Institut für Kulturpflanzenwissenschaften

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Browsing Institut für Kulturpflanzenwissenschaften by Sustainable Development Goals "9"

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    Computing optimal allocation of trials to subregions in crop‐variety testing in case of correlated genotype effects
    (2025) Prus, Maryna; Prus, Maryna; Biostatistics Unit (340c), Institute of Crop Science, University of Hohenheim, Stuttgart, Germany
    The subject of this work is the allocation of trials to subregions in crop variety testing in the case of correlated genotype effects. A solution for computation of optimal allocations using the OptimalDesign package in R is proposed. The obtained optimal designs minimize linear criteria based on the mean squared error matrix of the best linear unbiased prediction of the genotype effects. The proposed computational approach allows for any kind of additional linear constraint on the designs. The results are illustrated by a real data example.
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    How many checks are needed per cycle in a plant breeding or variety testing programme?
    (2025) Piepho, Hans‐Peter; Laidig, Friedrich; Piepho, Hans‐Peter; Biostatistics Unit, Institute of Crop Science, University of Hohenheim, Stuttgart, Germany; Laidig, Friedrich; Biostatistics Unit, Institute of Crop Science, University of Hohenheim, Stuttgart, Germany
    Check varieties are used in plant breeding and variety testing for a number of reasons. One important use of checks is to provide connectivity between years, which facilitates comparison among genotypes of interest that are tested in different years. When long‐term data are available, such comparisons allow an assessment of realized genetic gain (RGG). Here, we consider the question of how many check varieties are needed per cycle for a reliable assessment of RGG. We propose an approach that makes use of variance component estimates for relevant random effects in a linear mixed model and plugs them into an analysis of dummy datasets set up to represent the design options being considered. Our results show that it is useful to employ a larger number of checks and to keep the replacement rate low. Furthermore, there is intercycle information to be recovered, especially when there are few checks and replacement rates are high, so modelling the cycle main effect as random pays off.
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    Impacts of different light spectra on CBD, CBDA and terpene concentrations in relation to the flower positions of different cannabis Sativa L. strains
    (2022) Reichel, Philipp; Munz, Sebastian; Hartung, Jens; Kotiranta, Stiina; Graeff-Hönninger, Simone
    Cannabis is one of the oldest cultivated plants, but plant breeding and cultivation are restricted by country-specific regulations. The plant has gained interest due to its medically important secondary metabolites, cannabinoids and terpenes. Besides biotic and abiotic stress factors, secondary metabolism can be manipulated by changing light quality and intensity. In this study, three morphologically different cannabis strains were grown in a greenhouse experiment under three different light spectra with three real light repetitions. The chosen light sources were as follows: a CHD Agro 400 ceramic metal-halide lamp with a sun-like broad spectrum and an R:FR ratio of 2.8, and two LED lamps, a Solray (SOL) and an AP67, with R:FR ratios of 13.49 and 4, respectively. The results of the study indicated that the considered light spectra significantly influenced CBDA and terpene concentrations in the plants. In addition to the different light spectra, the distributions of secondary metabolites were influenced by flower positions. The distributions varied between strains and indicated interactions between morphology and the chosen light spectra. Thus, the results demonstrate that secondary metabolism can be artificially manipulated by the choice of light spectrum, illuminant and intensity. Furthermore, the data imply that, besides the cannabis strain selected, flower position can have an impact on the medicinal potencies and concentrations of secondary metabolites.