43 .27 .61 .16 2.1 58 10 Min. 13 9 1.6 .12 0.0 62 37 .22 .59 .13 0.4 52 8 Max. 22 16 2.2 .20 1.6 90 53 .29 .64 .20 3.2 66 14 10°F 00% GOO GOO IFOH 0. #ON boos- oo oo 00 00 @0101 0N9 N501 NNH CCU lRangevaluesareofprogenymeans (averagedoversanples). 3See Tables 2, 3, and 4 for descriptions of cultivar abbreviations. See Table 8 for a description of character codes. 79 Table A3. Full-sib family means and ranges1 of norphological characters measured on the 'Montmorency' half-sib family. Character Code3 Paternal Parent2 V1V2V3 V4V5V6V7 V8 V9VlOV11V12V13V14 AV Mean 19 14 2.1 .16 0.2 89 60 .27 .69 .16 1.2 58 7 0.8 Min. 13 9 1.4 .09 0.0 44 35 .24 .60 .13 0.0 53 5 0.0 Max. 28 23 2.6 .19 1.2 113 77 .32 .79 .23 2.2 62 9 1.8 H4 Mean 22 14 1.9 .14 0.8 82 53 .24 .64 .17 1.4 59 9 1.2 Min. 13 9 1.4 .09 0.0 58 28 .19 .49 .13 0.4 54 5 0.0 Max. 30 22 2.6 .19 2.8 114 69 .31 .76 .24 3.0 67 13 2.6 MK Mean 21 13 2.1 .17 1.0 82 52 .26 .64 .15 1.4 63 8 1.3 Min. 15 7 1.7 .11 0.0 67 40 .20 .54 .10 0.6 54 5 0.0 Max. 24 18 2.7 .24 3.4 102 65 .33 .75 .20 2.2 71 12 2.4 Nf Mean 20 14 1.8 .13 0.9 76 46 .24 .60 .19 0.9 60 9 1.2 Min. 15 11 1.5 .10 0.0 63 36 .22 .52 .14 0.0 56 7 0.0 Max. 26 18 2.1 .16 2.2 86 53 .27 .70 .25 2.0 64 14 2.2 R1 Mean 23 17 2.2 .13 0.8 91 59 .25 .66 .19 1.1 62 8 1.5 Min. 13 9 1.5 .09 0.0 59 41 .19 .47 .13 0.0 57 6 0.4 Max. 32 28 2.7 .21 3.6 119 74 .30 .79 .28 2.4 67 13 2.8 R2 'Mean 19 14 1.8 .13 0.9 77 48 .24 .62 .19 0.7 60 8 1.0 Min. 16 9 1.3 .11 0.0 63 41 .19 .57 .13 0.2 56 7 0.0 Max. 23 20 2.2 .16 2.0 88 62 .29 .70 .22 1.6 66 10 2.2 'IR man 20 14 2.0 .14 1.7 84 52 .24 .61 .18 0.8 62 11 0.9 Min. 11 11 1.6 .13 0.0 53 32 .20 .56 .15 0.0 57 9 0.0 Max. 28 17 2.4 .15 3.0 109 69 .27 .66 .20 2.0 67 13 2.0 :Ramevaluesareofprogenymears (averagedoversanples). See Table See Table 5 for a description of cultivar abbreviations. 8 for a description of character codes. 60 69 .13 0.4 56 .66 .17 1.6 .75 .25 2.0 .57 .25 .21 .29 rphologidal characters measured 80 ofmo CharacterOode3 'V1 V2 V3 V4 V5 'V6 V7 V8 V9‘V10 V11 V12 V13 V14 98 64 0 61 40 1.8 119 78 1 0 on.the open-pollinated families. .13 0.2 Means and Table.A4. Parent2 621 59 52 .08 0.0 .21 1.8 65 .15 1 .50 .11 0 .70 .19 2 .15 0.8 .57 .63 .54 .72 .24 .22 .29 .24 .21 .28 82 52 59 40 97 63 8 2 .66 .21 1.2 .59 .18 0. .67 .56 .15 0. .26 .21 .28 73 43 .0 61 36 .4 92 52 .3 1.1 .19 1.2 .15 0.2 .77 .26 3.2 .60 .17 1 .51 .10 0 .25 2 .57 .69 .25 .21 .30 .27 .22 .35 76 51 83 49 56 36 .25 3.6 102 67 0.0 61 37 2.6 107 78 0 0 .17 1. .71 .25 3.8 .50 .11 0. .58 .23 .17 .28 00 .61 .17 1.6 .51 .13 0. .24 3. .16 .70 .25 .17 .31 .57 .50 .11 .24 .18 .30 a veraged over samples). 76 44 52 31 9o 58 ( means 1ption of cultivar abbreviations description of character codes progeny escr values are of table 6 for a d table 8 for a $133198 3See APPENDIX B Computer Programs Table APPENDIX B: Computer Programs B1. SAS program for computing means and ranges. Command ===> 00001 00002 00003 00004 00005 00006 00007 00008 00009 00010 00011 00012 00013 00014 00015 00016 00017 00018 00019 00020 00021 00022 00023 00024 00025 00026 00027 00028 00029 00030 00031 00032 00033 00034 00035 00036 00037 00038 00039 Program Editor CMS FILEDEF RAWDATA DISK FILENAME FILETYPE A: DATA CHERRY; INFILE RAWDATA: INPUT FEMALE 1-2 MALE 4-5 REP 7-8 SAMPLE 16 INTRNODE 18-19 PETLNGTH 21-22 PETWIDTH 24-26 .3 LEAFLNG 28-30 LEAFWDTH 32-33 LEAFTHIK 35-36 .3 VEINANGL 38-39 SERRPRCM 41-42 PETGLNDS 44 LEAFHAIR 46 SWGLONLF 48; PETWIDTH=PETWIDTH*25.4; LEAFTHIK=LEAFTHIK*25.4: LFRATIO=LEAFWDTH/LEAFLNG3 PETRATIO=PETWIDTH/PETLNGTH3 PTLFRATO=PETLNGTH/LEAFLNG3 PROC SORT: BY MALE REP: PROC MEANS NOPRINT; BY MALE REP; VAR INTRNODE PETLNGTH PETWIDTH LEAFLNG LEAFWDTH LEAFTHIK VEINANGL SERRPRCM PETGLNDS LEAFHAIR SWGLONLF LFRATIO PETRATIO PTLFRATO; OUTPUT OUT=DATAMNS MEAN=INTRNODE PETLNGTH PETWIDTH LEAFLNG LEAFWDTH LEAFTHIK VEINANGL SERRPRCM PETGLNDS LEAFHAIR SWGLONLF LFRATIO PETRATIO PTLFRATO; PROC SUMMARY DATA=DATAMNS; VAR INTRNODE PETLNGTH PETWIDTH LEAFLNG LEAFWDTH LEAFTHIK VEINANGL SERRPRCM PETGLNDS LEAFHAIR SWGLONLF LFRATIO PETRATIO PTLFRATO: BY MALE; OUTPUT OUT=MEANS MEAN= 3 PROC PRINT DATA=MEANS3 PROC SUMMARY DATA=DATAMNS; VAR INTRNODE PETLNGTH PETWIDTH LEAFLNG LEAFWDTH LEAFTHIK VEINANGL SERRPRCM PETGLNDS LEAFHAIR SWGLONLF LFRATIO PETRATIO PTLFRATO; BY MALE: OUTPUT OUT=RANGES RANGE= 7 PROC PRINT DATA=RANGE83 RUN: 81 82 Table 32. SAS program for computing Pearson correlation coefficients. Command ===> Program Editor 00001 CMS FILEDEF RAWDATA DISK FILENAME FILETYPE A; 00002 DATA CHERRY; 00003 INFILE RAWDATA; 00004 INPUT FEMALE 1-2 MALE 4-5 REP 7-8 SAMPLE 16 00005 INTRNODE 18-19 PETLNGTH 21-22 PETWIDTH 00006 24-26 .3 LEAFLNG 28-30 LEAFWDTH 32-33 00007 LEAFTHIK 35-36 .3 VEINANGL 38-39 SERRPRCM 00008 41-42 PETGLNDS 44 LEAFHAIR 46 SWGLONLF 48; 00009 PETWIDTH=PETWIDTH*25.4; 00010 LEAFTHIK=LEAFTHIK*25.4: 00011 LFRATIO=LEAFWDTH/LEAFLNG3 00012 PETRATIO=PETWIDTH/PETLNGTH3 00013 PTLFRATO=PETLNGTH/LEAFLNG; 00015 PROC SORT: 00016 BY MALE REP: 00017 PROC MEANS NOPRINT: 00018 BY REP; 00019 VAR INTRNODE PETLNGTH PETWIDTH LEAFLNG 00020 LEAFWDTH LEAFTHIK VEINANGL SERRPRCM PETGLNDS 00021 LEAFHAIR SWGLONLF LFRATIO PETRATIO PTLFRATO; 00023 OUTPUT OUT=DATAMNS 00024 MEAN=INTRNODE PETLNGTH PETWIDTH LEAFLNG 00025 LEAFWDTH LEAFTHIK VEINANGL SERRPRCM PETGLNDS 00026 LEAFHAIR SWGLONLF LFRATIO PETRATIO PTLFRATO; 00028 PROC CORR RANK: 00029 VAR INTRNODE PETLNGTH PETWIDTH LEAFLNG 00030 LEAFWDTH LEAFTHIK VEINANGL SERRPRCM PETGLNDS 00031 LEAFHAIR SWGLONLF LFRATIO PETRATIO PTLFRATO; 00040 RUN; 83 Table B3. SAS program for analysis of variance. Command === Program Editor 00001 CMS FILEDEF RAWDATA DISK FILENAME FILETYPE A: 00002 00003 00004 00005 00006 00007 00008 00009 00010 00011 00012 00013 00014 00015 00016 00017 00018 00019 00020 00021 00022 DATA CHERRY; INFILE RAWDATA: INPUT FEMALE 1-2 MALE 4-5 REP 7-8 SAMPLE 16 INTRNODE 18-19 PETLNGTH 21-22 PETWIDTH 24-26 .3 LEAFLNG 28-30 LEAFWDTH 32-33 LEAFTHIK 35-36 .3 VEINANGL 38-39 SERRPRCM 41—42 PETGLNDS 44 LEAFHAIR 46 SWGLONLF 48: PETWIDTH=PETWIDTH*25.4; LEAFTHIK=LEAFTHIK*25.4: LFRATIO=LEAFWDTH/LEAFLNG3 PETRATIO=PETWIDTH/PETLNGTH3 PTLFRATO=PETLNGTH/LEAFLNG; IF FEMALE=1: PROC GLM: CLASSES MALE REP SAMPLE: MODEL INTRNODE PETLNGTH PETWIDTH LEAFLNG LEAFWDTH LEAFTHIK VEINANGL SERRPRCM PETGLNDS LEAFHAIR SWGLONLF LFRATIO PETRATIO PTLFRATO = MALE REP(MALE); MANOVA H=MALE E=REP(MALE) / PRINTH PRINTE HTYPE=1 ETYPE-l: 00023 RUN: 84 Table B4. SAS program for principal component analysis. Command ===> Program Editor 00001 CMS FILEDEF RAWDATA DISK FILENAME FILETYPE A; 00002 DATA CHERRY; 00003 INFILE RAWDATA: 00004 INPUT FEMALE 1-2 MALE 4-5 REP 7-8 SAMPLE 16 00005 INTRNODE 18-19 PETLNGTH 21-22 PETWIDTH 00006 24-26 .3 LEAFLNG 28-30 LEAFWDTH 32-33 00007 LEAFTHIK 35-36 .3 VEINANGL 38-39 SERRPRCM 00008 41-42 PETGLNDS 44 LEAFHAIR 46 SWGLONLF 48: 00009 PETWIDTH=PETWIDTH*25.4: 00010 LEAFTHIK=LEAFTHIK*25.4: 00011 LFRATIO=LEAFWDTH/LEAFLNG3 00012 PETRATIO=PETWIDTH/PETLNGTH3 00013 PTLFRATO=PETLNGTH/LEAFLNG3 00014 ID=MALE: 00015 PROC SORT: 00016 BY MALE: 00017 PROC MEANS NOPRINT; 00018 BY MALE: 00019 VAR INTRNODE PETLNGTH PETWIDTH LEAFLNG 00020 LEAFWDTH LEAFTHIK VEINANGL SERRPRCM PETGLNDS 00021 LEAFHAIR SWGLONLF LFRATIO PETRATIO PTLFRATO 00022 ID; 00023 OUTPUT OUT=DATAMNS 00024 MEAN=INTRNODE PETLNGTH PETWIDTH LEAFLNG 00025 LEAFWDTH LEAFTHIK VEINANGL SERRPRCM PETGLNDS 00026 LEAFHAIR SWGLONLF LFRATIO PETRATIO PTLFRATO 00027 ID: 00028 PROC PRINCOMP STANDARD DATA=DATAMNS OUT=PCA7 00029 VAR INTRNODE PETLNGTH PETWIDTH LEAFLNG 00030 LEAFWDTH LEAFTHIK VEINANGL SERRPRCM PETGLNDS 00031 LEAFHAIR SWGLONLF LFRATIO PETRATIO PTLFRATO; 00032 PROC BROWSE; 00033 LIST 1,#MEANS PRIN1 PRIN2 PRIN3: 00034 PROC PLOT: 00035 PLOT PRIN2*PRIN1=ID / HREF=0 VREF=07 00036 PROC PLOT; 00037 PLOT PRIN3*PRIN1=ID / HREF=0 VREF=0; 00038 PROC PLOT: 00039 PLOT PRIN3*PRIN2=ID / HREF=0 VREF=03 00040 RUN; 85 Table BS. Clustan program for cluster analysis. 01=IEZZONI,PNXXXXXXX,R62,CM150000. 02=HAL,L*UNSUP,CLUSTAN. 03=*EOS 04=FILE 05= 06= 5 16 S 10E 07= (2F4.2,F4.3,2F4.2,F3.3,2F4.2,3F3.2,F2.2,F3.2,3F4.4) 08=167 124 177 744 414 26 583 099 13 14 20 3 24 559 149 168 093168 127 168 678 413 26 586 097 07 11 20 6 26 611 136 190 10=185 133 199 753 430 27 579 095 14 13 18 2 20 573 155 178 11=166 090 150 567 330 26 581 101 06 16 19 4 24 586 178 161 12=170 116 179 711 433 27 577 101 10 15 21 6 27 611 161 164 13=CORREL 14= 1 5 15=HIERARCHY 16=6 2 4 17=PLINK 18= 6.7 4.3 0.15 19=DENDROGRAM OF THE 'WOLYNSKA' HALF-SIB FAMILY. 20=RESULT 218 X X 22=STOP "111111111111111111111