Metodyka statystyczna pobierania próby do tworzenia kolekcji podstawowej roślinnych zasobów genowych: przegląd dorobku

Marcin Studnicki

marcin_studnicki@sggw.edu.pl
Katedra Doświadczalnictwa i Bioinformatyki, SGGW w Warszawie (Poland)

Wiesław Mądry


Katedra Doświadczalnictwa i Bioinformatyki, SGGW w Warszawie (Poland)

Abstrakt

Kolekcje podstawowe są podzbiorem obiektów wybranych z aktualnie zgromadzonej kolekcji (kolekcji wyjściowej) zasobów genowych, tak aby reprezentowały, z minimalna liczbą duplikatów, one różnorodność genetyczną w kolekcji wyjściowej. Tworzenie tego typu kolekcji ma na celu redukcje kolekcji wyjściowej do rozsądnej liczby obiektów co ułatwi systematyczną i pełną ocenę zmienności genetycznej w kolekcji dla wielu cech genotypowych oraz markerów molekularnych. Kolekcje podstawowe odgrywają ważną rolę w zarządzaniu i wykorzystaniu kolekcji zasobów genowych w badaniach i programach hodowli roślin. Opracowano wiele metod służących do tworzenia kolekcji podstawowych z już istniejących kolekcji roślinnych zasobów genowych. Ważnym aspektem w trakcie tworzenia kolekcji podstawowej jest dobór odpowiedniej metody pobierania próby. Metody pobierania próby są powszechnie stosowane do wyboru próby, która tworzą reprezentatywne kolekcje podstawowe z kolekcji wyjściowej.

Instytucje finansujące

Niniejsza praca wykonana była w ramach projektu promotorskiego numer N N310 066339, przyznanego przez Ministerstwo Nauki i Szkolnictwa Wyższego.

Słowa kluczowe:

kolekcje podstawowe, kolekcje zasobów genowych, metody pobierania próby

Agrama H., Yan A., Wen Gui L., Fleet F., Robert C., Ming-Hsuan J., McClung M. 2009. Genetic Assessment of a Mini-Core Subset Developed from the USDA Rice Genebank. Crop Science 49: 1336 — 1346.
Google Scholar

Amalraj V.A., Balakrishnan R., Jebadhas A.W., Balasundaram N. 2006. Constituting a core collection of Saccharum spontaneum L. and comparison of three stratified random sampling procedures Genetic Resources and Crop Evolution 53: 1563 — 1572.
Google Scholar

Balakrishnan R., Nair N., Sreenivasan T. 2000. A method for establishing a core collection of Saccharum officinarum L. germplasm based on quantitative-morphological data Genetic Resources and Crop Evolution 47: 1 — 9.
Google Scholar

Balfourier F., Roussel V., Strelchenko P., Exbrayat-Vinson F., Sourdill P., Boutet G., Koenig J., Ravel C., Mitrofanova O., Beckert M., Charmet G. 2007. A worldwide bread wheat core collection arrayed in a 384-well plate. Theoretical and Applied Genetics 114: 1265 — 1275.
Google Scholar

Brown A.H.D. 1989 a. Core collections: a practical approach to genetic resources management. Genome 31: 818 — 824.
Google Scholar

Brown A. H. D. 1989 b. The case for core collections. In: The Use of Plant Genetic Resources (A.H.D. Brown, O. H. Frankel, D. R. Marshall and J. T. Williams, eds.). Cambridge University Press, Cambridge, UK.
Google Scholar

Brown A.H.D. 1995. The core collection at the crossroads. w: Core Collections of Plant Genetic Resources (T. Hodgkin, A.H.D. Brown, Th. J. L. van Hintum and E. A. V. Morales, eds.). John Wiley and Sons, UK.
Google Scholar

Brown A.H.D., Spillane C. 1999. Implementing core collections — principles, procedures, progress, problems and promise. w: Johnson, R.C. and T. Hodgkin. 1999. Core collections for today and tomorrow. International Plant Genetic Resources Institute, Rome, Italy.
Google Scholar

Bulińska-Radomska Z., Łapiński B., Arseniuk E. 2008. Plant genetic resources for food and agriculture in Poland – Second National Report. Plant Breeding and Acclimatization Institute, Radzików, Polska
Google Scholar

Chandra S., Huaman Z., Krishna S.H., Ortiz R. 2002. Optimal sampling strategy and core collection size of Andean tetraploid potato based on isozyme data — a simulation study. Theoretical and Applied Genetics 104: 1325 — 1334.
Google Scholar

Charmet G., Balfourier F. 1995. The use of geostatistics for sampling a core collection of perennial ryegrass population. Genetic Resources and Crop Evolution 42: 303 — 309.
Google Scholar

Chavarriaga-Aguirre P., Maya M., Tohme J., Duque M. C., Iglesias C., Bonierbale M. W., Kresovich S., Kochert G. 1999. Using microsatellites, isozymes and AFLPs to evaluate genetic diversity and redundancy in the cassava core collection and to assess the usefulness of DNA-based markers to maintain germplasm collections. Molecular Breeding 5: 263 — 273.
Google Scholar

Chung H.K., Kim K.W., Chung J.W., Lee J.R., Lee S.Y., Dixit A., Kang H.K., Zhao W., McNally K.L., Hamilton R.S., Gwag J.G., Park Y.J. 2009. Development of a core set from a large rice collection using a modified heuristic algorithm to retain maximum diversity. Journal of Integrative Plant Biology 51: 1116 — 1125.
Google Scholar

Cochran W.G. 1977. Sampling techniques, 3rd ed., John Wiley and Sons, New York, USA
Google Scholar

Crossa J., DeLacy I.H., Taba S. 1995. The use of multivariate methods in developing a core collection. Pp. in Core Collections of Plant Genetic Resources (T. Hodgkin, A.H.D. Brown, Th.J.L. van Hintum and E.A.V. Morales, eds.). John Wiley and Sons, UK: 77 — 92.
Google Scholar

Crossa J., Franco J. 2004. Statistical methods for classifying genotypes. Euphytica 153: 19 — 37.
Google Scholar

Diwan N., Bauchan G.R., McIntosh M.S. 1994. A core collection for the United States annual Medicago germplasm collection. Crop Sci. 34: 279 — 285.
Google Scholar

Diwan N., McIntosh M.S., Bauchan G. R. 1995. Methods of developing a core collection of annual Medicago species. Theoretical and Applied Genetics 90: 755 — 761.
Google Scholar

Dwivedi S. L., Puppala N., Upadhyaya H.D., Manivannan N., Singh S. 2008. Developing a core collection of peanut specific to Valencia market type. Crop Sci. 48: 625 — 632.
Google Scholar

Dwivedi S. L., Upadhyaya H. D., Hegd D.M. 2005. Development of core collection using geographic information and morphological descriptors in safflower (Carthamus tinctorius L.) germplasm. Genetic Resources and Crop Evolution 52: 821 — 830.
Google Scholar

Escribano P., Viruel M., Hormaza J. 2008. Comparison of different methods to construct a core germplasm collection in woody perennial species with simple sequence repeat markers. A case study in cherimoya (Annona cherimola, Annonaceae), an underutilised subtropical fruit tree species. Annals of Applied Biology 153: 25 — 32.
Google Scholar

FAO 1996. Global plan of action for the conservation and sustainable utilization of plant genetic resources for food and agriculture. FAO, Rome, Italy.
Google Scholar

FAO 2010. The second report on the state of the world’s plant genetic resources for food and agriculture. FAO, Rome, Italy.
Google Scholar

Franco J., Crossa J., Desphande S. 2010. Hierarchical multiple-factor analysis for classifying genotypes based on phenotypic and genetic data. Crop Sci. 50: 105 — 117.
Google Scholar

Franco J., Crossa J., Ribout J.M., Betran J. 2001. A method for combining molecular markers and phenotypic attributes for classifying plant genotypes. Theoretical and Applied Genetics 103: 944 — 952.
Google Scholar

Franco J., Crossa J., Taba S., Shands H. 2003. A multivariate method for classifying cultivars and studying group x environment x trait interaction. Crop Sci. 43: 1249 — 1258.
Google Scholar

Franco J., Crossa J., Taba S., Shands H. 2005. A sampling strategy for conserving genetic diversity when forming core subsets. Crop Sci. 45: 1035 — 1044.
Google Scholar

Franco J., Crossa J., Villasenor J., Taba S., Eberhart S.A. 1998. Classifying genetic resources by categorical and continuous variables. Crop Sci. 38:1688 — 1696.
Google Scholar

Franco J., Crossa J., Villasenor J., Taba S., Eberhart S.A. 1999. A two-stage, three-way method for classifying genetic resources in multiple environments. Crop Sci. 39: 259 — 267.
Google Scholar

Franco J., Crossa J., Warburton M., Taba S. 2006. Sampling strategies for conserving maize diversity when forming core subsets using genetic markers. Crop Sci. 46: 854 — 864.
Google Scholar

Frankel O.H. 1984. Genetic perspectives of germplasm conservation. In: W. Arber, K. Llimensee, W.J. Peacock D. P. Starlinger, (eds.). Genetic Manipulation: Impact on Man and Society. Cambridge University Press, Cambridge: 161 — 170.
Google Scholar

Frankel O.H., Brown A.H.D. 1984. Plant genetic resources today: A critical appraisal. W: J.H.W. Holden and J.T. Williams, eds. Crop Genetic Resources: Conservation and Evaluation. Allen and Unwin, Winchester, Massachusetts, USA.
Google Scholar

Gauthier M.F., Lumaret R. 1999. Genetic introgression on between tetraploid Dactylis glomerata sp. reichenbachii and glomerata in the French Alps. Insight from morphological and isoenzyme variation, plant systematic and evolution. Plant Syst. Evol. 241: 219 — 234.
Google Scholar

Ghamkhar K., Snowball R., Bennett S.J. 2005. Improving the utilization of germplasm of Trifolium spumosum L. by the development of a core collection using ecogeographical and molecular techniques. p: 262. W: M.O. Humphreys (ed.) Molecular breeding for the genetic improvement of forage crops and turf. Wageningen Academic, Wageningen, Holandia.
Google Scholar

Ghamkhar K., Snowball R., Wintle B.J., Brown A. H. D. 2008. Strategies for developing a core collection of bladder clover (Trifolium spumosum L.) using ecological and agro-morphological data. Australian Journal of Agricultural Research 59:1103 — 1112.
Google Scholar

Gouesnard B., Bataillon T.M., Decoux G., Rozale C., Schoen D.J., David J.L 2001. MSTRAT: An Algorithm for Building Germ Plasm Core Collections by Maximizing Allelic or Phenotypic Richness. Journal of Heredity 92: 93 — 94.
Google Scholar

Gouesnard B., Dallard J., Bertin P., Boyat A., and A. Charcosset. 2005. European maize landraces: Genetic diversity, core collection definition and methodology of use. Maydica 50: 225 — 234.
Google Scholar

Gowda C.L.L., Upadhyaya H.D., Dronavalli N., Singh S. 2011. Identification of large-seeded high-yielding stable kabuli chickpea germplasm lines for use in crop improvement. Crop Sci. 51: 198 — 209.
Google Scholar

Gower J.C. 1971. A general coefficient of similarity and some of its properties. Biometrics 27: 857 — 874.
Google Scholar

Grenier C., Bramel-Cox P. J., Noirot M., Prasada Rao K. E., Hamon, P. 2000b. Assessment of genetic diversity in three subsets constituted from the ICRISAT sorghum collection using random vs. non-random sampling procedures B. Using molecular markers. Theoretical and Applied Genetics 101: 197 — 202.
Google Scholar

Grenier C., Bramel Cox P. J., Noirot M., Prasada Rao K. E., Hamon, P. 2000 a. Assessment of genetic diversity in three subsets constituted from the ICRISAT sorghum collection using random vs. non-random sampling procedures A. Using morpho-agronomical and passport data. Theoretical and Applied Genetics 101: 190 — 196.
Google Scholar

Grenier C., Hamon P., Bramel.Cox P. J. 2001. Core Collection of Sorghum: II. Comparison of Three Random Sampling Strategies. Crop Sci. 41: 241 — 246.
Google Scholar

Hao C., Zhang X., Wang L., Dong Y., ShangX., Jia J. 2006. Genetic diversity and core collection evaluations in common wheat germplasm from the Northwestern Spring Wheat Region in China. Molecular Breeding 17: 69 — 77.
Google Scholar

Harch B.D., Brasford K.E., DeLacy I.H., Lawrence P.K., Cruickshank A. 1995. Patterns of diversity in fatty acid composition in the Australian groundnut germplasm collection. Genetic Resources and Crop Evolution 42: 243 — 256.
Google Scholar

Hartung K. 2006. Biometrical approaches for analysing gene bank evaluation data on barley (Hordeum spec.). Rozprawa doktorska, Uniwersytet w Hohenheim, Stuttgart, Niemcy.
Google Scholar

Haussmann B.I.G., Parzies H.K., Presterl T., Susic Z., Miedaner T. 2004. Plant genetic resources in crop improvement (Review). Plant Genetic Resources: Characterization and utilization 2: 3 — 21.
Google Scholar

Holbrook C.C., Dong W. 2005. Development and evaluation of a mini core collection for the U.S. peanut germplasm collection. Crop Sci. 45: 1540 — 1544.
Google Scholar

Hu J., Zhu J., Xu H. 2000. Methods of constructing core collections by stepwise clustering with three sampling strategies based on the genotypic values of crops. Theoretical and Applied Genetics 101: 264 — 268.
Google Scholar

Igartua E., Gracia M., Lasa J., Medina B., Molina-Cano J., Montoya J., Romagosa I. 1998. The Spanish barley core collection. Genetic Resources and Crop Evolution 45: 475 — 481.
Google Scholar

Islam M.R., Hamid A., Khaliq O.A., Ahmed J.U., Haque M.M., Karim M.A. 2007. Genetic variability in flooding tolerance of mungbean (Vigna radiata L. Wilczek) genotypes. Euphytica 156: 247 — 255.
Google Scholar

Jahufer M.Z.Z., Cooper M., Harch B.D. 1997. Pattern analysis of the diversity of morphological plant attributes and herbage yield in a world collection of white clover (Trifolium repens L.) germplasm characterised in a summer moisture stress environment of Australia. Genetic Resources and Crop Evolution 44: 289 — 300.
Google Scholar

Jansen J., van Hintum Th. 2007. Genetic distance sampling: a novel sampling method for obtaining core collections using genetic distances with an application to cultivated lettuce. Theoretical and Applied Genetics 114: 421 — 428.
Google Scholar

Johnson R.A., Wichern D.W. 2002. Applied multivariate statistical analysis. Prentice-Hall, Inc. Upper Saddle River, New Jork, USA.
Google Scholar

Johnson R.C. and Hodgkin T. 1999. Core collections for today and tomorrow. International Plant Genetic Resources Institute, Rome, Italy.
Google Scholar

Khan M. A., von Witzke-Ehbrecht S., Maass B. L., Becker H. C. 2009. Relationships among different geographical groups, agro-morphology, fatty acid composition and RAPD marker diversity in safflower (Carthamus tinctorius). Genetic Resources and Crop Evolution 6: 19 — 30.
Google Scholar

Kim K.W., Chung H.K., Cho G.T., Ma K.H., Chandrabalan D.. Gwag J.G.. Kim T.S., Cho E.G., Park Y.J. 2007. PowerCore: a program applying the advanced M strategy with a heuristic search for establishing core sets. Bioinformatics 23: 2155 — 2162.
Google Scholar

Kociuba W., Mądry W., Kramek A., Ukalski K., Studnicki M. 2010. Multivariate diversity of Polish winter triticale cultivars for spike and other traits. Plant Breeding and Seed Science 62:31 — 42
Google Scholar

Kölliker R., Stadelmann F.J., Reidy B., Nösberger J. 1999. Genetic variability of forage grass cultivars: A comparison of Festuca pratensis Huds., Lolium perenne L., and Dactylis glomerata L.. Euphytica 106: 261 — 270.
Google Scholar

Krebs C. 1989. Ecological Methodology. HarperCollins, New York, USA.
Google Scholar

Krzanowski W.J. 1988. Principles of multivariate analysis: a user’s perspective. Oxford University Press, Oxford, UK.
Google Scholar

Levene H. 1960. Robust tests for equality of variances. In: Olkin, I. (Ed.), Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling. Stanford University Press, Stanford.
Google Scholar

Li C. T., Shi, C. H., Wu, J. G., Xu, H. M., Zhang, H. Z. & Ren, Y. L. 2004. Methods of developing core collections based on the predicted genotypic value of rice (Oryza sativa L.). Theoretical and Applied Genetics 108: 1172 — 1176.
Google Scholar

Li Y., Shi Y., Cao Y., Wang T. 2005. Establishment of a core collection for maize germplasm preserved in Chinese National Genebank using geographic distribution and characterization data. Genetic Resources and Crop Evolution 51: 845 — 852.
Google Scholar

Li Y.X., Li T.H., Zhang H.L., Qi Y.W. 2007. Sampling strategy for a primary core collection of peach (Prunus persica (L.) Batsch.) germplasm. European Journal of Horticultural Science 72: 268 — 274.
Google Scholar

Li Z., Zhang H., Zeng Y., Yang Z., Shen S., Sun C., Wang X. 2002. Studies on sampling schemes for the establishment of core collection of rice landraces in Yunnan, China. Genetic Resources and Crop Evolution 49: 67 — 74.
Google Scholar

Liu X.L., Cai Q., Ma L., Wu C.W., Lu X., Ying X.M., Fan Y.H. 2009. Strategy of sampling for pre-core collection of sugarcane hybrid. Acta Agronomica Sinica 35: 1209 — 1216.
Google Scholar

LogozzoG., Donnoli R., Macaluso L., Papa R., Knüpffer H., Zeuli P. 2007. Analysis of the contribution of Mesoamerican and Andean gene pools to European common bean (Phaseolus vulgaris L.) germplasm and strategies to establish a core collection. Genetic Resources and Crop Evolution 54:. 1763 — 1779.
Google Scholar

Luan F., Delannay I., Staub J. E. 2008. Chinese melon (Cucumis melo L.) diversity analyses provide strategies for germplasm curation, genetic improvement, and evidentiary support of domestication patterns. Euphytica 164: 445 — 461.
Google Scholar

Mahajan R.K., Bisht I.S., Gautam P.L. 1999. Sampling strategies for developing Indian sesame core collection. Indian Journal of Plant Genetic Resources 12: 1 — 9
Google Scholar

Mahalakshmi V., Ng Q., Atalobhor J., Ogunsola D., Lawson M., Ortiz R. 2007. Development of a West African yam Dioscorea spp. core collection. Genetic Resources and Crop Evolution 54: 1817 — 1825.
Google Scholar

Malosetti M., Abadie T. 2001. Sampling strategy to develop a core collection of Uruguayan maize landraces based on morphological traits. Genetic Resources and Crop Evolution 48:.381 — 390.
Google Scholar

Marita J. M., Rodriguez J. M., Nienhuis J. 2000. Development of an algorithm identifying maximally diverse core collections. Genetic Resources and Crop Evolution 47: 515 — 526.
Google Scholar

McKhann H.I., Camilleri C., Bera A., Bataillon T., David J.L., Reboud X., Le Corre V., Gut I.G. , Brunel D. 2004. Nested core collections maximizing genetic diversity in Arabidopsis thaliana. Plant J. 38: 193 — 202.
Google Scholar

Mohammadi S.A., Prasanna M. 2003. Analysis of genetic diversity in crop plants — salient statistical tools and considerations. Crop Sci. 43: 1235 — 248.
Google Scholar

Mosjidis J. A., Klingler K. A. 2006. Genetic Diversity in the Core Subset of the U.S. Red Clover Germplasm. Crop Sci. 46: 758 — 762.
Google Scholar

Nei M. 1973. Analysis of gene diversity in subdivided populations. Proceedings of the National Academy of Sciences 70: 3321 — 3323.
Google Scholar

Neyman J. 1934. On the two different aspects of the representative method: The method of stratified sampling and the method of purposive selection. Journal of the Royal Statistical Society 97: 558 — 625.
Google Scholar

Noirot M., Hamon S., Anthony F. 1996. The principal component scoring: a new method of constituting a core collection using quantitative data. Genetic Resources and Crop Evolution 43: 1 — 6.
Google Scholar

Ntundu W.H., Shillah S.A., Marandu W.Y.F., Christiansen J.L. 2006. Morphological diversity of bambara groundnut [Vigna subterranea (L.) Verdc.] landraces in Tanzania. Genetic Resources and Crop Evolution 53: 367 — 378
Google Scholar

Oliveira M. F., Nelson R. L., Geraldi I. O., Cruz C. D., de Toledo J. F. F. 2010. Establishing a soybean germplasm core collection. Field Crops Research 119: 277 — 289.
Google Scholar

Olukolu B.A., Mayes S., Stadler F., Ng N.Q., Fawole I., Dominique D., Azam-Ali S.N., Abbott A.G., Kole C. 2011. Genetic diversity in Bambara groundnut (Vigna subterranea (L.) Verdc.) as revealed by phenotypic descriptors and DArT marker analysis. Genetic Resources and Crop Evolution DOI: 10.1007/s10722-011-9686-5.
Google Scholar

Ramanatha Rao V., Hodgkin T. 2002. Genetic diversity and conservation and utilization of plant genetic resources. Plant Cell, Tissue and Organ Culture 68: 1 — 19.
Google Scholar

Reddy L. J., Upadhyaya H.D., Gowda C.L.L., Singh S. 2005. Development of core collection in pigeonpea [Cajanus cajan (L.) Millspaugh] using geographic and qualitative morphological descriptors. Genetic Resources and Crop Evolution 52: 1049 — 1056.
Google Scholar

Reif J.C., Melchinger A.E., Frisch M. 2005. Genetical and mathematical properties of similarity and dissimilarity coefficients applied to plant breeding and seed bank management. Crop Sci. 45: 1 — 7.
Google Scholar

Robertson L.D., Singh K.B., Erskine W., Abd El Moneim A.M. 1996. Useful genetic diversity in germplasm collections of food and forage legumes from West Asia and North Africa. Genetic Resources and Crop Evolution 43: 447 — 460.
Google Scholar

Rodino A., Santalla M., Ro A.D., Singh S. 2003. A core collection of common bean from the Iberian peninsula. Euphytica 131: 165 — 175.
Google Scholar

Ronfort J., Bataillon T., Santoni S., Delalande M., David J.L., Prosperi J-M. 2006. Microsatellite diversity and broad scale geographic structure in a model legume: Building a set of nested core collection for studying naturally occurring variation in Medicago truncatula L. BMC Plant Biology 6: 28.
Google Scholar

Santos M., Dias J., 2004. Evaluation of a core collection of Brassica oleracea accessions for resistance to white rust of crucifers (Albugo candida) at the cotyledon stage. Genetic Resources and Crop Evolution 51: 713 — 722.
Google Scholar

Schmidt J. 2005 a. The European Lolium perenne core collection in the Botanical Garden of the Plant Breeding and Acclimatization Institute, Bydgoszcz, Poland. In: Boller B., Willner E., Maggioni L., Lipman E. Report of a Working Group on Forages. Eighth meeting, 10–12 April 2003, Linz, Austria. International Plant Genetic Resources Institute, Rome, Italy.
Google Scholar

Schmidt J. 2005b. Variation of European ecotypes of perennial rygrass (Lolium perenne L.) in Poland. Plant Breeding and Seed Science 51: 75 — 89.
Google Scholar

Schoen D.J., Brown A.H.D. 1993. Conservation of allelic richness in wild crop relatives is aided by assessment of genetic markers. Proceedings of the National Academy of Sciences 90: 10623 — 10627.
Google Scholar

Skinner D.Z., Bauchan G.R., Auricht G., Hughes S. 1999. Developing a core collection from a large annual Medicago germplasm collection. W: Johnson, R.C., Hodgkin T. 1999. Core collections for today and tomorrow. International Plant Genetic Resources Institute, Rzym, Włochy.
Google Scholar

Skroch P.W., Nienhuis J., Beebe S., Tohme J., PedrazaF. 1998. Comparison of Mexican common bean (Phaseolus vulgaris L.) core and reserve germplasm collections. Crop Sci. 38: 488 — 496.
Google Scholar

Spagnoletti Zeuli P.L., Qualset C.O. 1993. Evaluation of five strategies for obtaining a core subset from a large genetic resource collection of durum wheat. Theoretical and Applied Genetics 87: 295 — 304.
Google Scholar

Studnicki M., Mądry W., Kociuba W. 2010a. The efficiency and effectiveness of sampling strategies used to develop a core collection for the Polish spring triticale (×Triticosecale Wittm.) germplasm resources. Communications in Biometry and Crop Sci. 5:.127 — 135.
Google Scholar

Studnicki M., Mądry W., Kociuba W. 2010b. Efektywność metod pobierania próby w tworzeniu kolekcji podstawowej pszenżyta jarego przy użyciu danych fenotypowych. Zeszyty Problemowe Postępów Nauk Rolniczych 555: 409 — 418.
Google Scholar

Studnicki M., Mądry W., Śmiałowski T. 2009. Porównanie efektywności metod statystycznych tworzenia kolekcji podstawowej na przykładzie pszenicy jarej. Biuletyn IHAR 252:105 — 117.
Google Scholar

Thachuk C., Crossa J., Franco J., Dreisigacker S., Warburton M., Davenport G.F. 2009. Core Hunter: an algorithm for sampling genetic resources based on multiple genetic measures. BMC Bioinformatics 10: 243.
Google Scholar

Thompson S.K. 2002. Sampling. 2nd ed. John Wiley & Sons, New York, USA.
Google Scholar

Upadhyaya H.D. 2003. Phenotypic diversity in groundnut (Arachis hypogaea L.) core collection assessed by morphological and agronomical evaluations. Genetic Resources and Crop Evolution 50: 539 — 550.
Google Scholar

Upadhyaya H.D., Dwivedi S.L., Gowda C., Singh S. 2007b. Identification of diverse germplasm lines for agronomic traits in a chickpea (Cicer arietinum L.) core collection for use in crop improvement Field Crops Research 100: 320 — 326.
Google Scholar

Upadhyaya H.D., Bramel P.J., Ortiz R., Singh S. 2002. Developing a mini core of peanut for utilization of genetic resources. Crop Sci. 42: 2150 — 2156.
Google Scholar

Upadhyaya H. D., Dwivedi S. L., Nadaf H. L., Singh S. 2011 a. Phenotypic diversity and identification of wild Arachis accessions with useful agronomic and nutritional traits. Euphytica (wdruku).
Google Scholar

Upadhyaya H. D., Gowda C., Pundir R., Reddy V. G., Singh, S. 2006 b. Development of core subset of finger millet germplasm using geographical origin and data on 14 quantitative traits Genetic Resources and Crop Evolution. 53: 679 — 685.
Google Scholar

Upadhyaya H.D., Gowda C.L.L., Buhariwalla H.K., Crouch J.H. 2006 a. Efficient use of crop germplasm resources: identifying useful germplasm for crop improvement through core and mini-core collections and molecular marker approaches. Plant Genetic Resources: Characterization and Utilization 4: 25 — 35.
Google Scholar

Upadhyaya H.D., Ortiz R. 2001. A mini core subset for capturing diversity and promoting utilization of chickpea genetic resources in crop improvement Theoretical and Applied Genetics 102: 1292 — 1298.
Google Scholar

Upadhyaya H.D., Ortiz R., Bramel P.J., Singh S. 2003. Development of a groundnut core collection using taxonomical, geographical and morphological descriptors. Genetic Resources and Crop Evolution 50: 139 — 148.
Google Scholar

Upadhyaya H.D., Ravishankar C.R., Narasimhudu Y., Sarma N.D.R.K., Singh S.K., Varshney S.K., Reddy V.G., Singh S., Parzies H.K., Dwivedi S.L., Nadaf H.L., Sahrawat S., Gowda C.L.L. 2011b. Identification of trait-specific germplasm and developing a mini core collection for efficient use of foxtail millet genetic resources in crop improvement. Field Crops Research 124: 459 — 467.
Google Scholar

Upadhyaya H.D., Reddy K.N., Gowda C.L.L., Singh S. 2007a. Phenotypic diversity in the pigeonpea (Cajanus cajan L.) core collection. Genetic Resources and Crop Evolution 54: 1167 — 1184.
Google Scholar

Upadhyaya H.D., Reddy K.N., Gowda C.L.L., Singh S. 2011c. Development of pearl millet minicore collection for enhanced utilization of germplasm. Crop Sci. 51: 217 — 223.
Google Scholar

Upadhyaya H.D., Reddy L.J., Gowda C.L.L., Singh S. 2006. Identification of diverse groundnut germplasm: Sources of early maturity in a core collection. Field Crops Research 97: 261 — 271.
Google Scholar

Upadhyaya H.D., Sharma S., Ramulu B., Bhattacharjee R., Gowda C. L. L., Gopal R.V., Singh S. 2010. Variation for qualitative and quantitative traits and identification of trait-specific sources in new sorghum germplasm. Crop and Pasture Science 61: 609 — 618.
Google Scholar

van de Wouw M., Chris, K., van Hintum, T., van Treuren, R., Visser, B. 2010a. Genetic erosion in crops: concept, research results and challenges. Plant Genetic Resources: Characterization and Utilization 8: 1 — 15.
Google Scholar

van de Wouw M., van Hintum T., Kik C., van Treuren R., Visser B. 2010b. Genetic diversity trends in 20th century crop cultivars — a meta analysis. Theoretical and Applied Genetics 120: 1241 — 1252.
Google Scholar

van Hintum Th.J.L. 1999. The general methodology for creating a core collection. w: Johnson, R.C. and T. Hodgkin. 1999. Core collections for today and tomorrow. International Plant Genetic Resources Institute, Rome, Italy.
Google Scholar

van Hintum Th.J.L., Brown A.H.D., C. Spillane and T. Hodgkin. 2000. Core collections of plant genetic resources. IPGRI Technical Bulletin No. 3. International Plant Genetic Resources Institute, Rzym, Włochy.
Google Scholar

van Raamsdonk L., Wijnker J. 2000 The development of a new approach for establishing a core collection using multivariate analyses with tulip as case. Genetic Resources and Crop Evolution 47: 403 — 416.
Google Scholar

Vencovsky R., Crossa J. 1999. Variance effective population size under mixed self and random mating with applications to genetic conservation of species. Crop Sci. 39: 1282 — 1294.
Google Scholar

Vencovsky R., Crossa J. 2003. Measurements of representativeness used in genetic resources conservation and plant breeding. Crop Sci. 43: 6: 1912 — 1921.
Google Scholar

Wang J.C., Hu J., Huang X.X., Xu S.C. 2008. Assessment of different genetic distances in constructing cotton core subset by genotypic values. Journal of Zhejiang University — Science B 9:356 — 362
Google Scholar

Wang J.C., Hu J., Xu H. M.,Zhang S. 2007. A strategy on constructing core collections by least distance stepwise sampling. Theoretical and Applied Genetics 115: 1 — 8.
Google Scholar

Wang Y., Zhang J., Sun H., Ning N., Yang L. 2011. Construction and evaluation of a primary core collection of apricot germplasm in China. Scientia Horticulturae 128: 311 — 319.
Google Scholar

Ward J. 1963. Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association 38: 236–244.
Google Scholar

Weihai M., Jinxin Y., Sihachakr D. 2008. Development of core subset for the collection of Chinese cultivated eggplants using morphological-based passport data. Plant Genetic Resources: Characterization and Utilization 6: 33 — 40.
Google Scholar

Xiurong Z., Yingzhong Z., Yong C., Xiangyun F., Qingyuan G., Mingde Z.,Hodgkin T. 2000. Establishment of sesame germplasm core collection in China. Genetic Resources and Crop Evolution 47: 273 — 279.
Google Scholar

Xu H., Mei Y., Hu J., Zhu J., Gong P. 2006. Sampling a core collection of Island cotton (Gossypium barbadense L.) based on the genotypic values of fiber traits. Genetic Resources and Crop Evolution 53: 515 — 521.
Google Scholar

Xu Y. 2010. Molecular plant breeding. CAB International, Wallingford, UK.
Google Scholar

Yan W.G., Ruter J.N., Bryant R.J., Bockelman H.E., Fjellstrom R.G., Chen M.H., Tai T.H., McClung A.M. 2007. Development and evaluation of a core subset of the USDA rice germplasm collection. Crop Sci. 47: 869 — 876.
Google Scholar

Zewdie Y., Tong N., Bosland P. 2004. Establishing a core collection of Capsicum using a cluster analysis with enlightened selection of accessions. Genetic Resources and Crop Evolution 51: 147 — 151.
Google Scholar

Zhang H., Zhang D., Wang M., Sun J., Qi Y., Li J., Wei X., Han L., Qiu Z., Tang S., Li Z. 2011. A core collection and mini core collection of Oryza sativa L. in China. Theoretical and Applied Genetics 122: 49 — 61.
Google Scholar

Pobierz


Opublikowane
03/29/2012

Cited By / Share

Studnicki, M. i Mądry, W. (2012) „Metodyka statystyczna pobierania próby do tworzenia kolekcji podstawowej roślinnych zasobów genowych: przegląd dorobku”, Biuletyn Instytutu Hodowli i Aklimatyzacji Roślin, (263), s. 129–160. doi: 10.37317/biul-2012-0081.

Autorzy

Marcin Studnicki 
marcin_studnicki@sggw.edu.pl
Katedra Doświadczalnictwa i Bioinformatyki, SGGW w Warszawie Poland

Autorzy

Wiesław Mądry 

Katedra Doświadczalnictwa i Bioinformatyki, SGGW w Warszawie Poland

Statystyki

Abstract views: 39
PDF downloads: 38


Licencja

Prawa autorskie (c) 2012 Marcin Studnicki, Wiesław Mądry

Creative Commons License

Utwór dostępny jest na licencji Creative Commons Uznanie autorstwa – Na tych samych warunkach 4.0 Miedzynarodowe.

Z chwilą przekazania artykułu, Autorzy udzielają Wydawcy niewyłącznej i nieodpłatnej licencji na korzystanie z artykułu przez czas nieokreślony na terytorium całego świata na następujących polach eksploatacji:

  1. Wytwarzanie i zwielokrotnianie określoną techniką egzemplarzy artykułu, w tym techniką drukarską oraz techniką cyfrową.
  2. Wprowadzanie do obrotu, użyczenie lub najem oryginału albo egzemplarzy artykułu.
  3. Publiczne wykonanie, wystawienie, wyświetlenie, odtworzenie oraz nadawanie i reemitowanie, a także publiczne udostępnianie artykułu w taki sposób, aby każdy mógł mieć do niego dostęp w miejscu i w czasie przez siebie wybranym.
  4. Włączenie artykułu w skład utworu zbiorowego.
  5. Wprowadzanie artykułu w postaci elektronicznej na platformy elektroniczne lub inne wprowadzanie artykułu w postaci elektronicznej do Internetu, lub innej sieci.
  6. Rozpowszechnianie artykułu w postaci elektronicznej w internecie lub innej sieci, w pracy zbiorowej jak również samodzielnie.
  7. Udostępnianie artykułu w wersji elektronicznej w taki sposób, by każdy mógł mieć do niego dostęp w miejscu i czasie przez siebie wybranym, w szczególności za pośrednictwem Internetu.

Autorzy poprzez przesłanie wniosku o publikację:

  1. Wyrażają zgodę na publikację artykułu w czasopiśmie,
  2. Wyrażają zgodę na nadanie publikacji DOI (Digital Object Identifier),
  3. Zobowiązują się do przestrzegania kodeksu etycznego wydawnictwa zgodnego z wytycznymi Komitetu do spraw Etyki Publikacyjnej COPE (ang. Committee on Publication Ethics), (http://ihar.edu.pl/biblioteka_i_wydawnictwa.php),
  4. Wyrażają zgodę na udostępniane artykułu w formie elektronicznej na mocy licencji CC BY-SA 4.0, w otwartym dostępie (open access),
  5. Wyrażają zgodę na wysyłanie metadanych artykułu do komercyjnych i niekomercyjnych baz danych indeksujących czasopisma.

Inne teksty tego samego autora

1 2 3 > >>