Matches in SemOpenAlex for { <https://semopenalex.org/work/W4304845716> ?p ?o ?g. }
- W4304845716 endingPage "25" @default.
- W4304845716 startingPage "10" @default.
- W4304845716 abstract "Abstract. Data from different multi-environmental trails (MET) were analysed, including different number of varieties, number of locations and different research periods. The first experiment (24 PhD) included 24 wheat varieties that were studied in five locations of the country over a period of four years (2009-2012). The second field experiment (40 ABC) consists of 40 new advanced wheat lines and cultivars, which were studied in three locations over a three-year period (2017-2019). The grain yield datasets from the two experiments were used to make a direct comparison of various statistical parameters to assess the genotype stability against the background of significant growing conditions. The study involves the use of several statistical packages that are specialized for this purpose. Based on the ranking assessment of the values of each statistical parameter, a critical analysis was made of its relationship with the yield, for each dataset separately. For this purpose, the possibilities of correlation, principal component and cluster analyses were used. Parameters for which information differs between datasets or between statistical packages are removed from the analysis list. The final set of 31 parameters was analysed according to the set goal, after a statistically justified possibility to merge the two datasets. Most of the rank parameters do not show correlation with grain yield. The units are the parameters, the correlation of which is either positive (Pi, Ysi, TOP, λ) or, respectively, negative (DJi, NP(1), CVi]). The analysis of the data through different statistical approaches shows that the parameters correspond to the dynamic concept of stability assessment. Only one of the parameters (θi) is related to static stability assessment. In the presence of many more effective than it, it should not be applied because it is an exception from the analysed group. The groups of parameters of the regression coefficient (bi), the deviation from the regression line (s2di), ecovalence (W2i) and the stability variance (σ²i), give objective information about the behaviour of the variety in environmental conditions and it is not influenced by software. Some of the non-parametric [S(i) NP(i)] assessment methods provide diametrically opposed information for stability because of differences arising from either the dataset or the software used. Suitable for stability assessment are non-parametric approaches - [S(1) and S(2)], which is fully confirmed by the three software packages. Each of the used software packages contains a set of parameters, the application of which as a set gives correct information about all aspects of the wheat stability" @default.
- W4304845716 created "2022-10-13" @default.
- W4304845716 creator A5078877500 @default.
- W4304845716 creator A5078936436 @default.
- W4304845716 creator A5081346032 @default.
- W4304845716 date "2022-09-01" @default.
- W4304845716 modified "2023-10-14" @default.
- W4304845716 title "Comparison of statistical parameters for estimating the yield and stability of winter common wheat" @default.
- W4304845716 cites W1483356436 @default.
- W4304845716 cites W1517215256 @default.
- W4304845716 cites W1587174555 @default.
- W4304845716 cites W1970729519 @default.
- W4304845716 cites W1978676827 @default.
- W4304845716 cites W1981957497 @default.
- W4304845716 cites W1999106449 @default.
- W4304845716 cites W2005648763 @default.
- W4304845716 cites W2010562603 @default.
- W4304845716 cites W2010684443 @default.
- W4304845716 cites W2016381774 @default.
- W4304845716 cites W2019218524 @default.
- W4304845716 cites W2025091503 @default.
- W4304845716 cites W2025950306 @default.
- W4304845716 cites W2026607452 @default.
- W4304845716 cites W2038681015 @default.
- W4304845716 cites W2041607989 @default.
- W4304845716 cites W2070773442 @default.
- W4304845716 cites W2074420045 @default.
- W4304845716 cites W2081282400 @default.
- W4304845716 cites W2087339712 @default.
- W4304845716 cites W2090327726 @default.
- W4304845716 cites W2101364071 @default.
- W4304845716 cites W2106228468 @default.
- W4304845716 cites W2113474175 @default.
- W4304845716 cites W2121225293 @default.
- W4304845716 cites W2123017873 @default.
- W4304845716 cites W2146879042 @default.
- W4304845716 cites W2152691531 @default.
- W4304845716 cites W2174345204 @default.
- W4304845716 cites W2337458438 @default.
- W4304845716 cites W2406695714 @default.
- W4304845716 cites W2509715244 @default.
- W4304845716 cites W2517144006 @default.
- W4304845716 cites W2903211240 @default.
- W4304845716 cites W2908988838 @default.
- W4304845716 cites W2919754206 @default.
- W4304845716 cites W2978385913 @default.
- W4304845716 cites W2989513338 @default.
- W4304845716 cites W2998260806 @default.
- W4304845716 cites W3009641619 @default.
- W4304845716 cites W3022186846 @default.
- W4304845716 cites W3031211396 @default.
- W4304845716 cites W3033701474 @default.
- W4304845716 cites W3037643524 @default.
- W4304845716 cites W3040893244 @default.
- W4304845716 cites W3089067860 @default.
- W4304845716 cites W3111911437 @default.
- W4304845716 cites W3144841351 @default.
- W4304845716 cites W3200137195 @default.
- W4304845716 cites W4210704495 @default.
- W4304845716 cites W4232239500 @default.
- W4304845716 cites W4238586206 @default.
- W4304845716 cites W43912433 @default.
- W4304845716 doi "https://doi.org/10.15547/ast.2022.03.032" @default.
- W4304845716 hasPublicationYear "2022" @default.
- W4304845716 type Work @default.
- W4304845716 citedByCount "2" @default.
- W4304845716 countsByYear W43048457162023 @default.
- W4304845716 crossrefType "journal-article" @default.
- W4304845716 hasAuthorship W4304845716A5078877500 @default.
- W4304845716 hasAuthorship W4304845716A5078936436 @default.
- W4304845716 hasAuthorship W4304845716A5081346032 @default.
- W4304845716 hasBestOaLocation W43048457161 @default.
- W4304845716 hasConcept C101601086 @default.
- W4304845716 hasConcept C105795698 @default.
- W4304845716 hasConcept C112972136 @default.
- W4304845716 hasConcept C119857082 @default.
- W4304845716 hasConcept C197129107 @default.
- W4304845716 hasConcept C23123220 @default.
- W4304845716 hasConcept C27438332 @default.
- W4304845716 hasConcept C2986587452 @default.
- W4304845716 hasConcept C2992211155 @default.
- W4304845716 hasConcept C33923547 @default.
- W4304845716 hasConcept C41008148 @default.
- W4304845716 hasConcept C6557445 @default.
- W4304845716 hasConcept C86803240 @default.
- W4304845716 hasConceptScore W4304845716C101601086 @default.
- W4304845716 hasConceptScore W4304845716C105795698 @default.
- W4304845716 hasConceptScore W4304845716C112972136 @default.
- W4304845716 hasConceptScore W4304845716C119857082 @default.
- W4304845716 hasConceptScore W4304845716C197129107 @default.
- W4304845716 hasConceptScore W4304845716C23123220 @default.
- W4304845716 hasConceptScore W4304845716C27438332 @default.
- W4304845716 hasConceptScore W4304845716C2986587452 @default.
- W4304845716 hasConceptScore W4304845716C2992211155 @default.
- W4304845716 hasConceptScore W4304845716C33923547 @default.
- W4304845716 hasConceptScore W4304845716C41008148 @default.
- W4304845716 hasConceptScore W4304845716C6557445 @default.
- W4304845716 hasConceptScore W4304845716C86803240 @default.