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    <responseDate>2026-10-11T08:54:25Z</responseDate>
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    <identifier>10.57760/sciencedb.40084</identifier>
    <datestamp>2026-06-17T15:37:35Z</datestamp>
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<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:date>2026-06-17</dc:date>
  <dc:title>Determination of Available Boron in Soil by Electric Furnace Preboiling-Boiling Water Extraction-Inductively Coupled Plasma Optical Emission Spectrometry</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.40084</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>A simple pretreatment method for the extraction of available boron from soil was established, employing an electric furnace for preboiling and a temperature-controlled hot plate to maintain gentle boiling, withpolytetrafluoroethylene (PTFE) beakers used as the extraction vessels. By adopting the preboiling strategy with an electric furnace, the time required to reach and maintain a gentle boil was significantly shortened, which significantly improved the efficiency of large-scale sample analysis. Furthermore, replacing the traditionally expensive quartz triangular flasks with PTFE beakers not only greatly reduced the experimental costs but also simplified the operational procedures. The results showed that available boron exhibited a good linear relationship in the concentration range of 0~1.0 mg/L, with a correlation coefficient (R) of 0.999 9. The method detection limit was 0.000 9 mg/L, the relative error (RE) ranged from &amp;ndash;3.80% to &amp;ndash;2.57%, and the relative standard deviation (RSD) was between 4.99% and 6.63%. This method fully meets the requirements for the rapid determination of available boron in large batches of samples during soil surveys.</dc:description>
  <dc:subject>soil; available boron; ICP-OES; electric furnace pre-boiling</dc:subject>
  <dc:creator>Li Niu</dc:creator>
  <dc:creator>Zhong Lixiang</dc:creator>
  <dc:creator>Zhang Fan</dc:creator>
  <dc:creator>Chen Xiaoyue</dc:creator>
  <dc:creator>Shi Lijuan</dc:creator>
  <dc:creator>Zhang Yuyan</dc:creator>
  <dc:creator>Ma Ruiling</dc:creator>
  <dc:creator>Feng Ruixuan</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.16495/j.1006-3757.2026.03.006</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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