{"id":42352,"date":"2023-07-06T20:42:13","date_gmt":"2023-07-06T20:42:13","guid":{"rendered":"https:\/\/agsci.colostate.edu\/soilinnovationlab\/?page_id=42352"},"modified":"2023-08-14T19:55:19","modified_gmt":"2023-08-14T19:55:19","slug":"evaluating-and-improving-accuracy-and-throughput-of-approaches-in-soil-organic-matter-studies","status":"publish","type":"page","link":"https:\/\/agsci.colostate.edu\/soilinnovationlab\/current-research-themes\/evaluating-and-improving-accuracy-and-throughput-of-approaches-in-soil-organic-matter-studies\/","title":{"rendered":"Evaluating and Improving Accuracy and Throughput of Approaches in Soil Organic Matter Studies"},"content":{"rendered":"

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Evaluating and Improving Accuracy and Throughput of Approaches in Soil Organic Matter Studies<\/h1>\n

Accurate quantification and mechanistic understanding of soil organic matter is built on robust, trustworthy measurements. Currently these use combinations of simple and sophisticated techniques and often rely on labor-intensive protocols, limiting large scale soil organic matter analysis which are often too costly and time consuming. Reliable data-driven decision-making calls for reducing time-per-soil sample analyses while preserving accuracy of determinations. <\/span>We develop and use robust soil sampling and processing protocols, soil organic matter physical fractionation, stable isotope labeling, Fourie Transformed InfraRed (FTIR) spectroscopy, and large data synthesis approaches to improve the accuracy and throughput of soil organic matter quantification methods and to advance the understanding of the formation and persistence of soil organic matter in a variety of terrestrial ecosystems. Additionally, we engage with trusted companies and offer our expertise to test new instruments, as for example for Studying Plant and Soil Dynamics with CO2 Isotope Measurements<\/a><\/p>\n

[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Evaluating and Improving Accuracy and Throughput of Approaches in Soil Organic Matter Studies” module_id=”evaluating” _builder_version=”4.20.0″ _module_preset=”default” background_color=”#F1F1F1″ locked=”off” collapsed=”off” global_colors_info=”{}”][et_pb_row column_structure=”1_3,1_3,1_3″ _builder_version=”4.21.0″ _module_preset=”default” hover_enabled=”0″ global_colors_info=”{}” use_custom_gutter=”on” gutter_width=”2″ sticky_enabled=”0″][et_pb_column type=”1_3″ _builder_version=”4.20.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_image _builder_version=”4.21.0″ _module_preset=”default” alt=”FRAN automatic instrument that can isolate the light particulate organic matter fraction” title_text=”soil-innovation-lab-fran” src=”https:\/\/agsci.colostate.edu\/soilinnovationlab\/wp-content\/uploads\/sites\/155\/2023\/07\/soil-innovation-lab-fran.jpeg” border_width_top=”4px” border_color_top=”#F15625″ hover_enabled=”0″ sticky_enabled=”0″][\/et_pb_image][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.20.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.20.0″ _module_preset=”default” header_2_font_size=”26.1px” global_colors_info=”{}” header_2_line_height=”1.5em” text_line_height=”1.5em”]<\/p>\n

Major Contribution and Highlights<\/h2>\n
    \n
  1. Design and Operation of a Continuous 13<\/sup>C and 15<\/sup>N Labeling Chamber<\/a><\/li>\n
  2. Physical fractionation techniques<\/a><\/li>\n
  3. Using Artificial Intelligence to increase throughput of POM and MAOM<\/a><\/li>\n
  4. Using Mid-Infrared Spectroscopy to Optimize Throughput and Costs of Soil Organic Carbon and Nitrogen Estimates<\/a><\/li>\n<\/ol>\n

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    Future Directions and Goals<\/h2>\n

    We are working to:<\/p>\n

      \n
    1. \n
        \n
      1. Optimize preprocessing of soil samples for accuracy and throughput of soil carbon quantification.<\/li>\n
      2. Inform the design and improve the performance of soil organic matter physical fractionation schemes,<\/li>\n
      3. Increase throughput of soil organic matter fractions C and N measurement.<\/li>\n
      4. Develop new applications for stable isotope labeling.<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

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