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    Wyświetlanie 1-2 z 2
    Tytuł:
    Spatial variability and efficiency of treatment mean comparisons in an experiment with fodder pea using modern statistical methods.
    Autorzy:
    Gołaszewski, Janusz
    Powiązania:
    https://bibliotekanauki.pl/articles/2198840.pdf
    Data publikacji:
    2001-06-21
    Wydawca:
    Instytut Hodowli i Aklimatyzacji Roślin
    Tematy:
    spatial variability
    ANOVA
    ANCOVA
    NNA
    kriging
    relative efficiency
    Opis:
    It is typical of breeding experimentation to conduct experiments on large breeding material tested on small plots with a limited number of replications. Under such conditions, observations made on adjacent plots are biased by the effect of autocorrelation and fertility trends. The actual treatment effects can be masked and the capability of the breeder to detect true treatment differences is impaired. This paper deals with the problem of the estimation of effects of spatial variability and their impact on the efficiency of treatment comparisons. The considerations are based on the results from a breeding experiment with 25 treatments of fodder pea arranged according to the partially balanced incomplete block design (IBD) with 4 replications. Plant height and seed yield were analysed with the conventional statistical method ANOVA, the nearest neighbour analysis (NNA) and kriging. Eventually, the efficiency of the neoclassical methods relative to the completely randomised design (CRD) and randomised block design (RBD) was calculated. The estimation of the treatment effect on plant height was accomplished most efficiently with the NNA, whereas the efficiency of the alternative methods in the estimation of seed yield was comparable to the efficiency of the RBD.
    Źródło:
    Plant Breeding and Seed Science; 2001, 45, 1; 87-98
    1429-3862
    2083-599X
    Pojawia się w:
    Plant Breeding and Seed Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Yield component analysis with SYCA and TDP in fodder pea.
    Autorzy:
    Gołaszewski, Janusz
    Idźkowska, Maria
    Milewska, Jadwiga
    Koczowska, Irena
    Powiązania:
    https://bibliotekanauki.pl/articles/2198817.pdf
    Data publikacji:
    2001-12-20
    Wydawca:
    Instytut Hodowli i Aklimatyzacji Roślin
    Tematy:
    yield component analysis
    sequential yield component analysis
    SYCA
    two-dimensional partitioning
    TDP
    fodder pea
    Opis:
    The paper presents some theoretical assumptions of the SYCA (Sequential Yield Component Analysis) and the application of SYCA followed by TDP (Two-dimensional Partitioning) to analysis of the data from a plant breeding experiment with fodder pea. Partially balanced incomplete block design with 25 morphologically different breeding forms in 4 replications was applied. In both methods of data analysis plant height was the first trait in a sequence of independent traits, followed by different traits depending on the method.The results of the analyses proved that in a morphologically highly differentiated population of fodder pea the contribution of plant height to the yield variability is reduced, with plant height to the first pod being one of the traits that have a significant effect on yield. According to the SYCA method, when the pea forms were divided into groups of plants similar in height, the effect of plant height as the first yield component was high and significant. Generally, the higher were the plants in the groups, the smaller was the share of the trait in the yield, although still relatively high and significant. For the purpose of yield component analysis in pea it is recommendable to divide the breeding material to groups of plants of a similar height.As for the other yield components, the highest contribution into the final yield was attributed to the number of nodes with pods by plant height and seed weight by number of seeds calculated according to the SYCA and the number of nodes with pods calculated according to the TDP method, respectively.The authors, who have used the two yield component analyses for several years, have gained enough experience to claim that the two methods can become effective statistical tools for the elaboration of yield components. Moreover, they can be useful not only in plant breeding studies but also in many other types of agricultural experimentation.
    Źródło:
    Plant Breeding and Seed Science; 2001, 45, 2; 77-85
    1429-3862
    2083-599X
    Pojawia się w:
    Plant Breeding and Seed Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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