Showing 21 - 40 results of 163 for search '"Multivariate statistics"', query time: 0.06s Refine Results
  1. 21
  2. 22
  3. 23

    Investigating the Impact of Anthropogenic and Natural Sources of Pollution on Quality of Water in Upper Indus Basin (UIB) by Using Multivariate Statistical Analysis by Mansoor A. Baluch, Hashim Nisar Hashmi

    Published 2019-01-01
    “…In order to analyze the similarities and dissimilarities for identifying the spatial variations in water quality of the Indus River and sources of contamination, multivariate statistical analysis, i.e., principle component analysis (PCA), cluster analysis, and descriptive analysis, was done. …”
    Get full text
    Article
  4. 24
  5. 25

    Screening of Anti-Inflammatory Components of Qin Jin Hua Tan Tang by a Multivariate Statistical Analysis Approach for Spectrum-Effect Relationships by Feipeng Duan, Yisheng Li, Meizhen Zhao, Tianyong Hu, Xinquan Pan, Yue Feng, Fang Ma, Shuqi Qiu, Yiqing Zheng

    Published 2021-01-01
    “…Our study aimed to screen the active anti-inflammatory components of QJHTT using a multivariate statistical analysis approach for spectrum-effect relationships. …”
    Get full text
    Article
  6. 26

    Multivariate Statistical Analysis Reveals the Heterogeneity of Lacustrine Tight Oil Accumulation in the Middle Permian Jimusar Sag, Junggar Basin, NW China by Yuce Wang, Jian Cao, Keyu Tao, Xiuwei Gao, Erting Li, Chunhua Shi

    Published 2020-01-01
    “…Here, we attempted multivariate statistical analysis to reveal the heterogeneity based on a case study in the lacustrine tight oil accumulation in the middle Permian Lucaogou Formation of the Jimusar sag, Junggar Basin, NW China. …”
    Get full text
    Article
  7. 27
  8. 28
  9. 29
  10. 30

    Comparing Relationships among Yield and Its Related Traits in Mycorrhizal and Nonmycorrhizal Inoculated Wheat Cultivars under Different Water Regimes Using Multivariate Statistics by Armin Saed-Moucheshi, Mohammad Pessarakli, Bahram Heidari

    Published 2013-01-01
    “…Multivariate statistical techniques were used to compare the relationship between yield and its related traits under noninoculated and inoculated cultivars with mycorrhizal fungus (Glomus intraradices); each one consisted of three wheat cultivars and four water regimes. …”
    Get full text
    Article
  11. 31

    Differentiation and characterization of volatile compounds in five common milk powders using HS-GC-IMS, HS-SPME-GC–MS, and multivariate statistical approaches by Yaxi Zhou, Diandian Wang, Jian Zhao, Yu Guo, Wenjie Yan

    Published 2025-01-01
    “…This study analysed and identified the flavor characteristics of five common types of milk powders in China, including yak milk powder, donkey milk powder, camel milk powder, goat milk powder, and cow milk powder, using Headspace-Gas Chromatography-Ion Mobility Spectrometry (HS-GC-IMS), Headspace Solid-Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC–MS), and multivariate statistical analysis. Results identified 55 and 86 volatile compounds via HS-GC-IMS and HS-SPME-GC–MS, respectively, revealing significant differences between milk powders. …”
    Get full text
    Article
  12. 32
  13. 33
  14. 34
  15. 35

    Water–rock interaction in the geothermal systems related to post-collision zone volcanism: A case study based on multivariate statistical analysis from the Kavak geothermal field (Konya, Turkey) by Gündüz, Mesut, Bozdağ, Ayla, Bayram, Ali Ferat, Bozdağ, Ali, Asan, Kürşad, Sardini, Paul

    Published 2023-12-01
    “…The chemical relationship between the KGF and high-K ErAVC is clearly seen in the cation-based diagrams. Multivariate statistical analysis confirms that first type and second type thermal waters identified based on their hydrochemistry formed two separate statistical groups, and suggests that the chemistry of the KGF waters was mainly controlled by the composition of the ErAVC rather than those of the basement metamorphic rocks as a result of water–rock interaction.…”
    Get full text
    Article
  16. 36
  17. 37
  18. 38
  19. 39
  20. 40