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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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Inter and intra species competition between blackgrass-wheat in relation to herbicide-resistance and environmental conditions of Poland

Authors: Wenda-Piesik, Anna;

Inter and intra species competition between blackgrass-wheat in relation to herbicide-resistance and environmental conditions of Poland

Abstract

Two parameters, namely fresh plants' biomass and the number of seeds per plant, were measured for both winter wheat W and blackgrass B. The blackgrass competitive ratio (BCR) was calculated for the mixtures of susceptible blackgrass (BS) with resistant blackgrass (BR), representing the comparative growth based on plants' fresh biomass (BCRb) and the number of grains (BCRgn). The competitive ratio between wheat and blackgrass WBCR was calculated separately for the mixtures of W and BS, and W and BR. BCR and WBCR were calculated according to the formula described by Hoffman and Buller. The analysis was performed for the replacement series experiment, where RYW ��� relative yield of the W; RYB ��� relative yield of the B; p ��� the proportion of species; Wmix ��� a value of the W parameter analyzed for the mixture; Wmon ��� a value of the W parameter analyzed for the monoculture; Bmix ��� a value of the B parameter analyzed for the mixture; Bmon ��� a value of the B parameter analyzed for the monoculture; TRY ��� total relative yield. The RY values were measured for both W and B, and were averaged for single plant. Statistical analysis The biomass and grain yield or seed number, calculated into RY and TRY, were presented as graphs and fitted into one of the five competition models according to Radosevich [66]. The most explanatory models were determined by using the ��2 goodness-of-fit giving the best fit for all tested sites and biotypes. If the RY is a straight line, it denotes no competition; a convex line shows a benefit to species; a concave line represents a loss to species. If the TRY equals 1 (straight line), there is a competition for the same resources between both species/biotypes. If the TRY is greater than 1 (convex), there is no competition since the demand does not exceed the resources. If TRY is less than 1 (concave), an antagonism resulting in a mutual loss to species involved becomes apparent. ANOVA of two models was performed, i.e. the two-way model for the year �� site of plants to calculate the BCRgn and BCRb in R/S blackgrass and and three-way model for the year �� site �� biotype to calculate the WBCRgn and WBCRb in wheat/blackgrass. Data of indexes were sqrt transformed to the normal distribution. The post-hoc HSD Tukey test was used for the means separation. The r-Pearson correlation coefficient was calculated for relations between BCRgn / WBCRgn and BCRb /WBCRb, the relations between hydrothermal K coefficient and BCRgn /WBCRgn and BCRb / WBCRb and the relations between sand [%] and BCRgn /WBCRgn and BCRb / WBCRb. The exploration technique of the main components PCA (principle component analysis) has been used to explain the multidimensional diversity of W and environmental variables in terms of the first two components. Five biometrical parameters of W, i.e. mean length and fresh biomass of plant, number of seeds per plant, the yield of seeds per plant, and the TGW (1000 grain weight), and four environmental parameters, i.e. hydrothermal coefficient K and soil texture were analyzed using the PCA and CA (k-means procedure). The calculations were performed in the STATISTICA 13.0 program (TIBCO Software Inc).

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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