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Showing 81 - 100 results of 222 for search 'farm is (((((remote. OR involves.) OR involves.) OR evolvedssdddss.) OR involved.) OR removed.)*', query time: 0.11s Refine Results
  1. 81

    Image 5_Swine influenza surveillance in Italy uncovers regional and farm-based genetic clustering.tiff by L. Cavicchio (21751946)

    Published 2025
    “…</p>Material and methods<p>Passive surveillance, conducted from 2013 to 2022, involved 253 farms located in three regions, collecting over 3,000 samples that were tested for swIAV. …”
  2. 82

    Image 3_Swine influenza surveillance in Italy uncovers regional and farm-based genetic clustering.tiff by L. Cavicchio (21751946)

    Published 2025
    “…</p>Material and methods<p>Passive surveillance, conducted from 2013 to 2022, involved 253 farms located in three regions, collecting over 3,000 samples that were tested for swIAV. …”
  3. 83

    Image 6_Swine influenza surveillance in Italy uncovers regional and farm-based genetic clustering.tiff by L. Cavicchio (21751946)

    Published 2025
    “…</p>Material and methods<p>Passive surveillance, conducted from 2013 to 2022, involved 253 farms located in three regions, collecting over 3,000 samples that were tested for swIAV. …”
  4. 84

    Multiple seasons spatialy distributed maize yield and soil properties data for crop modeling applications in precision agriculture by Simphiwe Maseko (21577652)

    Published 2025
    “…<p dir="ltr">This data was collected from a data-intensive farm management (DIFM) maize trial in Hennenman, Free State South Africa, from a private farm that allowed the research to be done and data used for academic purposes. …”
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  9. 89

    Data Sheet 1_Swine influenza surveillance in Italy uncovers regional and farm-based genetic clustering.pdf by L. Cavicchio (21751946)

    Published 2025
    “…</p>Material and methods<p>Passive surveillance, conducted from 2013 to 2022, involved 253 farms located in three regions, collecting over 3,000 samples that were tested for swIAV. …”
  10. 90

    Data Sheet 1_Digital technology adoption and farm household income in ethnic minority areas: evidence from Xinjiang, China.docx by Yan Tang (195081)

    Published 2025
    “…Specifically, digital adoption reduces reliance on traditional labor inputs in agricultural production, boosting agricultural incomes while increasing the likelihood of non-farm employment, thereby promoting income diversification. …”
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