Statistical assessment of determination of fruit yield in blackcurrant (Ribes nigrum L.) by two multiplicative yield components

Stanisław Pluta

io@inhort.pl
Instytut Sadownictwa i Kwiaciarstwa, ul. Pomologiczna Skierniewice (Poland)

Wiesław Mądry


Szkoła Główna Gospodarstwa Wiejskiego, Warszawa (Poland)

Edward Żurawicz


Instytut Sadownictwa i Kwiaciarstwa, ul. Pomologiczna Skierniewice (Poland)

Marcin Kozak


Szkoła Główna Gospodarstwa Wiejskiego, Warszawa (Poland)

Abstract

Results of studies on determination of blackcurrant fruit yield per plant by two multiplicative yield components (number of fruits per plant and mean fruit weight) are presented. The genetic as well as joint environmental and individual variability was considered. A field experiment with 14 genotypes (15 plants per genotype) was established at the Experimental Orchard of the Research Institute of Pomology and Floriculture (RIPF) in Dąbrowice, near Skierniewice, in 1996. Measurements of the fruit yield per plant and its two multiplicative components were performed in 1998–2001. The sequential yield component analysis (SYCA) has shown that the number of fruits per plant had determined 50% to 90% of genotypic variability of the fruit yield, depending on weather conditions in the years of investigation. Mean fruit weight determined only 6% to 24% of genotypic variability of the fruit yield. The relations found in determining the environmental variability pattern for both yield components were similar to those detected for the genotypic variability. The number of fruits per plant determined 72% to 96% of the environmental variability of fruit yield, whereas the mean fruit yield determined only 3% to 20% of this variability among the examined genotypes.


Keywords:

Ribes nigrum L., blackcurrant, multiplicative yield components, sequential yield component analysis (SYCA), fruit yield per plant, fruit number per plant, mean fruit weight

Baumann T. E.; Eaton G.W.; Spaner D. 1993. Yield components of day-neutral and short-day strawberry varieties on raised beds in British Columbia. HortScience 28 (9): 891 — 894.
Google Scholar

Board, J. E., Kang, M. S., Bodrero, M. L. 2003. Yield components as indirect selection criteria for late-planted soybean cultivars. Agronomy Journal 95: 420 — 429.
Google Scholar

Bonney G. E., Kissling G. E. 1986. Gram-Schmidt Orthogonalization of Multinormal Variates: Applications in Genetics. Biometrical Journal 28: 417 — 425.
Google Scholar

Bock R. D. 1975. Multivariate statistical methods in behavioural research. Toronto: McGraw-Hill.
Google Scholar

Cortell J. M.; Strik B. C. 1997. Effect of floricane number in 'Marion' trailing blackberry. II. Yield components and dry mass partitioning. Journal-of-the-American-Society-for-Horticultural-Science. 122: 611 — 615.
Google Scholar

Eaton, G. W., Kyte, T. R. 1978. Yield component analysis in strawberry. J. Am. Soc. Horticult. Sci., 103:578 — 583.
Google Scholar

Eaton G. W., McPherson E. A. 1978. Morphological components of yield in cranberry. Horticultural Research 17: 73 — 82.
Google Scholar

Fraser J., Eaton G. W. 1983. Applications of yield component analysis to crop research. Field Crop Abstracts 36:787 — 796.
Google Scholar

Freeman J. A., Eaton G. W., Baumann T. E., Daubeny H. A., Dale A. 1989. Primocane removal enhances yield component of raspfruits. Journal of the American Society of Horticultural Science 114: 6 — 9.
Google Scholar

Gołaszewski J. 1996. A method of yield component analysis. Biometrical Letters 33: 79 — 88.
Google Scholar

Kang M. S. 1994. Applied quantitative genetics. Baton Rouge, LA: M.S. Kang Publication.
Google Scholar

Kang M. S. 2003. Formulas and software for plant geneticists and plant breeders. New York: Food Products Press.
Google Scholar

Kozak M. 2002. Statystyczna analiza uwarunkowania zmienności plonu roślin przez jego składowe. Praca doktorska, SGGW, Warszawa.
Google Scholar

Kozak M., Mądry W. 2006. Note on yield component analysis. Cereal Res. Commun. 34:933 — 940.
Google Scholar

Lacey C. N. D. 1973. Phenotypic correlations between vegetative characters and yield components in strawberry. Euphytica 22: 546 — 554.
Google Scholar

Mądry W., Kozak M. 2000. Analiza ścieżek i sekwencyjna analiza plonu w badaniach zależności plonu od cech łanu. Cz. I. Opis metod. Rocz. N. Roln., Seria A, 115:143 — 157.
Google Scholar

Mądry W., Kozak. M., Pluta S., Żurawicz E. 2003. Zastosowanie sekwencyjnej analizy plonu w badaniach nad uwarunkowaniem zmienności plonu owoców porzeczki czarnej (Ribes nigrum L.) na roślinie przez cechy plonotwórcze. Biul. IHAR 226/227/1: 31 — 40.
Google Scholar

Mądry W., Kozak M., Pluta S., Żurawicz E. 2005. A New approach to sequential yield component analysis (SYCA): Application to fruit yield in blackcurrant (Ribes nigrum L.). Journal of New Seeds, 7: 85 — 107.
Google Scholar

Neter J., Wasserman W., Kutner M. H. 1990. Applied linear statistical models. Regression, analysis of variance and experimental designs. IRWIN, New York.
Google Scholar

Panteyev A. V., Korolenko A. V. 2000. Correlative relationships between the main yield components in black currant. Plodowodstwo. 13:116 — 118.
Google Scholar

Piepho H. P. 1995. A simple procedure for yield component analysis. Euphytica 84: 43 — 48.
Google Scholar

Pluta S. 1994. Analiza dialleliczna cech użytkowych porzeczki czarnej. Praca doktorska, ISK Skierniewice
Google Scholar

Pluta S. 1996. Zeszyty Pomologiczne. Porzeczki i Agrest. Wyd. ISK:1 — 89.
Google Scholar

Pomologia odmianoznawstwo roślin sadowniczych — aneks. 2003. Porzeczka czarna. Porzeczka czerwona. Agrest. Praca zbiorowa pod red. E. Żurawicza, PWRiL, Warszawa 2003: 165 — 173; 175 — 180; 182 — 188.
Google Scholar

Rozbicki J. 1997. Agrotechniczne uwarunkowania wzrostu, rozwoju i plonowania pszenżyta ozimego. Rozprawa habilitacyjna, Fundacja Rozwój SGGW, Warszawa.
Google Scholar

Sparnaaij L.D. and Bos I. 1993. Component analysis of complex characters in plant breeding. I. Proposed method for quantifying the relative contribution of individual components to variation of the complex character. Euphytica 70: 225 — 235.
Google Scholar

Strik B.C. and Proctor J.T.A. 1988. Yield component analysis of strawberry genotypes differing in productivity. Journal of the American Society of Horticultural Science 113: 124 — 129.
Google Scholar

Webb R. A. 1976 a. The components of yield in black currants. Scientia Horticulturae, 4: 247 — 254.
Google Scholar

Webb R. A. 1976 b. The influence of yield components on cultivar differences in black currants. Scientia Horticulture, 5:119 — 126.
Google Scholar

Winer B. J. 1971. Statistical principles in experimental design. New York: McGraw–Hill
Google Scholar

Yadav O. P., Manga V. K., Saxena M. B. L. 1994. Ontogenetic approach to grain production in pearl millet (Pennisetum gluacum L.) based on path-coefficient analysis. Indian J. Agric. Sci. 64: 233 — 236.
Google Scholar


Published
2008-09-30

Cited by

Pluta, S. (2008) “Statistical assessment of determination of fruit yield in blackcurrant (Ribes nigrum L.) by two multiplicative yield components”, Bulletin of Plant Breeding and Acclimatization Institute, (249), pp. 241–249. doi: 10.37317/biul-2008-0051.

Authors

Stanisław Pluta 
io@inhort.pl
Instytut Sadownictwa i Kwiaciarstwa, ul. Pomologiczna Skierniewice Poland

Authors

Wiesław Mądry 

Szkoła Główna Gospodarstwa Wiejskiego, Warszawa Poland

Authors

Edward Żurawicz 

Instytut Sadownictwa i Kwiaciarstwa, ul. Pomologiczna Skierniewice Poland

Authors

Marcin Kozak 

Szkoła Główna Gospodarstwa Wiejskiego, Warszawa Poland

Statistics

Abstract views: 67
PDF downloads: 28


License

Copyright (c) 2008 Stanisław Pluta, Wiesław Mądry, Edward Żurawicz, Marcin Kozak

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Upon submitting the article, the Authors grant the Publisher a non-exclusive and free license to use the article for an indefinite period of time throughout the world in the following fields of use:

  1. Production and reproduction of copies of the article using a specific technique, including printing and digital technology.
  2. Placing on the market, lending or renting the original or copies of the article.
  3. Public performance, exhibition, display, reproduction, broadcasting and re-broadcasting, as well as making the article publicly available in such a way that everyone can access it at a place and time of their choice.
  4. Including the article in a collective work.
  5. Uploading an article in electronic form to electronic platforms or otherwise introducing an article in electronic form to the Internet or other network.
  6. Dissemination of the article in electronic form on the Internet or other network, in collective work as well as independently.
  7. Making the article available in an electronic version in such a way that everyone can access it at a place and time of their choice, in particular via the Internet.

Authors by sending a request for publication:

  1. They consent to the publication of the article in the journal,
  2. They agree to give the publication a DOI (Digital Object Identifier),
  3. They undertake to comply with the publishing house's code of ethics in accordance with the guidelines of the Committee on Publication Ethics (COPE), (http://ihar.edu.pl/biblioteka_i_wydawnictwa.php),
  4. They consent to the articles being made available in electronic form under the CC BY-SA 4.0 license, in open access,
  5. They agree to send article metadata to commercial and non-commercial journal indexing databases.

Most read articles by the same author(s)

1 2 3 4 5 > >> 

Similar Articles

<< < 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 > >> 

You may also start an advanced similarity search for this article.