The Swedish EPA (Naturv&#229;rdsverket) (agreement 2208-13-001) and Centre for Chemical Pesticides (CKB) are gratefully acknowledged for funding this project. We thank M&#228;rit Peterson, Henrik Jernstedt, Emma Gurnell and Elin Paulsson at the OMK-lab, SLU, for skillful assistance with analytical support and supply of pesticide standards.

1.被动采样设计和准备<ol><li> 硅橡胶板 <ol><li>切断的硅橡胶片材英寸（600 mm×600毫米，厚0.5毫米）到使用不锈钢刀和使用不锈钢盲铆钉连接它们（3.2毫米×10毫米为2.5毫米×600毫米和2.5毫米×314毫米条纹）用铆钉枪，以获得2.5毫米×914毫米（表面积=457厘米2，吸着剂的质量= 15.6Hz克，体积共取样的条带大小=22.9厘米3）。 </li></ol></li><li>放置硅橡胶在Soxhlet装置的提取室。加入50mL EA在提取室和添加250毫升EA和在500毫升圆底烧瓶三种馏程石。 <ol><li>提取室与瓶烧瓶和冷凝器连接。清洗由索氏提取96小时的硅酮橡胶在约80℃，并在温和的氮气随后干燥。 </li></ol></li><li>附加硅橡胶STRI通过包装杆围绕硅橡胶条在保持器（ 图1）PE到不锈钢蜘蛛样品架。硅橡胶带的两端连接到一杆使用电缆扎带持有人。 </li></ol><img alt="图1" src="/files/ftp_upload/54053/54053fig1.jpg" /> 图1.原理硅橡胶。被动采样原理图显示了硅橡胶条纹在不锈钢蜘蛛样品架用从顶部和B）侧视附件）硅橡胶。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54053/54053fig1large.jpg" target="_blank">请点击此处查看大图这个数字。</a> <ol start="2"><li> POCIS-A和POCIS-B <ol><li>对于POCIS-A，将通过9.0厘米SQUAR 29.0厘米之间220毫克HLB松散的吸着（表面积= 1.78×10 6 平方厘米）的È聚醚砜（PES）膜（ 图2）。 </li><li>对于POCIS-B，放置220毫克的吸附剂混合物的（ 即 ，羟基化的聚苯乙烯-二乙烯基苯树脂（80％）和分散在苯乙烯二乙烯基苯共聚物的碳质吸附剂（20％））（表面积= 2.82×10 6 cm 2）的两者之间的PES膜（ 图2）。 </li><li>压缩吸附剂和手动两个不锈钢环之间有两个PES（内直径= 5.4Hz厘米）和将其固定在不锈钢样品架（ 图2）。 </li></ol></li></ol><img alt="图2" src="/files/ftp_upload/54053/54053fig2.jpg" /> 图2.原理被动采样磁盘。被动采样原理图POCIS A，POCIS B，SDB-RPS盘并呈现出 ）被动取样器的装配采用不锈钢戒指，聚醚砜-C 18盘（PES）MEMBRANES和接收阶段，和B）在不锈钢样品架装配。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54053/54053fig2large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <ol start="3"><li> SDB-RPS盘和C盘18 <ol><li>放置之间的SDB-RPS（表面积= 35 平方厘米，吸附剂质量= 0.34克，体积= 1.7 毫升 ）和C 18的磁盘（表面积= 35 平方厘米，吸附剂质量= 0.58克，体积= 1.7 毫升 ）两个PE膜（ 图2）。压缩磁盘和手动两个不锈钢环之间有两个PES（内直径= 5.4Hz厘米），将其固定在不锈钢样品架（ 图2）。 </li></ol></li></ol> 2.实验室摄取实验注:进行实验室实验摄取定量表征摄取ķinetics 124个人农药控制的条件下五种不同的被动采样装置。 <ol><li>进行矩形玻璃容器摄取研究（各〜95 L）:坦克1）硅橡胶（N = 16），罐2）POCIS-A（N = 16），POCIS-B（N = 16），和坦克3 ）SDB-RPS盘（N = 16），C 18盘（N = 16）。填写自然水变成了三辆坦克。 </li><li>在恒定水温度（〜20℃），并使用连接于在每一侧的壁两个电动泵湍流水条件（至10厘米秒-1）下进行所有的实验。在黑暗中进行的实验中，以尽量减少光降解​​的效果。 </li><li>穗各玻璃容器与含有用玻璃注射器124杀虫剂杀虫剂标准混合物（三≈400纳克L -1在水箱个别农药）。从储罐手动取出被动采样，在时间间隔5中，11，20，和26ðAYS，确定杀虫剂的采样率。 </li><li>通过在第0天，5，11，20收集100ml水中的样品监测在每个箱中的农药的浓度，和26的水样品的分析如别处21所述进行。 <ol><li>在质量控制方面，在第0天暴露空白样品到室内空气中1小时，然后保存并把它们当作真正的样品。存储所有提取物以及在-18℃直至进一步分析从罐中收集的100ml水中的样品。 </li></ol></li></ol> 3.样品提取<ol><li> 硅橡胶 <ol><li>之前提取，干燥下高纯氮气流的硅橡胶条。 </li><li>气相色谱-质谱（GC-MS）分析，进行使用索氏提取22的固-液萃取。 <ol><li>放置硅橡胶入索氏提取器中。添加250毫升PE / ACE（50/50，体积/体积）和3博伊凌石成圆底烧瓶中。 </li><li>用100μl的尖峰的硅橡胶是用玻璃注射器混合物（C = 5纳克毫升-1）。加入50mL的PE / ACE（50/50，体积/体积）到索氏提取器中。交换机上的加热器和运行索氏提取19小时，然后关闭加热器。 </li><li>通过旋转蒸发然后温和氮气放空到1ml浓缩提取物。通过氮放空到1ml过程中加入三次1毫升CH / ACE（90/10，体积/体积）交换到CH / ACE（90/10，体积/体积）的溶剂。 </li></ol></li><li>用于液相色谱-串联质谱（LC-MS / MS）分析，进行使用索氏提取22的提取。 <ol><li>放置硅橡胶入索氏提取器中。加入250毫升甲醇和3沸腾的石头放入圆底烧瓶和50毫升甲醇成索氏提取器。穗硅橡胶用100μl的IS混合物（C = 5纳克毫升-1）使用玻璃SYR英格。 </li><li>交换机上的加热器和运行索氏提取19小时，然后关闭加热器。通过旋转蒸发然后温和氮气放空到1ml浓缩提取物。通过氮放空至1ml中加入1ml乙腈交换溶剂，乙腈。 </li></ol></li></ol></li><li> POCIS-A和POCIS-B <ol><li>小心地打开POCIS采样，并使用漏斗用超纯水的吸附剂转移到含有两个聚乙烯（PE）玻璃料一个预清洁空聚丙烯固相萃取（SPE）柱（6毫升）中。通过真空干燥吸附剂以除去水。记录空和填充SPE柱的重量来控制吸附剂材料的重量。请注意，不同的墨盒被用于GC-MS和LC-MS / MS分析。 </li><li>之前洗脱，使用玻璃注射器尖峰用100μl的吸附剂IS混合物（C = 5纳克毫升-1）。用5洗脱POCIS-A和POCIS-B吸附剂毫升EA为GC-MS 22。 <ol><li>通过温和氮气放空浓缩萃取液至1ml。通过氮放空到1ml过程中加入三次1毫升CH / ACE（90/10，体积/体积）交换到CH / ACE（90/10，体积/体积）的溶剂。 </li></ol></li><li>用1.5ml的MeOH中，随后用8ml DCM / MeOH中洗脱POCIS-A和POCIS-B柱（80/20，体积/体积）用于LC-MS / MS分析22。通过温和氮气放空浓缩萃取液至1ml。通过氮放空至1ml中加入1ml乙腈交换溶剂，乙腈。 </li></ol></li><li> SDB-RPS和C 18盘 <ol><li>转移SDB-RPS和C 18盘的各个磁盘到一个玻璃烧杯中，并在氮气干燥。用5毫升的EA尖峰用100μl的磁盘IS混合物（C = 5纳克毫升-1）用玻璃注射器和超声处理他们两次在室温下的玻璃烧杯中，首先进行10分钟，然后用3毫升的EA 10分钟。 </li><li>传输博次萃取到一个玻璃管中，将它们集中至2ml通过温和氮气吹下来，然后将它们分成两个1毫升级分（用于GC-MS和LC-MS / MS分析，分别）。 </li><li>通过温和氮气放空浓缩萃取液至0.5 ml和交换溶剂，CH / ACE（90/10，体积/体积）用于GC-MS分析22。通过温和氮气放空浓缩萃取液至0.5 ml和交换溶剂，乙腈用于LC-MS / MS分析22。 </li></ol></li></ol> 4.水样<ol><li>穗用100μl的20毫升水样品IS混合物用玻璃注射器（C = 5纳克毫升-1），加入3毫升DCM中，涡旋3分钟，倾倒到一个相分离器用于GC-MS分析22。 <ol><li>两相分离后，过滤DCM相到玻璃试管中。重复使用3-毫升DCM中的提取，和冲洗用2ml DCM中的管中。最后，通过温和氮气吹下来EXCHAN浓缩萃取液至0.5毫升戈到CH溶剂/ ACE（90/10，体积/体积）。 </li></ol></li><li>分析使用大容量注射剂，类似于通过LC-MS / MS 21别处描述的方法中的水样。 </li></ol> 5.仪器分析<ol><li> GC-MS分析<ol><li>执行使用GC-MS系统，电子电离（EI）和负化学电离（NCI）模式，分别为22的CH / ACE提取物的仪器分析。 </li><li>对于使用EI由GC-MS法，注入1微升用不分流进样方法上的HP-5MS UI柱（30m，0.25内径，0.25微米的膜）等分试样。 </li><li>对于由GC-MS，用方法CI，注入的上一个的HP-5MS UI塔3微升（30米，0.25内径，0.25微米的膜）等分试样。 </li></ol></li><li> HPLC-MS / MS分析<ol><li>执行乙腈的仪器分析提取物用HPLC-MS / MS接口与在负电喷雾电离源（（ - ）。ESI）和正离子米颂（（+）ESI）22。 </li><li>为（+）。ESI，稀释100微升的乙腈用FA调节至pH 5 900微升超纯水提取。 </li><li>对于（ - ）ESI，稀释100微升乙腈的用1％FA的超纯水900微升解提取。 </li><li>为（+）。ESI，使用由2-丙醇/甲醇/ 10mM的甲酸铵（92年6月2日，体积/体积/体积）和MeOH的二元梯度以0.3ml分钟-1的流速。 </li><li>为（ - ）。ESI，使用由乙腈/超纯水0.1％醋酸和ACN + 0.1％醋酸的二元梯度以0.3ml分钟-1的流速。 </li><li>使用的使用两个在线固相萃取柱（均为20×2毫米内径和20至25微米的粒度），以及一个分析柱（C 18，100×3毫米，3.5微米）21 500微升大体积注射注入所有样本。 </li></ol></li></ol> 6.理论的被动采样注:该化学品到被动采样器mediu摄取轮廓米（PSM）被分为三个部分:线性的，曲线的和平衡（ 图3）。 <img alt="图3" src="/files/ftp_upload/54053/54053fig3.jpg" /> 图3.被动采样的吸收曲线。 A）和C）以ng绝对分别脒和乐果，累计量摄取曲线，在被动采样（N t）和B）和D）的脒与乐果，分别以ng升水罐浓度- 1。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54053/54053fig3large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <ol><li>通过将目标化合物的累积量在被动采样后曝光的吨天（N&#39; 吨计算被动采样器的等效水体积（V 当量 L）的</su通过使用抓斗和时间集成有源采样在水相中的浓度（C W，纳克L-1）P&gt;，纳克）。 <img alt="式（1）" src="/files/ftp_upload/54053/54053eq1.jpg" /> （1） </li><li>派生从摄取轮廓的线性吸收阶段的采样速率（R S，L天-1），通过取V 当量与部署时的斜率。 </li><li>计算在K PW使用公式个别农药（-1大号公斤）。 2。 <img alt="公式（2）" src="/files/ftp_upload/54053/54053eq2.jpg" /> （2） 其中m，p是每采样吸附剂质量（NG）。 </li><li>线性吸收阶段，计算在由被动采样衍生水分析物的TWA浓度（ 三TWA，纳克L-1），使用式3。 <img alt="公式3" src="/files/ftp_upload/54053/54053eq3.jpg" /> （3） 其中R S是SAmpling率（L天-1），t是部署时间（天）。 </li><li>在曲线阶段，用公式计算ÇTWA。 4。 <img alt="公式4" src="/files/ftp_upload/54053/54053eq4.jpg" /> （4） </li><li>在平衡期，用公式计算ÇTWA。 5。 <img alt="公式5" src="/files/ftp_upload/54053/54053eq5.jpg" /> （5） </li></ol> 7.统计数据分析<ol><li>测试使用夏皮罗-威尔克测试23数据的非正态分布。使用在K PW和R S非参数Spearman秩相关VS测试农药的理化性质（斯皮尔曼的Rho范围从-1到1）24。 </li></ol>

<ol>
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I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+contaminant+removal+of+reverse+osmosis+and+advanced+oxidation+in+full-scale+operation+by+combining+passive+sampling+with+chemical+analysis+and+bioanalytical+tools.">Evaluation of contaminant removal of reverse osmosis and advanced oxidation in full-scale operation by combining passive sampling with chemical analysis and bioanalytical tools.</a> Environ. Sci. Technol. 45, 5387-5394 (2011).</li><li>Pesce, S., Morin, S., Lissalde, S., Montuelle, B., Mazzella, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Combining+polar+organic+chemical+integrative+samplers+(POCIS)+with+toxicity+testing+to+evaluate+pesticide+mixture+effects+on+natural+phototrophic+biofilms.">Combining polar organic chemical integrative samplers (POCIS) with toxicity testing to evaluate pesticide mixture effects on natural phototrophic biofilms.</a> Environ. Pollut. 159 (3), 735-741 (2011).</li><li>Booij, K., Smedes, F., Van Weerlee, E. M., Honkoop, P. J. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Environmental+monitoring+of+hydrophobic+organic+contaminants:+The+case+of+mussels+versus+semipermeable+membrane+devices.">Environmental monitoring of hydrophobic organic contaminants: The case of mussels versus semipermeable membrane devices.</a> Environ. Sci. Technol. 40 (12), 3893-3900 (2006).</li><li>Harman, C., Allan, I. J., Vermeirssen, E. L. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Calibration+and+use+of+the+polar+organic+chemical+integrative+sampler-a+critical+review.">Calibration and use of the polar organic chemical integrative sampler-a critical review.</a> Environ. Toxicol. Chem. 31 (12), 2724-2738 (2012).</li><li>Jonker, M. T. O., Der Heijden, S. A. V. a. n., Kotte, M., Smedes, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantifying+the+effects+of+temperature+and+salinity+on+partitioning+of+hydrophobic+organic+chemicals+to+silicone+rubber+passive+samplers.">Quantifying the effects of temperature and salinity on partitioning of hydrophobic organic chemicals to silicone rubber passive samplers.</a> Environ. Sci. Technol. 49 (11), 6791-6799 (2015).</li><li>Jansson, C., Kreuger, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiresidue+analysis+of+95+pesticides+at+low+nanogram/liter+levels+in+surface+waters+using+online+preconcentration+and+high+performance+liquid+chromatography/tandem+mass+spectrometry.">Multiresidue analysis of 95 pesticides at low nanogram/liter levels in surface waters using online preconcentration and high performance liquid chromatography/tandem mass spectrometry.</a> J. AOAC Int. 93 (6), 1732-1747 (2010).</li><li>Ahrens, L., Daneshvar, A., Lau, A. E., Kreuger, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+five+passive+sampling+devices+for+monitoring+of+pesticides+in+water.">Characterization of five passive sampling devices for monitoring of pesticides in water.</a> J. Chromatogr. A. 1405, 1-11 (2015).</li><li>Royston, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Approximating+the+Shapiro-Wilk+W-test+for+non-normality.">Approximating the Shapiro-Wilk W-test for non-normality.</a> Stat. Comput. 2 (3), 117-119 (1992).</li><li>Gauthier, T. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Detecting+trends+using+Spearman's+rank+correlation+coefficient.">Detecting trends using Spearman's rank correlation coefficient.</a> Environ. Forensics. 2 (4), 359-362 (2001).</li><li>Morin, N., Mi&#232;ge, C., Coquery, M., Randon, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chemical+calibration,+performance,+validation+and+applications+of+the+polar+organic+chemical+integrative+sampler+(POCIS)+in+aquatic+environments.">Chemical calibration, performance, validation and applications of the polar organic chemical integrative sampler (POCIS) in aquatic environments.</a> TrAC - Trend. Anal. Chem. 36, 144-175 (2012).</li><li>. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Water+Quality+-+Sampling+-+Part+23:+Guidance+on+Passive+Sampling+in+Surface+Waters.">Water Quality - Sampling - Part 23: Guidance on Passive Sampling in Surface Waters.</a> ISO 5667-23:2011. , (2011).</li><li>Morin, N., Camilleri, J., Cren-Oliv&#233;, C., Coquery, M., Mi&#232;ge, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Determination+of+uptake+kinetics+and+sampling+rates+for+56+organic+micropollutants+using+"pharmaceutical"+POCIS.">Determination of uptake kinetics and sampling rates for 56 organic micropollutants using "pharmaceutical" POCIS.</a> Talanta. 109, 61-73 (2013).</li></ol>

The authors have nothing to disclose.

在质量控制方面，作为标准程序，实验室空白，检测（LOD），回收率和重复性的限制进行了检查23。在低浓度水平空白样本中检测到一些农药。检测限被设置为最低点的符合的信号的标准来3.信噪比平均检测限为8.0皮克绝对注入对硅橡胶，1.7皮克绝对为POCIS-A，1.6柱校正曲线上的值皮克绝对的POCIS-B，3.0皮克绝对的SDB-RPS磁盘和1.6皮克绝对对C盘18。所有浓度通过加标校正IS混合物。基于本地农药的加标被动样本平均方法回收率（n = 3）分别为68％，110％，92％，89％和硅橡胶70％，POCIS-A，POCIS-B，SDB-RPS盘和C 18盘，分别为。平均重复性个别杀虫剂（10）分别为19％，20％，16％，33％和硅氧烷擦36％BER，POCIS-A，POCIS-B，SDB-RPS分别为磁盘和C 18盘。 最杀虫剂具有124短线性吸收曲线（5至10天）和26天后平衡， 即 124为硅橡胶89，124为POCIS-A 97，124为POCIS-B 99，32，用于SDB-RPS磁盘，对于C 18盘124 36。因此，对于大多数杀虫剂日志K&#39;PW可以计算（ 表1）。如果农药没有平衡，日志K&#39; 的PW被假定为比计算1o9 氏更高"PW的平衡相。平均R&#39;S（l·天-1）分别为0.86硅橡胶，0.22 POCIS-B，0.18 POCIS-A，0.05 SDB-RPS磁盘和0.02对C盘18。高的R&#39;为硅橡胶S能够通过硅橡胶的较高的吸附剂质量（m p）的 （M p为说明</青霉&gt; = 15.6Hz G）相对于其他被动采样（M p值= 0.22-0.58克）。平均1o9 氏PW（L公斤-1）为4.78的POCIS-B，为4.56 POCIS-A，3.17 SDB-RPS盘，3.14硅橡胶和2.71对C盘18。差异可以通过比较硅橡胶不同的表面面积（A P），这是对POCIS-A和POCIS-B高（ 且p = 1.78×10 6 平方厘米和2.82×10 6 平方厘米，分别）（ 的p解释=457厘米2），SDB-RPS盘和C盘18（ 的p = 35 平方厘米两种）。重要的是要注意的是，R&#39;S能不同的校准方法和被动采样的类型之间变化，从而有必要定义标准化的协议用 ​​于校准程序25。 使用静态DEPL进行这项研究这具有这样的优点奥迅具有简单的设置有许多重复，但需要考虑随时间的浓度耗尽。未来的摄取研究应采用流通曝光坦克的接触浓度常数或原位真实的现场部署条件19下进行。在实验室校准实验中使用的天然水，但是，在DOC可以对采样率的确定产生影响。19此外，性能和参照化合物（潜能再生），其部署之前被掺入到被动采样器的使用，可以被用来计算在原位吸收速率，并允许TWA浓度的更准确的估计。26 硅橡胶和C 18盘的1o9 氏PW表现出与1o9 氏OW一个显著正相关（斯皮尔曼的RHO = 0.53和0.48，分别; P &lt;0.0001）。对于卷筒R S值，一个显著正相关关系只发现卷筒R 标间和日志硅橡胶K个OW（斯皮尔曼的RHO = 0.56，P &lt;0.0001）。在一般情况下，在K OW已被证明是预测为特定目标化合物14,27被动采样器的适用性良好的参数。各种不同的农药在这项研究中有1o9 氏OW范围从-2.6到7.0进行了调查。一般情况下，五个测试被动采样有能力积累与硅橡胶多种不同钾肥OW农药（K OW = 0.70 - 7.0），POCIS A（-1.9 - 5.3），POCIS B（-1.9 - 5.2） ，SDB-RPS盘（-1.2 - 4.7）和C 18盘（1.3 - 5.3）（ 图4）。我们的结果表明，硅橡胶是更适合的疏水性化合物（1o9 氏OW&gt; 5.3），而更极性化合物（1o9 氏OW &lt;0.70）由POCIS A，POCIS B和SDB-RPS盘（ 图4）被更好吸收。

农药不断引入到水生环境，并可能对水生生物1的风险。通常由于在流或偶发输入（ 例如 ，沉淀，合并的下水道溢出污水泻湖释放）2的波动进行在水性环境农药监测采用抓斗采样，但是，这种取样技术不能完全解释的浓度的时间变化，3。因此，监测的方法需要与杀虫剂相关的环境风险的更好的估计加以改进。被动采样允许在一段时间以最少的基础设施和低污染物浓度4,5-长时间连续监测。 被动采样已被证明是在地下水6的监测，淡水7-10，废水11和海水12的宝贵工具。除了监控的目的<suP&gt; 13,14，被动采样器也已用于非目标分析15，毒理学试验16,17，并且作为替代sediment-和生物监测18。被动采样水不断积聚的化学品和提供时间加权平均（TWA）的浓度14。污染物的吸收取决于采样速率（R S）和被动采样-水分配系数（K PW），它依赖于被动采样设计，采样器材料，污染物的物理化学性质，和环境条件（ 例如 ，水湍流，温度）13,14,19,20。 详细的视频旨在展示如何校准和应用被动采样器在水中的农药。具体目标包括我），以使用五种不同类型的被动SAMPL的124个别农药进行准备，提取和仪器分析器，包括硅橡胶，极性有机化学综合采样（POCIS）-A，POCIS-B，SDB-RPS和C 18磁盘，ⅱ）以评估R 5和K PW用于在实验室摄取研究的杀虫剂，以及iii）来演示如何选择感兴趣和如何计算TWA浓度对于各个被动采样的目标化合物相应的被动采样器。 参考标准和被动采样装置 目标化合物包括124遗留和目前使用的杀虫剂，包括除草剂，杀虫剂和杀真菌剂（ 表1）。内部标准混合物（IS混合物）包括fenoprop（2,4,5-TP），可尼丁-D 3，乙硫磷和特丁-D 5。其他使用的化学品包括甲醇（MeOH），乙腈（ACN），丙酮（ACE）二氯甲烷（DCM），环己烷（CH），乙酸乙酯（EA），石油等她的（PE），2-丙醇，25％氨水溶液，乙酸（醋酸）和甲酸（FA）。五种不同的被动采样装置进行了表征，包括硅橡胶，POCIS-A和POCIS-B，SDB-RPS和C 18盘1,21。 表1.被动采样器的采样率（R&#39;S，L天-1），采样-水分配系数（K&#39;PW，L千克-1），用于浓度的野外样品个别在计算方程（方程） 杀虫剂 。 （从色谱A的1405，卢茨阿伦斯，Atlasi Daneshvar，安娜E.刘珍妮第六，别上五个被动采样器件表征转载于水，1-11版权所有（2015）农药监测，经许可爱思唯尔）22 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54053/Table_1.xlsx" target="_blank">请点击此处下载此文件。</a>

<table border="0" cellpadding="0" cellspacing="0" width="1047">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:492px;">Methanol</td>
			<td style="width:164px;">Merck Millipore</td>
			<td style="width:163px;">1.06035.2500</td>
			<td style="width:228px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Acetonitrile</td>
			<td>Merck Millipore</td>
			<td>1.00029.2500&#160;</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:22px;width:492px;">Acetone</td>
			<td>Merck Millipore</td>
			<td style="width:163px;">1.00012.2500</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">2-propanol</td>
			<td>Merck Millipore</td>
			<td>1.00272.2500</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Dichloromethane</td>
			<td>Merck Millipore</td>
			<td>1.06054.2500</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Ammoniak</td>
			<td>Merck Millipore</td>
			<td>1.05428.1000</td>
			<td>Purity 25%</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Formic acid</td>
			<td style="width:164px;">Sigma-Aldrich</td>
			<td>94318-50ML-F</td>
			<td>Purity ~98%</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:22px;">Ethyl acetate&#160;</td>
			<td style="width:164px;">Sigma-Aldrich</td>
			<td>31063-2.5L</td>
			<td>for pesticide residue analysis</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:22px;">Petroleum ether&#160;</td>
			<td style="width:164px;">Sigma-Aldrich</td>
			<td>34491-4X2.5L</td>
			<td>for pesticide residue analysis</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Acetic acid&#160;</td>
			<td style="width:164px;">Sigma-Aldrich</td>
			<td>320099-500ML</td>
			<td>Purity &#8805;99.7%</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Cyclohexane&#160;</td>
			<td style="width:164px;">Fisher Chemicals</td>
			<td>C/8933/17</td>
			<td>for residue analysis</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Empty polypropylene SPE Tube with PE frits, 20 &#956;m porosity, volume 6&#160;mL</td>
			<td style="width:164px;">Supelco</td>
			<td>57026</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:492px;">Empore SPE Disks, C18, diam. 47&#160;mm</td>
			<td>Supelco</td>
			<td style="width:163px;">66883-U</td>
			<td>Passive sampler</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:492px;">Empore SPE Disks, SDB-RPS (Reversed-Phase Sulfonate), diam. 47&#160;mm</td>
			<td>Supelco</td>
			<td style="width:163px;">66886-U&#160;</td>
			<td>Passive sampler</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:492px;">POCIS-A&#160;</td>
			<td>EST</td>
			<td style="width:163px;">POCIS-HLB</td>
			<td>Passive sampler</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:492px;">POCIS-B</td>
			<td>EST</td>
			<td style="width:163px;">POCIS-Pesticide&#160;</td>
			<td>Passive sampler</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:492px;">Polyethersulfone (PES) membranes</td>
			<td>EST</td>
			<td style="width:163px;">PES</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:492px;">Silicone rubber sheet</td>
			<td style="width:164px;">Altec</td>
			<td style="width:163px;">03-65-4516</td>
			<td>Passive sampler</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:492px;">Agilent 5975C</td>
			<td style="width:164px;">Agilent Technologies</td>
			<td style="width:163px;">5975C</td>
			<td>GC-MS</td>
		</tr>
		<tr height="23">
			<td height="23" style="height:23px;width:492px;">HP-5MS UI</td>
			<td style="width:164px;">J&#38;W Scientific</td>
			<td style="width:163px;">HP-5MS</td>
			<td>Analytical column for GC-MS</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:492px;">Agilent 6460</td>
			<td style="width:164px;">Agilent Technologies</td>
			<td style="width:163px;">6460</td>
			<td>HPLC-MS/MS</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:492px;">Strata C18&#8211;E, 20 x 2 mm id and 20&#8211;25 &#956;m particle size</td>
			<td style="width:164px;">Phenomenex</td>
			<td style="width:163px;">Strata C18&#8211;E</td>
			<td style="width:228px;">Online SPE column for LC-MS/MS</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:492px;">Strata X, 20 x 2 mm id and 20&#8211;25 &#956;m particle size</td>
			<td style="width:164px;">Phenomenex</td>
			<td style="width:163px;">Strata X</td>
			<td style="width:228px;">Online SPE column for LC-MS/MS</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:492px;">Zorbax Eclipse Plus C18</td>
			<td style="width:164px;">Agilent Technologies</td>
			<td style="width:163px;">Zorbax Eclipse Plus C18</td>
			<td>Analytical column for LC-MS/MS</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:492px;">Isolute phase separator, 25 mL</td>
			<td style="width:164px;">Biotage</td>
			<td style="width:163px;">120-1907-E</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:492px;">Stainless steel blind rivet, 3.2x10 mm</td>
			<td style="width:164px;">Ejot &#38; Avdel</td>
			<td style="width:163px;">951222</td>
			<td></td>
		</tr>
	</tbody>
</table>

characterization and application of passive samplers for monitoring of pesticides in water

五种不同的水被动采样进行实验室条件下校准124遗产的测量和当前使用的农药。这项研究提供了被动采样准备，校准，提取方法和仪器分析的协议。采样率（R S）和被动采样水分配系数（K PW）分别计算硅橡胶，极性有机化工综合采样POCIS-A，POCIS-B，SDB-RPS和C 18盘。所选化合物的摄取取决于它们的物理化学性质， 即 ，硅橡胶表现出对更疏水的化合物更好的摄取（登录辛醇-水分配系数（K OW）&gt; 5.3），而POCIS-A，POCIS-B和SDB- RPS盘更适合亲水性化合物（1o9 氏OW &lt;0.70）。

五种不同的被动采样技术124遗产的摄取和当前使用的农药，包括硅橡胶（ 图1），POCIS A，POCIS B，SDB-RPS和C 18盘（ 图2）进行比较。提取方法和仪器分析的性能得到了优化。实验室摄取实验的结果可用于计算R&#39;S和登录K&#39;PW的值的基础上为各个杀虫剂（ 图3）的摄取信息（ 见表1）。结果表明，硅橡胶更适合于疏水性化合物（辛醇-水分配系数（K&#39;OW）&gt; 5.3），而更多的极性化合物（日志K&#39;OW &lt;0.70）均好采取由POCIS A，POCIS乙和SDB-RPS盘（ 图4）:R 作者: </sub&gt;（L天-1），K&#39;PW（L千克-1）和公式（公式）可以用于浓度的野外样品个别杀虫剂（ 表1）22中的计算。 <img alt="图4" src="/files/ftp_upload/54053/54053fig4.jpg" /> 图4.ķOW VS 被动采样类型箱须-地块由硅橡胶占用单个农药（N = 86），极性有机化工综合采样器（POCIS）-A（N = 106），POCIS-B（N在关系到他们的辛醇-水分配系数（K OW）= 110），SDB-RPS盘（N = 65）和C 18盘（N = 54）。注意:如果在被动采样的平均农药浓度大于0.1％，比均值PE农药只包括sticide浓度在水中。 （从色谱A的，1405，卢茨阿伦斯，Atlasi Daneshvar，安娜E.刘珍妮第六，别上五个被动采样设备特性修改为水，1-11版权所有（2015）农药监测，经许可爱思唯尔）22 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54053/54053fig4large.jpg" target="_blank">请点击此处查看该图的放大版本。</a>

Watch this Scientific Journal Video about Characterization and Application of Passive Samplers for Monitoring of Pesticides in Water at JoVE.com

Characterization and Application of Passive Samplers for Monitoring of Pesticides in Water

A protocol about the characterization and application of five different passive sampling devices is presented.

表征和被动采样的应用在农药水监测

Five different water passive samplers were calibrated under laboratory conditions for measurement of 124 legacy and current used pesticides. This study ...

characterization-application-passive-samplers-for-monitoring

Nanyang Technological University

Research

JoVE Journal

Environment

9.4K 次观看.  Swedish University of Agricultural Sciences. A protocol about the characterization and application of five different passive sampling devices is presented.

视频: Characterization and Application of Passive Samplers for Monitoring of Pesticides in Water

Waste Water Derived Electroactive Microbial Biofilms: Growth, Maintenance, and Basic Characterization

The growth of anodic electroactive microbial biofilms from waste water inocula in a fed-batch reactor is demonstrated using a three-electrode setup controlled by a potentiostat. Thereby the use of potentiostats allows an exact adjustment of the electrode potential and ensures reproducible microbial culturing conditions. During growth the current production is monitored using chronoamperometry (CA). Based on these data the maximum current density (jmax) and the coulombic efficiency (CE) are discussed as measures for characterization of the bioelectrocatalytic performance. Cyclic voltammetry (CV), a nondestructive, i.e. noninvasive, method, is used to study the extracellular electron transfer (EET) of electroactive bacteria. CV measurements are performed on anodic biofilm electrodes in the presence of the microbial substrate, i.e. turnover conditions, and in the absence of the substrate, i.e. nonturnover conditions, using different scan rates. Subsequently, data analysis is exemplified and fundamental thermodynamic parameters of the microbial EET are derived and explained: peak potential (Ep), peak current density (jp), formal potential (Ef) and peak separation (&#916;Ep). Additionally the limits of the method and the state-of the art data analysis are addressed. Thereby this video-article shall provide a guide for the basic experimental steps and the fundamental data analysis.

Chronoamperometric growth of anodic electroactive microbial biofilms in a fed-batch reactor using a three-electrode setup, controlled by a potentiostat, is demonstrated. The extracellular electron transfer is characterized using cyclic voltammetry in the presence of the electron donor and in the absence of the electron donor. Fundamental data analysis is demonstrated.

The growth of anodic electroactive microbial biofilms from waste water inocula in a fed-batch reactor is demonstrated using a three-electrode setup ...

科研

环境科学

EPA Method 1615. Measurement of Enterovirus and Norovirus Occurrence in Water by Culture and RT-qPCR. I. Collection of Virus Samples

EPA Method 1615 was developed with a goal of providing a standard method for measuring enteroviruses and noroviruses in environmental and drinking waters. The standardized sampling component of the method concentrates viruses that may be present in water by passage of a minimum specified volume of water through an electropositive cartridge filter. The minimum specified volumes for surface and finished/ground water are 300 L and 1,500 L, respectively. A major method limitation is the tendency for the filters to clog before meeting the sample volume requirement. Studies using two different, but equivalent, cartridge filter options showed that filter clogging was a problem with 10% of the samples with one of the filter types compared to 6% with the other filter type. Clogging tends to increase with turbidity, but cannot be predicted based on turbidity measurements only. From a cost standpoint one of the filter options is preferable over the other, but the water quality and experience with the water system to be sampled should be taken into consideration in making filter selections.

EPA Method 1615 uses an electropositive filter to concentrate enteroviruses and noroviruses in environmental and drinking waters. This manuscript describes the procedure for collecting samples for Method 1615 analyses.

EPA方法1615测量肠道病毒和诺瓦克病毒发生水由文化和RT-qPCR的了。病毒样本的收集I.

EPA Method 1615 was developed with a goal of providing a standard method for measuring enteroviruses and noroviruses in environmental and drinking waters. ...

EPA Method 1615. Measurement of Enterovirus and Norovirus Occurrence in Water by Culture and RT-qPCR. Part III. Virus Detection by RT-qPCR

EPA Method 1615 measures enteroviruses and noroviruses present in environmental and drinking waters. This method was developed with the goal of having a standardized method for use in multiple analytical laboratories during monitoring period 3 of the Unregulated Contaminant Monitoring Rule. Herein we present the protocol for extraction of viral ribonucleic acid (RNA) from water sample concentrates and for quantitatively measuring enterovirus and norovirus concentrations using reverse transcription-quantitative PCR (RT-qPCR). Virus concentrations for the molecular assay are calculated in terms of genomic copies of viral RNA per liter based upon a standard curve. The method uses a number of quality controls to increase data quality and to reduce interlaboratory and intralaboratory variation. The method has been evaluated by examining virus recovery from ground and reagent grade waters seeded with poliovirus type 3 and murine norovirus as a surrogate for human noroviruses. Mean poliovirus recoveries were 20% in groundwaters and 44% in reagent grade water. Mean murine norovirus recoveries with the RT-qPCR assay were 30% in groundwaters and 4% in reagent grade water.

Here we present a procedure to quantify enterovirus and norovirus in environmental and drinking waters using reverse transcription-quantitative PCR. Mean virus recovery from groundwater with this standardized procedure from EPA Method 1615 was 20% for poliovirus and 30% for murine norovirus.

EPA方法1615测量肠道病毒和诺瓦克病毒发生水由文化和RT-qPCR的了。第三部分。病毒检测用RT-qPCR的

EPA Method 1615 measures enteroviruses and noroviruses present in environmental and drinking waters. This method was developed with the goal of having a ...

Calibrated Passive Sampling - Multi-plot Field Measurements of NH3 Emissions with a Combination of Dynamic Tube Method and Passive Samplers

Agricultural ammonia (NH3) emissions (90% of total EU emissions) are responsible for about 45% airborne eutrophication, 31% soil acidification and 12% fine dust formation within the EU15. But NH3 emissions also mean a considerable loss of nutrients. Many studies on NH3 emission from organic and mineral fertilizer application have been performed in recent decades. Nevertheless, research related to NH3 emissions after application fertilizers is still limited in particular with respect to relationships to emissions, fertilizer type, site conditions and crop growth. Due to the variable response of crops to treatments, effects can only be validated in experimental designs including field replication for statistical testing. The dominating ammonia loss methods yielding quantitative emissions require large field areas, expensive equipment or current supply, which restricts their application in replicated field trials. This protocol describes a new methodology for the measurement of NH3 emissions on many plots linking a simple semi-quantitative measuring method used in all plots, with a quantitative method by simultaneous measurements using both methods on selected plots. As a semi-quantitative measurement method passive samplers are used. The second method is a dynamic chamber method (Dynamic Tube Method) to obtain a transfer quotient, which converts the semi-quantitative losses of the passive sampler to quantitative losses (kg nitrogen ha-1). The principle underlying this approach is that passive samplers placed in a homogeneous experimental field have the same NH3 absorption behavior under identical environmental conditions. Therefore, a transfer co-efficient obtained from single passive samplers can be used to scale the values of all passive samplers used in the same field trial. The method proved valid under a wide range of experimental conditions and is recommended to be used under conditions with bare soil or small canopies (&#60;0.3 m). Results obtained from experiments with taller plants should be treated more carefully.

Calibrated Passive Sampling - Multi-plot Field Measurements of NH3 Emissions with a Combination of Dynamic Tube Method and Passive Samplers

Ammonia emissions are a major threat to the environment by eutrophication, soil acidification and fine particle formation and stem mainly from agricultural sources. This method allows ammonia loss measurements in replicated field trials enabling statistical analysis of emissions and of relationships between crop development and emissions.

校准被动采样 - NH多情节场测量<sub&gt; 3</sub&gt;与动态管法和被动采样的组合排放

Agricultural ammonia (NH3) emissions (90% of total EU emissions) are responsible for about 45% airborne eutrophication, 31% soil acidification and 12% ...

Extraction of Organochlorine Pesticides from Plastic Pellets and Plastic Type Analysis

Plastic resin pellets, categorized as microplastics (&#8804;5 mm in diameter), are small granules that can be unintentionally released to the environment during manufacturing and transport. Because of their environmental persistence, they are widely distributed in the oceans and on beaches all over the world. They can act as a vector of potentially toxic organic compounds (e.g., polychlorinated biphenyls) and might consequently negatively affect marine organisms. Their possible impacts along the food chain are not yet well understood. In order to assess the hazards associated with the occurrence of plastic pellets in the marine environment, it is necessary to develop methodologies that allow for rapid determination of associated organic contaminant levels. The present protocol describes the different steps required for sampling resin pellets, analyzing adsorbed organochlorine pesticides (OCPs) and identifying the plastic type. The focus is on the extraction of OCPs from plastic pellets by means of a pressurized fluid extractor (PFE) and on the polymer chemical analysis applying Fourier Transform-InfraRed (FT-IR) spectroscopy. The developed methodology focuses on 11 OCPs and related compounds, including dichlorodiphenyltrichloroethane (DDT) and its two main metabolites, lindane and two production isomers, as well as the two biologically active isomers of technical endosulfan. This protocol constitutes a simple and rapid alternative to existing methodology for evaluating the concentration of organic contaminants adsorbed on plastic pieces.

Microplastics act as vector of potentially toxic organic contaminants with unpredictable effects. This protocol describes an alternative methodology for assessing the levels of organochlorine pesticides adsorbed on plastic pellets and identifying the polymer chemical structure. The focus is on pressurized fluid extraction and attenuated total reflectance Fourier transform infrared spectroscopy.

从塑料颗粒中提取有机氯农药和塑料类型分析

Plastic resin pellets, categorized as microplastics (&#8804;5 mm in diameter), are small granules that can be unintentionally released to the environment ...

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Pollutant concentrations and loads in watersheds vary considerably with time and space. Accurate and timely information on the magnitude of pollutants in water resources is a prerequisite for understanding the drivers of the pollutant loads and for making informed water resource management decisions. The commonly used &#34;grab sampling&#34; method provides the concentrations of pollutants at the time of sampling (i.e., a snapshot concentration) and may under- or overpredict the pollutant concentrations and loads. Continuous monitoring of nutrients and sediment has recently received more attention due to advances in computing, sensing technology, and storage devices. This protocol demonstrates the use of sensors, sondes, and instrumentation to continuously monitor in situ nitrate, ammonium, turbidity, pH, conductivity, temperature, and dissolved oxygen (DO) and to calculate the loads from two streams (ditches) in two agricultural watersheds. With the proper calibration, maintenance, and operation of sensors and sondes, good water quality data can be obtained by overcoming challenging conditions such as fouling and debris buildup. The method can also be used in watersheds of various sizes and characterized by agricultural, forested, and/or urban land.

With the advancement of technology and the rise in end-user expectations, the need and use of higher temporal resolution data for pollutant load estimation has increased. This protocol describes a method for continuous in situ water quality monitoring to obtain higher temporal resolution data for informed water resource management decisions.

农业流域营养盐和泥沙的连续河道监测

Pollutant concentrations and loads in watersheds vary considerably with time and space. Accurate and timely information on the magnitude of pollutants in ...

Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds

Vernal ponds, also referred to as vernal pools, provide critical ecosystem services and habitat for a variety of threatened and endangered species. However, they are vulnerable parts of the landscapes that are often poorly understood and understudied. Land use and management practices, as well as climate change are thought to be a contribution to the global amphibian decline. However, more research is needed to understand the extent of these impacts. Here, we present methodology for characterizing a vernal pond's morphology and detail a monitoring station that can be used to collect water quantity and quality data over the duration of a vernal pond's hydroperiod. We provide methodology for how to conduct field surveys to characterize the morphology and develop stage-storage curves for a vernal pond. Additionally, we provide methodology for monitoring the water level, temperature, pH, oxidation-reduction potential, dissolved oxygen, and electrical conductivity of water in a vernal pond, as well as monitoring rainfall data. This information can be used to better quantify the ecosystem services that vernal ponds provide and the impacts of anthropogenic activities on their ability to provide these services.

Understanding the ecosystem services and processes provided by vernal ponds and the impacts of anthropogenic activities on their ability to provide these services requires intensive hydrologic monitoring. This sampling protocol using in-situ monitoring equipment was developed to understand the impact of anthropogenic activities on water levels and quality.

春季池塘连续水文水质监测

Vernal ponds, also referred to as vernal pools, provide critical ecosystem services and habitat for a variety of threatened and endangered species. ...

Improving Infrared Spectroscopy Characterization of Soil Organic Matter with Spectral Subtractions

Soil organic matter (SOM) underlies numerous soil processes and functions. Fourier transform infrared (FTIR) spectroscopy detects infrared-active organic bonds that constitute the organic component of soils. However, the relatively low organic matter content of soils (commonly &#60; 5% by mass) and absorbance overlap of mineral and organic functional groups in the mid-infrared (MIR) region (4,000-400 cm-1) engenders substantial interference by dominant mineral absorbances, challenging or even preventing interpretation of spectra for SOM characterization. Spectral subtractions, a post-hoc mathematical treatment of spectra, can reduce mineral interference and enhance resolution of spectral regions corresponding to organic functional groups by mathematically removing mineral absorbances. This requires a mineral-enriched reference spectrum, which can be empirically obtained for a given soil sample by removing SOM. The mineral-enriched reference spectrum is subtracted from the original (untreated) spectrum of the soil sample to produce a spectrum representing SOM absorbances. Common SOM removal methods include high-temperature combustion (&#39;ashing&#39;) and chemical oxidation. Selection of the SOM removal method carries two considerations: (1) the amount of SOM removed, and (2) absorbance artifacts in the mineral reference spectrum and thus the resulting subtraction spectrum. These potential issues can, and should, be identified and quantified in order to avoid fallacious or biased interpretations of spectra for organic functional group composition of SOM. Following SOM removal, the resulting mineral-enriched sample is used to collect a mineral reference spectrum. Several strategies exist to perform subtractions depending on the experimental goals and sample characteristics, most notably the determination of the subtraction factor. The resulting subtraction spectrum requires careful interpretation based on the aforementioned methodology. For many soil and other environmental samples containing substantial mineral components, subtractions have strong potential to improve FTIR spectroscopic characterization of organic matter composition.

SOM underlies many soil functions and processes, but its characterization by FTIR spectroscopy is often challenged by mineral interferences. The described method can increase the utility of SOM analysis by FTIR spectroscopy by subtracting mineral interferences in soil spectra using empirically obtained mineral reference spectra.

利用光谱减法改进土壤有机质的红外光谱表征

Soil organic matter (SOM) underlies numerous soil processes and functions. Fourier transform infrared (FTIR) spectroscopy detects infrared-active organic ...

The Plant Infection Test: Spray and Wound-Mediated Inoculation with the Plant Pathogen Magnaporthe Grisea

Plants possess a powerful system to defend themselves against potential threats by pathogenic fungi. For agriculturally important plants, however, current measures to combat such pathogens have proved too conservative and, thus, not sufficiently effective, and they can potentially pose environmental risks. Therefore, it is extremely necessary to identify host-resistance factors to assist in controlling plant diseases naturally through the identification of resistant germplasm, the isolation and characterization of resistance genes, and the molecular breeding of resistant cultivars. In this regard, there is need to establish an accurate, rapid, and large-scale inoculation method to breed and develop plant resistance genes. The rice blast fungal pathogen Magnaporthe grisea causes severe disease symptoms and yield losses. Recently, M. grisea has emerged as a model organism for studying the mechanisms of plant-fungal pathogen interactions. Hence, we report the development of a plant virulence test method that is specific for M. grisea. This method provides for both spray inoculation with a conidial suspension and wounding inoculation with mycelium cubes or droplets of conidial suspension. The key step of the wounding inoculation method for detached rice leaves is to make wounds on plant leaves, which avoids any interference caused by host penetration resistance. This spray/wounding protocol contributes to the rapid, accurate, and large-scale screening of the pathotypes of M. grisea isolates. This integrated and systematic plant infection method will serve as an excellent starting point for gaining a broad perspective of issues in plant pathology.

The Plant Infection Test: Spray and Wound-Mediated Inoculation with the Plant Pathogen Magnaporthe Grisea

Here, we present a protocol to test plant virulence with the plant pathogen Magnaporthe grisea. This report will contribute to the large-scale screening of the pathotypes of fungi isolates and serve as an excellent starting point for understanding the resistant mechanisms of plants during molecular breeding.

植物感染试验: 以植物病原菌为载体的喷雾和伤口介导接种

Plants possess a powerful system to defend themselves against potential threats by pathogenic fungi. For agriculturally important plants, however, current ...

Visualizing Efficacy of Pesticides Against Disease Vector Mosquitoes in the Field

Efficacy of public health pesticides targeting nuisance and disease-vector insects such as mosquitoes, sand flies, and filth-breeding flies is not uniform across ecological zones. To best protect public and veterinary health from these insects, the environmental limitations of pesticides need to be investigated to inform effective use of the most appropriate pesticide formulations and techniques. We have developed a research program to evaluate combinations of pesticides, pesticide application equipment, and application techniques in hot-arid desert, hot-humid tropical, warm and cool temperate, and urban locations to derive pesticide use guidelines specific to target insect and environment. To these ends we designed a system of protocols to support efficient, cost-effective, portable, and standardized evaluation of a diverse range of pesticides and equipment across multiple environments. At the core of these protocols is the use of an array of small cages with colony-reared sentinel mosquitoes (adults and immatures) and sand flies (adults), strategically arranged in natural habitats and exposed to pesticide spray. Spatial and temporal patterns of pesticide efficacy are derived from percent mortality in sentinel cages, then mapped and visualized in a geographic information system. Maps of sentinel mortality data may be statistically compared to evaluate relative efficacy of a pesticide across multiple environments, or to study multiple pesticides in a single environment. Protocols may be modified to accommodate a variety of scenarios, including, for example, the vertical orientation of sentinels in canopy habitats or simultaneous testing of ground and aerial application methods.

The efficacy of public health pesticides targeting nuisance and disease-vector insects is not uniform across different ecological zones. Here we present a system of techniques using captive vector insects as sentinels for pesticide efficacy to derive electronic maps supporting the standard evaluation of pesticides across multiple environments.

农药在田间对病媒蚊子的影响

Efficacy of public health pesticides targeting nuisance and disease-vector insects such as mosquitoes, sand flies, and filth-breeding flies is not uniform ...