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sas/stat® v 9.1 statistical package  (SAS institute)


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    SAS institute sas/stat® v 9.1 statistical package
    Sas/Stat® V 9.1 Statistical Package, supplied by SAS institute, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/sas-stat+statistical+package/sas+version+9+4/pm39128999-100-12-13
    Average 90 stars, based on 1 article reviews
    sas/stat® v 9.1 statistical package - by Bioz Stars, 2026-10
    90/100 stars

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    Article Title: Pasta-Making Quality QTLome From Mediterranean Durum Wheat Landraces
    Article Snippet: Restricted maximum likelihood was used to estimate the variance components and to produce the best linear unbiased predictors (BLUPs) for the quality traits of each cultivar and year with the SAS-STAT statistical package (SAS Institute Inc, Cary, NC, USA).

    Article Title: Identification of QTL hotspots affecting agronomic traits and high-throughput vegetation indices in rainfed wheat
    Article Snippet: Restricted maximum likelihood (REML) was used to estimate the variance components and to produce the best linear unbiased predictors (BLUPs) for agronomic traits and VIs, following the MIXED procedure of the SAS-STAT statistical package (SAS Institute Inc., Cary, NC, USA).

    Article Title: Pasta-Making Quality QTLome From Mediterranean Durum Wheat Landraces
    Article Snippet: Combined ANOVAs were performed across experiments through the GLM procedure of the SAS-STAT statistical package (SAS Institute Inc, Cary, NC, USA), considering the cultivar and the year as random effects, and the year × cultivar interaction as the error term.

    Article Title: Exploring the Genetic Architecture of Root-Related Traits in Mediterranean Bread Wheat Landraces by Genome-Wide Association Analysis
    Article Snippet: Restricted maximum likelihood was used to estimate the variance components and to produce the best linear unbiased predictors (BLUPs) for the traits of each cultivar and year with the SAS-STAT statistical package (SAS Institute Inc, Cary, NC, USA).

    Article Title: Identification of Quantitative Trait Loci Hotspots Affecting Agronomic Traits and High-Throughput Vegetation Indices in Rainfed Wheat.
    Article Snippet: Phenotypic data were fitted to a linear mixed model considering the check cultivars as the fixed effect, and the row and column number and accessions as random in the model for each environment following the MIXED procedure of the SAS-STAT statistical package (SAS Institute Inc., Cary, NC, USA). y = xβ + zγ + ε where β is an unknown vector of fixed-effects parameters with known designmatrix x, γ is an unknown vector of random-effects parameters with known design matrix z, and ε is an unknown random error vector whose elements are no longer required to be independent and homogeneous.

    Article Title: Discovering Loci for Breeding Prospective and Phenology in Wheat Mediterranean Landraces by Environmental and eigenGWAS.
    Article Snippet: Phenotypic data were fitted to a linear mixed model considering the check cultivars as the fixed effect, and the row and column number and accessions as random in the model for each environment following the MIXED procedure of the SAS-STAT statistical package (SAS Institute Inc., Cary, NC, USA) y = Xβ + Zγ + ε (1) Int.

    Article Title: Using Unmanned Aerial Vehicle and Ground-Based RGB Indices to Assess Agronomic Performance of Wheat Landraces and Cultivars in a Mediterranean-Type Environment
    Article Snippet: Restricted maximum likelihood (REML) was used to estimate the variance components and produce the best linear unbiased predictors (BLUPs) for agronomical traits, VIs, and RGB indices, following the MIXED procedure of the SAS-STAT statistical package (SAS Institute, Inc., Cary, NC, USA).

    Article Title: Inheritance of Resistance to Gummy Stem Blight in Watermelon
    Article Snippet: We performed segregation analysis and the chi-square goodness-of-fit tests (P < 0.05) for each F2 and BC1Pr progeny with the SAS-STAT statistical package (SAS Institute, Cary, NC) and the SASGENE 1.2 program (Liu et al., 1997).



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