Resin-extractable phosphate (PO4-P) is a widespread sink-based measure of soil bioavailable phosphorus (P) used in biogeochemistry and soil fertility. However, acid elution of P may hydrolyze organic P and thus compromise measurement of PO4-P. We evaluated sodium bicarbonate (NaHCO3) as an alternative to sulfuric acid (H2SO4) for PO4-P elution. We found 0.5 M NaHCO3 achieved ≈100% PO4-P recovery at higher initial PO4-P concentrations (20 and 30 mg P/L), compared to 95%–98% with 0.25 M H2SO4. For 24 soil samples representing all 12 USDA soil orders, NaHCO3 elution yielded 9.6% higher resin extractable PO4-P than H2SO4. Additionally, the PO4-P remaining in water extract after resin removal (H2Ore-PO4) was consistently quantifiable, and constituted up to 46% of total extractable PO4-P. These results demonstrate (i) NaHCO3 is a more effective eluent for resin extractable P than H2SO4, and (ii) H2Ore-PO4 should be quantified when measuring resin extractable P.
树脂可提取磷(PO4-P)是一种广泛应用于生物地球化学和土壤肥力的土壤生物有效磷(P)测量方法。然而,磷的酸洗脱可能会水解有机磷,从而影响PO4-P的测量。我们评估了碳酸氢钠(NaHCO3)作为硫酸(H2SO4)的替代品来处理PO4-P。我们发现,在较高的初始PO4-P浓度(20和30 mg P/L)下,0.5 M NaHCO3的PO4-P回收率约为100%,而0.25 M H2SO4的回收率为95%-98%。对于代表所有12个USDA土壤级的24个土壤样品,NaHCO3洗脱的树脂可提取PO4-P比H2SO4高9.6%。此外,树脂去除后水提物中剩余的PO4-P (H2Ore-PO4)始终是可量化的,占可提取PO4-P总量的46%。这些结果表明(1)NaHCO3比H2SO4对树脂可提取P更有效;(2)在测定树脂可提取P时,应将H2Ore-PO4定量。
{"title":"Phosphate elution from anion-exchange membranes in soil analysis","authors":"Suwei Xu, Andrew J. Margenot","doi":"10.1002/ael2.70012","DOIUrl":"10.1002/ael2.70012","url":null,"abstract":"<p>Resin-extractable phosphate (PO<sub>4</sub>-P) is a widespread sink-based measure of soil bioavailable phosphorus (P) used in biogeochemistry and soil fertility. However, acid elution of P may hydrolyze organic P and thus compromise measurement of PO<sub>4</sub>-P. We evaluated sodium bicarbonate (NaHCO<sub>3</sub>) as an alternative to sulfuric acid (H<sub>2</sub>SO<sub>4</sub>) for PO<sub>4</sub>-P elution. We found 0.5 M NaHCO<sub>3</sub> achieved ≈100% PO<sub>4</sub>-P recovery at higher initial PO<sub>4</sub>-P concentrations (20 and 30 mg P/L), compared to 95%–98% with 0.25 M H<sub>2</sub>SO<sub>4</sub>. For 24 soil samples representing all 12 USDA soil orders, NaHCO<sub>3</sub> elution yielded 9.6% higher resin extractable PO<sub>4</sub>-P than H<sub>2</sub>SO<sub>4</sub>. Additionally, the PO<sub>4</sub>-P remaining in water extract after resin removal (H<sub>2</sub>O<sub>re</sub>-PO<sub>4</sub>) was consistently quantifiable, and constituted up to 46% of total extractable PO<sub>4</sub>-P. These results demonstrate (i) NaHCO<sub>3</sub> is a more effective eluent for resin extractable P than H<sub>2</sub>SO<sub>4</sub>, and (ii) H<sub>2</sub>O<sub>re</sub>-PO<sub>4</sub> should be quantified when measuring resin extractable P.</p>","PeriodicalId":48502,"journal":{"name":"Agricultural & Environmental Letters","volume":"10 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ael2.70012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tulsi P. Kharel, Heather L. Tyler, Partson Mubvumba, Yanbo Huang, Ammar B. Bhandari, Reginald S. Fletcher, Saseendran Anapalli, Deepak R. Joshi, Alemu Mengistu, Girma Birru, Kabindra Adhikari, Madhav Dhakal, Mahesh L. Maskey, Krishna N. Reddy, David E. Clay
This study aimed to estimate mixed-species cover crop (CC) biomass and nutrient contents using remote sensing, as ground-based measurements are time-consuming and costly. Eleven CC treatments with varying grass-legume proportions (GLP) were sampled, and nutrient contents were determined along with multispectral imagery captured during the first and fourth weeks of March and the fourth week of April 2023. Biomass N (R2 = 0.46–0.60) and K% (R2 = 0.41—0.71) decreased with increasing GLP. The chlorophyll absorption ratio index and the normalized difference vegetation index closely followed the biomass nutrients N, P, and K combined yield (Bio_NPK) trend. Machine learning algorithms random forest (RF) and partial least square (PLS) regression were better for biomass (R2 = 0.74 with RF) and N% (R2 = 0.72 with PLS) prediction compared to the Bio_NPK prediction. These results are crucial for scientists to devise appropriate analysis approaches for estimating the benefits of mixed-species CC.
{"title":"Machine learning on multi-spectral imagery to estimate nutrient yield of mixed-species cover crops","authors":"Tulsi P. Kharel, Heather L. Tyler, Partson Mubvumba, Yanbo Huang, Ammar B. Bhandari, Reginald S. Fletcher, Saseendran Anapalli, Deepak R. Joshi, Alemu Mengistu, Girma Birru, Kabindra Adhikari, Madhav Dhakal, Mahesh L. Maskey, Krishna N. Reddy, David E. Clay","doi":"10.1002/ael2.70009","DOIUrl":"10.1002/ael2.70009","url":null,"abstract":"<p>This study aimed to estimate mixed-species cover crop (CC) biomass and nutrient contents using remote sensing, as ground-based measurements are time-consuming and costly. Eleven CC treatments with varying grass-legume proportions (GLP) were sampled, and nutrient contents were determined along with multispectral imagery captured during the first and fourth weeks of March and the fourth week of April 2023. Biomass N (<i>R</i><sup>2</sup> = 0.46–0.60) and K% (<i>R</i><sup>2</sup> = 0.41—0.71) decreased with increasing GLP. The chlorophyll absorption ratio index and the normalized difference vegetation index closely followed the biomass nutrients N, P, and K combined yield (Bio_NPK) trend. Machine learning algorithms random forest (RF) and partial least square (PLS) regression were better for biomass (<i>R</i><sup>2 </sup>= 0.74 with RF) and N% (<i>R</i><sup>2 </sup>= 0.72 with PLS) prediction compared to the Bio_NPK prediction. These results are crucial for scientists to devise appropriate analysis approaches for estimating the benefits of mixed-species CC.</p>","PeriodicalId":48502,"journal":{"name":"Agricultural & Environmental Letters","volume":"10 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ael2.70009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143115669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}