Article(id=1217529313516241655, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1217529305693864468, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20250324005, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1742745600000, receivedDateStr=2025-03-24, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1768211208942, onlineDateStr=2026-01-12, pubDate=1752508800000, pubDateStr=2025-07-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1768211208942, onlineIssueDateStr=2026-01-12, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1768211208942, creator=13701087609, updateTime=1768211208942, updator=13701087609, issue=Issue{id=1217529305693864468, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='13', pageStart='1', pageEnd='320', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1768211207077, creator=13701087609, updateTime=1768212057891, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1217532874337730593, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1217529305693864468, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1217532874337730594, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1217529305693864468, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=170, endPage=179, ext={EN=ArticleExt(id=1217529314296382240, articleId=1217529313516241655, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Research progress on the application of smart hydrogel technology in agro-product safety detection, columnId=1151895321388347923, journalTitle=Journal of Food Safety & Quality, columnName=Food Analysis and Detection, runingTitle=null, highlight=null, articleAbstract=

Agricultural product safety form the foundation of constructing food supply systems. Smart hydrogels exhibit promising application prospects in agricultural safety analysis due to their stimuli responsiveness, mechanical stability, biocompatibility, and adjustable pore size. This review focused on the classification, preparation methods, responsive mechanisms and applications of smart hydrogels in agricultural product safety. Based on synthesis methods, they could be divided into physically cross-linked and chemically cross-linked hydrogels, while stimulus-responsive types included temperature-responsive, pH-responsive, biomolecule-responsive, electric field-responsive and magnetic field-responsive hydrogels. This study summarized their applications in contaminants adsorption/separation, foodborne pathogen detection, mycotoxin detection, pesticide/veterinary drug residue analysis, illegal additive identification, and heavy metal detection for agricultural product assurance. Development prospects of smart hydrogels are further discussed to provide references for their expanded utilization in agricultural product safety.

, correspAuthors=Hai-Hua LI, Wei ZHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Yi-Han WANG, Shu-Lin WEI, Ping WANG, Jia-Yun QIAO, Hai-Hua LI, Wei ZHANG), CN=ArticleExt(id=1217529314682258241, articleId=1217529313516241655, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=智能水凝胶技术在农产品安全检测中的应用研究进展, columnId=1151895321958773274, journalTitle=食品安全质量检测学报, columnName=食品分析与检测, runingTitle=null, highlight=null, articleAbstract=

农产品安全是构建食物供给体系的基础。智能水凝胶具有良好的刺激响应性、机械稳定性、生物兼容性以及孔径可调等特点, 在农产品安全分析领域具有广泛的应用前景。本文围绕智能水凝胶的分类、制备方法及其响应机制在农产品安全中的应用进行综述。根据合成方法的不同分为物理和化学合成方法, 按照刺激反应的类型可以分为温度响应型、pH响应型、生物分子响应型、电场响应型和磁场响应型水凝胶等。重点总结了智能水凝胶在农产品安全领域应用于污染物的吸附分离、食源性致病微生物检测、霉菌毒素检测、农药与兽药残留检测、非法添加物检测及重金属检测的研究进展。最后, 讨论了智能水凝胶的发展前景, 旨在为其在农产品安全领域的应用提供参考。

, correspAuthors=李海花, 张维, authorNote=null, correspAuthorsNote=
*李海花(1981—), 女, 博士, 教授, 主要研究方向为兽医微生物学与免疫学。E-mail: ;
张维(1982—), 男, 博士, 副研究员, 主要研究方向为饲料质量安全分析与毒理学。E-mail:
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#王意涵和魏书林为共同第一作者

王意涵(2000—), 女, 硕士研究生, 主要研究方向为动物性食品安全。E-mail:

魏书林(1978—), 女, 硕士, 助理研究员, 主要研究方向为饲料质量安全分析与检测。E-mail:

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2 中国农业科学院农业质量标准与检测技术研究所, 北京 100081, bio={"content":"

王意涵(2000—), 女, 硕士研究生, 主要研究方向为动物性食品安全。E-mail:

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王意涵(2000—), 女, 硕士研究生, 主要研究方向为动物性食品安全。E-mail:

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魏书林(1978—), 女, 硕士, 助理研究员, 主要研究方向为饲料质量安全分析与检测。E-mail:

"}, bioImg=null, bioContent=

魏书林(1978—), 女, 硕士, 助理研究员, 主要研究方向为饲料质量安全分析与检测。E-mail:

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智能水凝胶技术在农产品安全检测中的应用研究进展
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王意涵 1, 2, # , 魏书林 2, # , 王平 3 , 乔家运 4 , 李海花 1, * , 张维 2, *
食品安全质量检测学报 | 食品分析与检测 2025,16(13): 170-179
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食品安全质量检测学报 | 食品分析与检测 2025, 16(13): 170-179
智能水凝胶技术在农产品安全检测中的应用研究进展
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王意涵1, 2, # , 魏书林2, # , 王平3, 乔家运4, 李海花1, * , 张维2, *
作者信息
  • 1 天津农学院动物科学与动物医学学院, 天津 300392
  • 2 中国农业科学院农业质量标准与检测技术研究所, 北京 100081
  • 3 北大荒农垦集团有限公司宝泉岭分公司, 鹤岗 154211
  • 4 天津师范大学生命科学学院, 天津 300387
  • 王意涵(2000—), 女, 硕士研究生, 主要研究方向为动物性食品安全。E-mail:

    魏书林(1978—), 女, 硕士, 助理研究员, 主要研究方向为饲料质量安全分析与检测。E-mail:

通讯作者:

*李海花(1981—), 女, 博士, 教授, 主要研究方向为兽医微生物学与免疫学。E-mail: ;
张维(1982—), 男, 博士, 副研究员, 主要研究方向为饲料质量安全分析与毒理学。E-mail:
Research progress on the application of smart hydrogel technology in agro-product safety detection
Yi-Han WANG1, 2, # , Shu-Lin WEI2, # , Ping WANG3, Jia-Yun QIAO4, Hai-Hua LI1, * , Wei ZHANG2, *
Affiliations
  • 1 College of Animal Science and Veterinary Medicine, Tianjin Agricultural University, Tianjin 300392, China
  • 2 Institute of Quality Standard and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Beijing 100081, China
  • 3 Beidahuang Group Baoquanling Branch Office, Hegang 154211, China
  • 4 College of Life Sciences, Tianjin Normal University, Tianjin 300387, China
出版时间: 2025-07-15 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250324005
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农产品安全是构建食物供给体系的基础。智能水凝胶具有良好的刺激响应性、机械稳定性、生物兼容性以及孔径可调等特点, 在农产品安全分析领域具有广泛的应用前景。本文围绕智能水凝胶的分类、制备方法及其响应机制在农产品安全中的应用进行综述。根据合成方法的不同分为物理和化学合成方法, 按照刺激反应的类型可以分为温度响应型、pH响应型、生物分子响应型、电场响应型和磁场响应型水凝胶等。重点总结了智能水凝胶在农产品安全领域应用于污染物的吸附分离、食源性致病微生物检测、霉菌毒素检测、农药与兽药残留检测、非法添加物检测及重金属检测的研究进展。最后, 讨论了智能水凝胶的发展前景, 旨在为其在农产品安全领域的应用提供参考。

智能水凝胶  /  农产品安全  /  生物传感  /  检测

Agricultural product safety form the foundation of constructing food supply systems. Smart hydrogels exhibit promising application prospects in agricultural safety analysis due to their stimuli responsiveness, mechanical stability, biocompatibility, and adjustable pore size. This review focused on the classification, preparation methods, responsive mechanisms and applications of smart hydrogels in agricultural product safety. Based on synthesis methods, they could be divided into physically cross-linked and chemically cross-linked hydrogels, while stimulus-responsive types included temperature-responsive, pH-responsive, biomolecule-responsive, electric field-responsive and magnetic field-responsive hydrogels. This study summarized their applications in contaminants adsorption/separation, foodborne pathogen detection, mycotoxin detection, pesticide/veterinary drug residue analysis, illegal additive identification, and heavy metal detection for agricultural product assurance. Development prospects of smart hydrogels are further discussed to provide references for their expanded utilization in agricultural product safety.

smart hydrogels  /  agro-product safety  /  biosensing  /  detection
王意涵, 魏书林, 王平, 乔家运, 李海花, 张维. 智能水凝胶技术在农产品安全检测中的应用研究进展. 食品安全质量检测学报, 2025 , 16 (13) : 170 -179 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250324005
Yi-Han WANG, Shu-Lin WEI, Ping WANG, Jia-Yun QIAO, Hai-Hua LI, Wei ZHANG. Research progress on the application of smart hydrogel technology in agro-product safety detection[J]. Journal of Food Safety & Quality, 2025 , 16 (13) : 170 -179 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250324005
农产品安全是构建多元化食物供给体系的重要基础。影响农产品安全的污染物种类众多, 如农药、兽药、微生物、真菌毒素、重金属等。检测技术是保障农产品安全的重要抓手, 包括仪器确证方法(如气相色谱-质谱法、液相色谱-质谱法等)以及快速检测方法(如酶联免疫吸附法、胶体金法等)。仪器方法灵敏度高, 但设备昂贵、技术门槛高; 快速检测方法检测速度快、应用简便, 但灵敏度和特异性仍有待不断提升。因此, 研发基于新材料的高效、灵敏快速检测技术对于保障农产品安全十分必要。
水凝胶是一种主要由水和高分子网络构成的材料, 具有良好的刺激响应性、机械稳定性、形状适应性和生物兼容性, 以及高比表面积和孔径可调等特点, 有望在农产品安全分析领域发挥重要作用[1]。智能水凝胶是水凝胶的一种特殊形式, 可以感知外界环境的细微物理、化学及生物变化(如温度、pH、光、离子强度、氧化还原反应、糖、酶等), 通过体积溶胀和收缩、形状弯曲、颜色变化, 或释放目标物等响应外界刺激[2]。智能水凝胶常分为温度响应型水凝胶、pH响应型水凝胶、生物分子响应型水凝胶、电场响应型水凝胶、磁场响应型水凝胶等[3]。智能水凝胶具有独特的生物兼容性和响应性, 在环境、生物医药、食品等领域具有巨大潜力, 可用于传感器件、分离分析、药物递送、细胞支架等研究。例如, 温度响应型水凝胶可用于响应体温变化触发药物释放, pH响应型水凝胶可用于靶向递送药物至肿瘤等特定微环境[4], 三磷酸腺苷(adenosine triphosphate, ATP)响应水凝胶用于水体中副溶血性弧菌的检测[5]。未来, 智能水凝胶在农产品安全领域具有广阔的应用前景, 如用于致病微生物、非法添加物等安全风险的分析, 重金属污染物的动态拦截与修复, 以及作物生长期农药残留动态检测等。
本文对智能水凝胶的分类及制备方法进行了介绍, 重点阐述了不同类型智能水凝胶在吸附净化、传感检测、原位和可视化检测等领域的研究进展, 并对智能水凝胶在农产品安全检测领域面临的挑战和发展方向进行了讨论, 旨在为其在农产品安全领域的应用提供参考。
智能水凝胶通常由天然或合成聚合物制成。常用的天然聚合物主要包括明胶(gelatin, GEL)、壳聚糖(chitosan, CTS)、透明质酸(hyaluronic acid, HA)、纤维素(cellulose)、DNA等; 合成聚合物主要包括聚乙二醇(polyethylene glycol, PEG)、聚乙烯醇(polyvinyl alcohol, PVA)、聚丙烯酸(polyacrylic acid, PAA)、聚丙烯酰胺(polyacrylamide, PAM)等。基于水凝胶形成交联的方式, 大致可分为物理交联和化学交联型水凝胶[6]
物理交联是指聚合物之间通过氢键、离子相互作用、疏水相互作用、主-客体相互作用和范德华力等形成水凝胶的过程[7]。物理交联通常采用冷冻-解冻循环、紫外线辐射或自组装等方法制备, 其交联网络是可逆的, 可通过调节温度、pH或离子浓度等环境因素调控。PVA是合成水凝胶的常用材料, 含有的大量羟基可与多种物质形成分子间和分子内氢键。BI等[8]通过对CTS-PVA碱性溶液进行冷冻-加热交替处理, 制备了基于多重氢键相互作用的高强度和高韧性CTS-PVA双重网络水凝胶。在第一层PVA网络和第二层聚糖网络中呈现的动态氢键赋予了水凝胶优越的压缩性能(60%-230 KPa)、拉伸性能(152 KPa-360%)、可重复使用性(5次循环后保持90.77%)以及抗溶胀性能。水凝胶中的疏水分子与疏水聚合物链连接, 在疏水位点引起2个或多个聚合物链产生分子间作用力而形成网络。FU等[9]构建了一种由亲水性聚(PEG)甲基丙烯酸甲醚酯[poly(poly (ethylene glycol) methyl ether methacrylate, PPEGMMA]作为中间嵌段和最高临界溶解温度(upper critical solution temperature, UCST)型热敏性聚(丙烯酰胺-共-丙烯腈)[poly(acrylamide-co-acrylonitrile), P(AAm-co-AN)]作为外嵌段组成的ABA线性三嵌段温敏型水凝胶, 其中疏水性的AN单元被用于调节聚合物链的亲水-疏水平衡, 以获得所需的UCST转变温度, 这类水凝胶在物质的持续释放以及可注射生物医用支架材料的制造等方面具有潜在的应用价值。主-客体相互作用利用主体物质具有的空腔结构包含客体分子时形成的相互作用。环糊精(cyclodextrin, CD)具有外亲水、内疏水的空腔结构和生物兼容性, 是常用的主体物质。LIU等[10]以羟丙基-α-CD为主体物质, PEG为客体物质, 将PEG高分子链穿过羟丙基-α-CD, 并以其为交联点串联形成具有较好抗拉强度和韧性的滑环水凝胶。与化学键和氢键相比, 范德华力相对较弱, 随着相互作用分子间的距离增加而迅速减小。为解决传统离子水凝胶传感器存在的内部蠕变不足, XU等[11]开发了一种由PVA和丙烯酰胺(acrylamide, AM)组成的具有低蠕变和高灵敏度柔性水凝胶传感器, PVA、AM和甘油交联形成的互穿双网络结构中的范德华力最大限度地减少了外部应力下的水凝胶蠕变, 使漂移比降低50%, 漂移率降低60%以上。物理合成水凝胶制备过程相对温和, 不引入有毒化学物质, 具有可逆性和较好的机械性能, 但结构稳定性和力学性能仍存在不足。目前, 研究人员通过不断设计新结构或新方法, 以期能够改善水凝胶的力学性能和稳定性。
化学交联水凝胶利用聚合物单体上的活性官能团与交联剂之间的活性基团通过共价键结合形成的交联聚合物网络, 例如自由基聚合、点击化学反应、酶催化等[7]。自由基聚合是制备化学交联水凝胶最常用的方法, 包括光引发聚合、辐射聚合以及化学引发剂聚合等。光引发聚合利用紫外光促使光敏化合物产生自由基, 引起单体聚合形成水凝胶。GUI等[12]通过光引发剂2-羟基-4’-(2-羟基乙氧基)-2-甲基丙酮[2-hydroxyl-4’-(2-hydroxyethoxy)-2-methylpropio phenone,12959]和PEG二丙烯酸酯[poly(ethylene glycol)diacrylate, PEG-DA]单体对巨噬细胞的直接渗透并通过随后的紫外照射实现细胞内的水凝胶化, 将活巨噬细胞转化为凝胶化巨噬细胞, 构建智能细菌检测传感器。辐射技术也是水凝胶合成的主要手段之一。伽马辐射、电子束和微波是目前研究最广泛的水凝胶辐照方法。γ辐射和电子束不需要任何引发剂或交联剂, 可以借此制造高纯度水凝胶产品, 并且可以在制备过程中实现灭菌, 有助于水凝胶在医疗领域的应用[13]。NIZAM-EL-DIN等[14]通过伽马辐射诱导, 构建了基于PVA和AM单体不同组合下的水凝胶。化学引发剂聚合常以氧化-还原体系为引发剂, 在氧化-还原系统中生成原始自由基, 从而引发单体聚合形成水凝胶[7]。YUAN等[15]以维生素C (vitamin C, VC)和过硫酸铵(ammonium persulfate, APS)作为氧化还原引发剂产生自由基, 纳米二氧化硅(nano-silicon dioxide, NSD)作为自由基稳定剂加速凝胶化, 制备出高性能酪蛋白-聚丙烯酰胺水凝胶, 具有高拉伸性、高强度和高可逆黏附性。点击化学是以碳-杂原子-碳键合成为基础完成的化学合成手段, 具有反应高选择性、模块化、条件温和、副产物少等特点[16], 为制备细胞培养、生物3D打印和药物释放水凝胶提供了化学工具库[17]。BAKER等[18]基于点击反应设计了肟交联HA水凝胶, 通过调控凝胶化速率与力学特性实现三维乳腺癌球体培养, 相较于基质胶或传统二维培养, 该HA-肟乳腺癌模型能维持与肿瘤异种移植物最为接近的基因表达特征。
温度响应型智能水凝胶是一种能够通过温度刺激引发可逆性体积相变或溶胶-凝胶转变的三维网络高分子材料, 其智能响应特性源于聚合物链中特定的热敏性官能团或分子间作用力的温度依赖性调控[19]。根据相变温度阈值的不同, 温度响应型水凝胶主要分为具有UCST和最低临界溶解温度(lower critical solution temperature, LCST)两大类别。UCST型水凝胶在低于临界温度时因氢键或离子相互作用增强而形成交联网络, 而在高温时解离呈现溶胶态, 其相变机制主要依赖于温度升高导致的熵驱动解离过程[20]。LCST型水凝胶在低温时通过亲水基团与水分子形成氢键而溶解, 当温度超过临界值后, 疏水基团主导分子内缔合引发脱水收缩[21]。两类材料均具有高度可调的响应温度(通过共聚单体比例或交联密度调控)、快速响应动力学(纳米级孔径结构设计)和生物相容性(天然/合成高分子复合)等特征[22]。UCST水凝胶在低温药物控释(如5-氟尿嘧啶在37 ℃肿瘤微环境中的靶向释放)和低温保护剂领域具有良好的应用潜力, LCST水凝胶则广泛应用于智能伤口敷料(体温触发的抗菌剂释放)、细胞培养支架(温度诱导的细胞片层剥离)和光学传感器(温敏光子晶体显色)等生物医学工程领域[23]
pH响应型水凝胶能通过溶胀和收缩的形变行为, 灵敏地响应环境pH变化。当周围介质发生pH变化时, 水凝胶聚合物骨架中的功能侧基发生电离, 引发水凝胶电荷密度的重新分布[24], 由此产生的带同性电荷(正或负)相邻聚合物链之间的静电排斥作用, 促使水凝胶整个聚合物网络吸水膨胀并改变形状[25]。pH响应型水凝胶可根据水凝胶网络中侧基的化学性质不同分为阴离子型水凝胶和阳离子型水凝胶。阴离子水凝胶的溶胀/收缩行为取决于其阴离子侧基的解离特性。只有当周围水溶液的pH超过水凝胶的酸解离常数(pKa)时, 这些阴离子基团才会解离并释放质子, 使原本电中性的水凝胶带负电荷。此时, 由静电排斥引发的渗透压会触发带电水凝胶的溶胀。相反, 含阳离子基团(如胺基)的阳离子水凝胶具有相反的响应特性, 即在较低pH环境(<pKa)下发生质子化作用并产生溶胀[25]。PAA功能性侧基为羧酸基团, 基于其pH响应特性引发的显著尺寸变化, PAAc水凝胶已广泛应用于生物驱动器领域[26]。其他pH响应型水凝胶如聚丙烯酰胺[poly(acrylamide), PAAm]基、聚甲基丙烯酸[poly(methacrylic acid), PMAA]基和PVA基水凝胶也常用于生物驱动器等智能水凝胶的开发应用。pH响应型水凝胶具有易操作性和对外界pH变化的高特异性响应优势, 已广泛应用于生物传感器和药物递送载体。但是如何提高其驱动开关状态的可控性仍是实际应用中亟待解决的关键问题。
电响应水凝胶可在外加电场作用下通过溶胀/收缩改变其几何形状和尺寸[27]。电响应智能水凝胶的响应行为常发生在电解质水溶液中, 即在电场刺激下, 水凝胶-电解质溶液体系中的可移动离子发生定向迁移, 从而引发水凝胶收缩。此外, 离子迁移会导致电荷分布不对称, 并沿电场方向形成离子浓度梯度, 由此产生的渗透压差将驱动水分子的电渗流运动。水凝胶在渗透压升高时溶胀, 降低时消溶胀[27]。电刺激响应智能水凝胶电场信号的幅值、频率和方向具有可精准调控性, 常见的电响应水凝胶材料包括CTS、PAA、丙烯酸4-羟基丁酯(4-hydroxybutyl acrylate, 4-HBA)以及聚(2-丙烯酰胺-2-甲基丙磺酸)[poly (2-acrylamido-2-methylpropanesulfonic acid), PAMPS]等[27]。CTS是由甲壳类动物外壳中富含的甲壳素制备的天然高分子聚合物。结合3D打印技术, 研究人员通过逐层堆叠法成功制备了CTS基电响应水凝胶驱动器, 因其增大的表面积-体积比加速了离子迁移, 在10 V电场刺激下展现出更快的弯曲速率和更大的弯曲幅度, 溶胀率可达70%[28]
磁响应水凝胶通常通过向水凝胶中掺入磁性响应物质来实现, 通过整合磁性材料, 原本无磁响应的水凝胶可被赋予对外界磁刺激的敏感性, 展现出磁致形变与运动特性, 可实现磁场调控下的可调谐、无线化响应驱动, 在人工肌肉、药物递送和细胞操纵等需要精密操控的领域展现出应用潜力[25]。目前已有多种磁性材料被引入磁响应水凝胶驱动器领域, 如Fe3O4纳米颗粒(Fe3O4 nanoparticles, Fe3O4 NPs)、Co纳米颗粒(cobalt nanoparticles, CoNPs)、NdFeB微颗粒和Fe微球等。然而, 磁性添加剂的生物兼容性和降解性问题仍是当前面临的主要挑战。Fe3O4纳米颗粒因其超顺磁性特性、生物兼容性和无细胞毒性等优势, 在生物医学领域应用尤为广泛。例如, 在开发肌肉替代材料时, 将Fe3O4微颗粒通过浓度梯度方式整合进入具有优异弹性的PVA水凝胶。当受磁场激活时, 磁性颗粒的梯度分布导致驱动器不同部位的偏转程度差异, 从而模拟人类多关节手指的运动模式[29]
具有对糖、蛋白质等生物分子刺激响应的水凝胶作为一种新型智能材料, 因其优异的生物学特性而广受关注。针对ATP酶、末端脱氧核苷酸转移酶等的刺激响应水凝胶已被用于细胞成像[30]、葡萄糖的可视化检测[31]等。具有ATP酶刺激响应的水凝胶体系中存在ATP时, 会导致凝胶-溶胶状态转变, 而ATP酶会导致ATP分解, 从而产生溶胶-凝胶状态转变。基于ATP酶的刺激响应性, 这类水凝胶可用于细胞质生物氧化过程的成像[30]。微生物本身也可以作为生物分子刺激水凝胶发生响应。研发兼具杀菌肽活性与刺激响应能力的水凝胶体系已成为热点。当存在致病微生物(如致病性金黄色葡萄球菌)时可刺激水凝胶结构变化释放抗菌肽, 在抗菌的同时促进伤口愈合[32]。农产品安全检测很多是针对其中的生物分子进行检测, 因此生物分子响应型智能水凝胶在农产品安全分析领域具有广泛的应用前景。
农产品安全问题存在于从农田到餐桌的全链条。开发适用于各环节不同场景的农产品安全检测技术是保障农产品安全的重要抓手。得益于优异的刺激响应性、生物兼容性、三维多孔结构、形状适应性、机械稳定性以及低成本等优势, 基于刺激响应性智能水凝胶的分析传感及保鲜指示技术已逐步应用于农产品安全分析领域, 主要针对食源性致病微生物、霉菌毒素、农药/兽药残留、非法添加物及重金属等目标物进行检测, 同时还可应用于污染物的吸附与分离等, 覆盖农产品生产全链条的主要环节。
水凝胶具有很强的亲水性却不溶于水, 因而在固液分离领域具有广泛的应用潜力。刘娜等[33]通过构建金属有机框架材料(metal-organic framework, MOF)掺杂的复合水凝胶(polyacrylamide-sodium alginate/metal-organic framework, PAAM-SA/MOF)以实现对养殖水体中孔雀石绿(malachite green, MG)的高效吸附与富集, 吸附率最高可达97%。海藻酸钠水凝胶作为天然高分子多糖基水凝胶, 富含羟基、羧基等官能团, 易被其他基团修饰。HUA等[34]通过采用离子交联法将磁性羟基磷灰石纳米颗粒(magnetic hydroxyapatite nanoparticles, MHNPs)包埋于海藻酸钠凝胶中, 成功制备出具有矮牵牛花粉结构的磁性水凝胶珠, 对MG和Pb²⁺的吸附容量分别达到208.06 mg/g和475.50 mg/g, 且在环境水样与果汁等实际应用场景中均展现出对MG和Pb²⁺的有效吸附去除。通过与不同识别元件、纳米材料等的结合, 可进一步增强水凝胶特异性识别、吸附靶标物质的能力, 实现在农产品安全中污染物的高效特异吸附。WANG等[35]以核黄素适配体和核黄素结合蛋白(riboflavin-binding protein, RBP)修饰聚(N-异丙基丙烯酰胺)(poly-N-isopropylacrylamide, PNIPAAm), 利用核黄素与核黄素适配体或核黄素结合蛋白的亲和相互作用, 选择性分离啤酒中的核黄素。得益于该智能聚合物的温度敏感特性, 所形成的复合物可便捷地从水相中分离, 有效选择性去除标准溶液及啤酒中的核黄素, 延长产品保质期和提升产品品质。果汁等饮料中常因原料中霉菌毒素的污染而导致产品中霉菌毒素含量超标。RANGARAJ等[36]通过构建鼠李糖乳杆菌(Lactobacillus rhamnosus)封装的动态交联角蛋白/CTS (keratin-chitosan, KC)水凝胶体系用于苹果汁中展青霉素(patulin, PAT)的脱除, KC水凝胶的三维网络结构可实现益生菌99.9%的固定化效率。在含25 mg/L PAT的模拟果汁体系中, 使用15 mg/mL的KC及KC-LR水凝胶于25 ℃处理6 h, PAT脱除率分别达85.2%和97.68%; 在真实苹果汁体系中, 二者脱除效率分别为76.3%和83.6%。包封益生菌的KC-LR水凝胶未对果汁品质产生负面影响, 且可重复使用, 有望成为解决果汁工业中PAT污染的解决方案。
农产品从田间到餐桌的各个环节都极易受到微生物的污染, 大肠杆菌、沙门氏菌、金黄色葡萄球菌等已成为影响农产品安全的主要微生物风险[37]。细菌主要通过静电相互作用、疏水键和氢键与水凝胶发生作用, 但这些相互作用不具有靶向性或特异性。因此, 常在水凝胶基质中添加酶、抗体、适配体和多糖等物质, 以增强其选择性和灵敏度。主动型传感器水凝胶凭借其固有特性能够感知周围细菌的存在。如细菌生长导致的pH变化、温度波动以及代谢酶和蛋白质分泌等外部刺激, 会通过改变水凝胶的孔径大小、交联度和离子组成等微观特性, 引发宏观结构的显著变化(如水凝胶溶胀或形变)。功能化水凝胶则是通过在水凝胶表面/网络中修饰具有细菌传感功能的元件来实现细菌检测。界面型传感水凝胶则是将水凝胶与独立的光学、机械或电学外置传感器界面结合, 构建稳健的细菌传感平台[38]
水凝胶具有的优异生物兼容性利于改性和修饰, 为生物活性物质提供了良好的存储平台, 推动了基于适配体、抗体等功能化水凝胶的传感器的开发应用。张彤等[39]基于醛基化磁珠(aldehyde magnetic beads, AMBs)、滚环扩增技术(rolling circle amplification, RCA)和DNA水凝胶构建了可视化适配体生物传感器, 可实现1 h内食品中最低浓度为4×103 CFU/mL的大肠杆菌O157:H7 (Escherichia coli O157: H7, E.coli O157: H7)的可视化检测。YU等[5]开发了一种基于离心管组装的目视荧光(visual fluorescence, FL)与微流控芯片联用的双模式智能水凝胶适配体传感器, 用于对养殖水体中副溶血弧菌(Vibrio parahaemolyticus)的现场快速检测。离心管盖修饰副溶血弧菌适配体实现目标菌富集, 管内水凝胶负载ATP适配体与金纳米簇(AuNCs)作为信号标签。当水中痕量副溶血弧菌被管盖特异性捕获后, 通过酶解反应释放ATP, 后者与水凝胶中的ATP适配体结合形成复合物, 同时释放AuNCs至液相进行双模式检测-ATP适配体复合物经微流控芯片定量, AuNCs通过荧光信号分析。荧光模式可在45 min内检出100 CFU/mL的副溶血弧菌, 微流控芯片检测灵敏度可达10 CFU/mL。水凝胶还可与拉曼光谱结合实现微生物的快速检测。YE等[40]开发了一种基于表面增强拉曼光谱(surface-enhanced Raman spectroscopy, SERS)的高灵敏度、高选择性大肠杆菌适配体传感器。利用大肠杆菌适配体功能化银纳米粒子(silver nanoparticles, AgNPs)修饰的CTS水凝胶作为SERS三维基底, 用于目标菌的特异性富集; 以负载拉曼信号分子4-巯基苯甲酸(4-mercaptobenzoic acid, 4-MBA)的大肠杆菌适配体修饰金纳米星(gold nanostars, AuNSs), 实现菌体的灵敏定量。通过AuNSs尖端结构、相邻纳米星间隙及金-银纳米粒子间空隙形成的多重热点区域, 产生显著的电磁场增强效应, 在无杂菌干扰条件下检出限可达3.46 CFU/mL, 动态线性范围3.2×101至3.2×107 CFU/mL, 可用于市售牛奶和果汁中大肠杆菌的定量检测。基于特异性标识物修饰的水凝胶可极大提升与细菌间的靶向识别, 结合新型水凝胶的研发并对其进行不同的功能化修饰, 将提升微生物传感检测能力。
pH响应型水凝胶已被整合至多功能水凝胶体系中, 并与微流控平台、电化学传感器及荧光系统结合应用。SHAIBANI等[41]选用静电纺丝法制备的pH敏感型PVA/ PAA [poly(vinyl alcohol)/PAA, PVA/PAA]水凝胶纳米纤维作为敏感层, 开发了一种基于便携式纳米纤维光寻址电位传感器(nanofiber-light addressable potentiometric sensor, NF-LAPS)的橙汁中大肠杆菌检测方法。该NF-LAPS系统可在1 h内成功检测大肠杆菌, 检出限为102 CFU/mL。水凝胶的高含水量和优异生物兼容性为细菌增殖提供了适宜环境, 推动了pH响应型水凝胶在细菌富集、原位定量/定性检测中的应用。
水凝胶良好的黏性和柔韧性使其在柔性传感器中具有很大的应用前景, 也成为细菌传感检测的发展趋势。LIN等[42]提出了一种复杂食品样本中无需前处理的快速、精准、无抑制核酸分析“水凝胶实验室”范式。交联PEG水凝胶通过纳米多孔结构赋予体系吸附-释放-分离-限域-自清洁5重功能, 凝胶内部进行微滴数字环介导等温扩增(loop- mediated isothermal amplification, LAMP)时, 其纳米结构可动态调控试剂存储与按需释放, 同时限域纳米环境有效促进酶促扩增反应。在生鲜果蔬样本中, 该方法可在20 min内完成大肠杆菌和伤寒沙门氏菌单细胞级精确定量(检出限1 CFU/mL)。基于柔性细菌纤维素水凝胶构建的弹性拭子也被开发用于叶面的大肠杆菌SERS原位检测和鉴别[43]
核酸检测在生物危害风险的现场检测中发挥了重要作用, 对植物、食品和环境样品上的核酸直接原位成像有助于病原风险的预警检测。YANG等[44]受细胞基质启发, 利用PEG作为原材料构建了仿生3D纳米限域水凝胶, 通过黏附在生物样本表面对表面核酸进行纳米限域束缚, 为水凝胶原位限域界面扩增(in situ space-confined interfacial amplification, iSCIA)提供了固定空间, 并结合人工智能深度学习模型对输出的荧光结果进行高分辨自动读取, 实现不同生物样本界面上多类别目标分析物原位成像分析, 检出限低至1拷贝/10 cm2。进一步将开发的水凝胶系统用于植物病原体的现场检测。PEG水凝胶与植物叶片表面紧密共形接触, 在水凝胶中预埋SYBR GREEN染料实现对叶片上链格孢菌(Alternaria alternata)感染情况的高分辨率原位成像。同时, 该水凝胶成像系统还被应用于检测鲜切生菜和梨表面大肠杆菌的分布与生长情况, 实现食品安全原位成像分析。
霉菌毒素污染是食品、农作物及其制品最主要的安全风险之一。赭曲霉毒素A (ochratoxin A, OTA)作为典型霉菌毒素, 在葡萄酒、坚果、啤酒、咖啡、谷物及小麦等农产品中广泛存在[45], 主要来源于曲霉属(Aspergillus)和青霉属(Penicillium)真菌。为提高OTA检测的灵敏度, HAO等[45]基于适配体识别技术, 结合RCA产物自组装的DNA水凝胶信号放大系统, 实现金纳米粒子(gold nanoparticles, AuNPs)在DNA水凝胶内的直接组装, 构建了用于OTA灵敏视觉检测的适配体传感器, 方法检出限达0.005 ng/mL, 且在啤酒样品中具有优异的检测回收率(92.8%~103.5%)。FAN等[46]构建了基于靶标响应型血红素封装与铜纳米簇(copper nanoclusters, CuNCs)功能化DNA水凝胶的双模式荧光-比色传感策略用于OTA的分析。通过在DNA交联的三维亲水网络结构中修饰荧光CuNCs, OTA与适配体连接链(Apt-linker)的特异性结合可调控水凝胶解体, 引发CuNCs荧光淬灭并释放包封的血红素。同时, OTA诱导Apt-linker构象转变形成G-四链体结构, 促使释放的血红素通过自组装形成具有过氧化物酶活性的G-四链体/血红素DNAzyme, 进一步催化过氧化氢(H2O2)引发的CuNCs荧光淬灭实现信号放大, 同时催化H2O2介导的3,3’,5,5’-四甲基联苯胺(tetramethylbenzidine, TMB)显色反应产生比色信号。该DNA-CuNCs水凝胶体系在荧光模式下检出限达3.49 pg/mL, 比色模式为0.25 ng/mL, 在大豆、啤酒和咖啡样品中OTA的检测回收率为95.6%~113.2%。HAO等[47]基于RCA产物自组装策略, 通过将适配体-互补序列-靶标分子的竞争性结合模式整合至DNA水凝胶体系, 成功构建用于啤酒中OTA检测的高灵敏荧光DNA水凝胶适配体传感器。该传感器线性检测范围为0.05~100 ng/mL, 检出限达0.01 ng/mL。
黄曲霉毒素主要由黄曲霉(Aspergillus flavus)、寄生曲霉(A. parasiticus)等曲霉属真菌产生, 全球范围内广泛分布于农作物种植、收获、储运及加工环节, 并在农产品、食品及动物饲料中普遍检出[48]。针对黄曲霉毒素B1 (aflatoxin B1, AFB1)的现场检测需求, ZHENG等[49]以DNA水凝胶为生物传感器基底、AFB1适配体为识别元件, 通过酶联信号放大策略构建了AFB1响应型适配体交联水凝胶传感器。样品中的AFB1与适配体发生竞争性结合, 引发水凝胶分解并释放包埋的辣根过氧化物酶(horseradish peroxidase, HRP), 引入核酸外切酶I促使AFB1从适配体上解离, 进而引发水凝胶二次分解释放更多HRP, 最终催化TMB与H2O2的显色反应。方法检出限4.93 nmol/L, 线性范围0~500 nM, 可用于花生油中AFB1的检测。CHEN等[50]将适配体整合至交联剂结构, 赋予水凝胶对AFB1的特异性识别能力, 同时将杂交链式反应(hybridization chain reaction, HCR)引入光子晶体(photonic crystals, PhCs)水凝胶体系, 成功实现通过HCR诱导PhCs光学信号定向转变, 并构建用于AFB1可视化定量检测的光子晶体-DNA水凝胶传感器。还有研究将AFB1响应性水凝胶与预载铂纳米粒子(platinum nanoparticles, PtNPs)的距离读数式体积条形芯片(volume barcode microfluidic chip, V-chip)联用, 应用于啤酒中AFB1检测[51]
基于水凝胶的传感方法也同样被用于伏马毒素(fumonisin, FBs)、玉米赤霉烯酮(zearalenone, ZEN)、T-2毒素(trichothecenes, TS)等霉菌毒素的分析检测。FBs主要由轮枝镰刀菌(Fusarium verticilliodes)和增殖镰刀菌(Fusarium proliferatum)产生, 其中伏马毒素B1(fumonisin B1, FB1)毒性最强且占比最高(约占总量的70%), 广泛存在于小麦、玉米、高粱及水稻等粮食作物中[52]。SUN等[53]利用卟啉基MOF (porphyrin-based MOF)具有的类过氧化物酶活性, 以及基于HCR构建的聚丙烯酰胺-DNA水凝胶对FB1分子的刺激响应性, 构建了刺激响应比色传感器用于玉米和小麦样品中FB1的测定, 方法的线性检测范围为0.05~100 ng/mL, 检出限低至0.024 ng/mL。ZEN是由各种镰刀菌属(Fusarium)产生的有毒次生代谢物, 污染多种农作物, 如玉米、谷物、大豆和饲料。LIU等[54]基于ZEN适配体与丙烯酰胺/聚二烯丙基二甲基氯化铵(poly dimethyl diallyl ammonium chloride, PDDA)静电作用形成的阳离子共轭骨架, 成功构建双模式ZEN响应性水凝胶体系。当ZEN存在时, 适配体-ZEN特异性结合引发水凝胶解离, 使包封的AuNPs释放至上清液, 通过肉眼可观测的显色变化实现定性检测。利用水凝胶释放的AuNPs高效催化TMB-H₂O₂显色反应, 实现低剂量可视化定量分析, 检出限达0.98 ng/mL, 在玉米与啤酒样品中的加标回收率分别为98.8%~101.3%与99.8%~101.5%。TS作为镰刀菌属产生的A型单端孢霉烯族中毒性最强的真菌毒素, 广泛存在于谷物类作物(小麦、燕麦、玉米、大麦及水稻)及其制品中[55]。CHEN等[55]通过PVA基质中原位钙离子介导的AgNPs组装策略, 成功构建水凝胶SERS芯片, 并开发出基于便携式拉曼光谱仪、无需复杂样品前处理的TS检测传感器, 能够实现5 min内对小麦、燕麦和大米中T-2毒素的快速检测, 检出限达到0.41 μg/kg。
基于智能水凝胶的传感器在农产品中霉菌毒素检测方面展现出广泛的应用前景, 通过识别元件创制、材料创新、传感机制优化、多功能集成等手段, 可实现高灵敏度、高特异性或可视化分析, 为不同应用场景下, 农产品中霉菌毒素的现场快速检测提供了技术手段。
以有机磷为代表的农药作为农作物害虫、杂草及病害防治的重要制剂, 在保障农业稳产增产方面发挥着关键作用。农业环境和农产品中有机磷等农药残留会引发环境与健康风险, 开发高效便携的农药现场检测方法具有重要意义。
基于水凝胶的刺激响应特性和高效负载能力, YAN等[56]通过将金纳米团簇@类沸石咪唑酯框架(AuNCs@ZIF)复合材料封装于双网络水凝胶中, 融合AuNCs的聚集诱导发光(aggregation-induced emission, AIE)效应、ZIF的刺激响应特性与水凝胶多孔网络结构, 开发出适用于农药残留分析的聚集诱导发光活性水凝胶圆片传感器, 在将水凝胶荧光图像转化为数字信号后, 可实现毒死蜱(chlorpyrifos, CPF)农药的精准定量(检出限0.2 ng/mL), 并可用于大白菜中CPF动态降解检测。LI等[57]通过将橙色荧光碳点/羟基氧化钴复合材料(CD/CoOOH)复合物封装于琼脂糖水凝胶中实现有机磷农药精准定量检测。乙酰胆碱酯酶(acetylcholinesterase, AChE)催化底物水解生成硫代胆碱, 诱导CoOOH分解触发荧光增强, 而有机磷农药通过特异性抑制AChE活性, 减少硫代胆碱生成, 导致荧光信号减弱。借助便携式光学设备将水凝胶荧光颜色转化为数字信号, 成功实现对模型农药对氧磷(parathion, PTN)的现场定量检测, 检出限达到10 ng/mL, 在梨汁、橙汁、苹果汁和大白菜等样品中具有良好的检测回收率(92.3%~107.8%)。该课题组同时也构建了基于金纳米团簇/MnO₂复合材料的水凝胶。通过将金纳米团簇/MnO₂复合材料固载于水凝胶基质, 催化邻苯二胺氧化反应产生具有内置校正功能的比率荧光信号, 结合乙酰胆碱酯酶催化反应与农药抑制效应, 在荧光颜色变化转化为数字信号后, 可灵敏检测对氧磷残留(检出限5.0 ng/mL)。研究人员还将该比率荧光水凝胶用于大白菜中PTN残留量动态变化的实时检测[58]
为提高样品中目标物的检测效率, 水凝胶微针正得到逐渐应用。YI等[59]开发了一种集成银纳米颗粒与透明质酸钠/PVA (HA/PVA)水凝胶微针贴片的SERS传感器, 通过微针阵列穿刺作用获取样品内部残留, 借助贴片基底黏附效应捕获表面残留, 在有效地放大农药残留拉曼信号的同时, 有效、快速地收集残留物, 突破传统技术无法同步检测表面与内部残留的局限。该传感器在茶叶基质的检测结果表明, 福美双(tetramethylthiuram disulfide, Thiram‌‌)和噻菌灵(thiabendazole, TBZ)农药残留检出限分别为10-7 mol/L和10-8 mol/L, 检测结果不受茶叶提取物的影响。检测过程具有微创性, 对农产品无损伤, 这种基于微针贴片的SERS传感器也可以扩展到其他动植物的安全健康检测。同时, 也可以用于对作物生长过程中农药浓度的实时检测。
抗生素类药物和抗真菌药等兽药在降低畜禽的发病率与死亡率、促进动物生长、改善动物产品品质和提高饲料利用率方面起到了重要的作用。但动物养殖中因科学用药知识的缺乏, 或受经济利益的驱使, 不合理用药与非法用药的现象仍很严重, 造成畜禽体内抗生素等兽药残留超标, 并最终经食物链危害人类健康。因此, 开发快速且准确的兽药残留检测方法对于保障动物源性食品安全至关重要。WANG等[60]构建了一种DNA水凝胶SERS传感器, 用于动物源性食品中链霉素(streptomycin, SM)残留的超敏检测。方法利用含DNAzyme (Pb-DNAzyme)的DNA水凝胶触发拉曼报告分子4-巯基苯甲腈(4-mercaptobenzonitrile, 4-MBN)的释放及信号放大, 并通过金纳米棒阵列进行检测, 检出限为4.85×10-3 nmol/L。牛奶和蜂蜜样品中SM的检测回收率范围为98.2%~117.3%, 也可用于鸡肉和奶粉中SM的快速检测。
卡那霉素(kanamycin, KANA)是常用抗生素之一, 也是动物源性食品及自然环境中常见的污染物。通过整合适配体的竞争结合模式, CHEN等[61]利用连接-滚环扩增生成的DNA水凝胶捕获未功能化的等离子体核壳纳米粒子。通过测量DNA水凝胶中捕获的等离子体核壳纳米粒子的SERS信号, 实现牛奶和蜂蜜中KANA的检测。DNA水凝胶中同步缠绕的磁珠赋予其磁响应性, 从而简化SERS信号测量过程, 检出限低至2.3 fmol/L。
基于水凝胶的三维多孔结构和纳米材料的刺激响应特性, 将农兽药浓度转化为物理响应信号(如比色、荧光、溶胶-凝胶状态变化), 实现农兽药即时定量检测, 将是未来研究方向之一。
克伦特罗(clenbuterol, CL)、莱克多巴胺(ractopamine, RAC)等都属于β-肾上腺素受体激动剂, 具有减少脂肪沉积并增加肌肉转化率功能。中国、欧盟均明令禁止CL、RAC等β-肾上腺素受体激动剂在动物养殖中使用[62]。构建“瘦肉精”类化合物超灵敏检测对保障畜产品安全和消费者健康具有重要意义。BIAN等[63]构建了基于金@钯纳米颗粒(Au@Pd)和DNA水凝胶的负载纳米酶生物活性水凝胶, 用于RAC的超灵敏光学检测。RAC适配体作为交联剂, Au@Pd纳米颗粒被均匀嵌入DNA水凝胶中。当RAC与适配体结合时, 水凝胶结构坍塌, 释放出嵌入的Au@Pd纳米颗粒, 并催化H2O2与TMB显色反应, 方法具有低检出限(7.39 ng/L)和宽检测范围(0.01~1000 μg/L), 在猪肉和进口牛肉样品中, 其检测回收率分别为94.3%~118.3%和94.3%~113.6%。
三聚氰胺(melamine, MEL)由于其高氮含量, 在宠物食品及婴幼儿奶粉中被非法添加以提高表观蛋白质含量, 曾导致2007年美国宠物食品污染事件及2008年中国婴幼儿奶粉掺假事件[64]。为实现MEL便携式灵敏检测, WANG等[65]通过将刺激响应型DNA水凝胶与微流控芯片结合, 开发了一种适用于牛奶和婴儿奶粉中MEL的即时检测方法。当存在MEL时, 其与适配体竞争性结合, 导致基于MEL适配体作为交联剂构建的DNA水凝胶解体并释放包覆的AuNPs, 从而实现MEL的目视检测与定量测量。
亚硝酸盐(nitrite, NIT)作为一种常见的食品添加剂, 被广泛用于各种加工肉制品, 如香肠、腊肠和火腿, 以防止食物变质和脂质氧化。考虑到NIT的潜在危害, 开发快速可靠的定量分析食品中NIT的技术对保障公众健康至关重要。CHEN等[66]以羧甲基CTS、聚多巴胺、海藻酸钠、聚乙烯亚胺和CuFe₂O₄为基材, 在室温下合成了一种新型的可注射多孔磁性水凝胶。正电性的聚乙烯亚胺通过静电吸引增强了对亚硝酸根(NO₂⁻)的吸附。采用多孔磁性水凝胶修饰的玻碳电极构建的电化学传感器对NIT的测定表现出较宽的线性范围(0.02~2250.00 μmol/L)和较低的检出限(3.60 nmol/L)。在脆皮炸猪肉和烤鸡样品中的加标回收实验显示优异回收率(91.01%~107.68%)。
在农产品安全监管中, 如何缩短样品前处理时间是开展安全快速检测的关键步骤。基于对MEL等的检测研究表明, 刺激响应型智能水凝胶的独特结构有利于简化农产品中非法添加物监管采样与检测流程。此外, 智能水凝胶的多形式信号输出能对目标物实现定性与定量检测, 在农产品安全生物传感领域展现出巨大潜力。
工业化导致的重金属污染不仅威胁果蔬种植和养殖水体环境, 土壤或水体中的铜(Cu)、镉(Cd)、铬(Cr)、汞(Hg)等重金属还会通过作物根系吸收进入果蔬可食部位, 或通过水体进入水产品体内, 并随着食物链进入人体而造成健康风险[67]。开展果蔬水产品中重金属残留检测, 对于保障农产品安全和消费者健康具有重要意义。
WANG等[68]将变性牛血清白蛋白(dBSA)与CdTe/CdS量子点偶联形成的CdTe/CdS@dBSA复合物组装并保留在PNIPAM水凝胶, 形成能够吸附和感知镉离子(Cd2⁺)的CdTe/CdS@dBSA-PNIPAM荧光水凝胶基底, 并以此建立了荧光-比色双模式检测系统, 其荧光检出限为2.88 nmol/L, 比色检出限为11.66 nmol/L, 可实现大米、茶叶、鱼、水体样品中Cd²⁺的定量检测。
Hg污染会损害人类大脑、肾脏和神经系统。含Hg量高的食物多来源于鱼类及其他海洋动物等海水生物。YI等[69]通过将菲咯啉修饰的四苯基乙烯衍生物(phenanthroline modified-tetraphenylethylene derivatives, DTPEP)与海藻酸钠水凝胶结合, 基于AIE特性及对Hg的高特异性构建AIE水凝胶汞传感器, 并可涂覆于手套、便利贴等不同载体上, 作为柔性传感器实现汞污染的便携式快速现场检测。通过基于灰度值的可视化结果分析对Hg2⁺定量检测, 检出限低至0.06 μmol/L, 检测时间不超过15 min。该方法在虾、柠檬、秋刀鱼和菠菜等实际样品中对Hg2⁺检测具有良好的回收率(90%~114%)。
基于智能水凝胶的重金属离子检测常不需要前处理步骤, 提高了检测效率。水凝胶基质的强韧力学性能赋予其可重复使用性, 降低了分析成本。未来, 构建可快速富集且可用于重金属离子实时检测的智能水凝胶将是主要的发展方向。
智能水凝胶的微观结构或理化性质可响应环境条件(如pH、离子组成、温度或光照等)的变化, 做出孔径变化(溶胀/收缩)、分子间作用力(吸引/排斥)或整体结构转变(凝胶-溶胶相变), 在农产品安全领域具有广泛的应用价值。然而, 基于水凝胶的智能生物传感器、营养素触发释放在农产品安全中的实际应用仍存在需解决的挑战。
(1)基于智能水凝胶开发新型超敏传感技术。用新型交联方法设计合成聚合物网络, 实现选择性、机械强度、导电性及对目标的生物/化学响应性等功能的目标精准调控, 开发聚合物结构与功能限制传感器; 将不同智能分子/材料引入水凝胶体系, 构建多样化生物传感器; 研究水凝胶与农产品基质的相互作用机制, 利用计算建模与虚拟仿真技术解析水凝胶的组分-结构-性能关系, 优化传感器结构设计, 提升传感器稳定性与选择性。
(2)研发基于刺激响应型水凝胶无损取样与分析检测技术。利用智能水凝胶良好的形状适应性和机械强度, 结合其多孔结构特性及对识别分子的高负载能力, 开发多类别靶标特异性或广谱性擦拭和微针贴片取样材料, 结合荧光、酶等信号放大机制, 构建适用于食品中抗生素、真菌毒素、非法添加物、微生物等危害因子的快速无损取样与分析技术, 实现“即贴即读”式分析实际应用; 结合水凝胶微针与高敏传感技术, 研发可穿戴植物/动物传感器, 实时检测植物/动物机体健康及风险因子赋存特征, 助力农产品安全源头控制。
(3)构建基于智能水凝胶的多靶标同步、多平台联合、无损分析平台。构建多风险目标检测平台, 满足多通道快速、同步、高灵敏检测需求; 将水凝胶传感器集成至芯片实验室或微流控系统, 推动便携式微型传感工具的研发; 结合表面增强拉曼光谱分析与水凝胶材料, 辅以金、银等纳米材料信号增强作用, 构建具有良好均匀性、稳定性和抗干扰性能的SERS基底, 提升SERS技术用于食品中抗生素、真菌毒素等风险物的检测灵敏度和重复性。进一步, 通过自动化和可编程的智能控制微流体装置实现形状均匀、可靠性和重复性强的SERS基底批量化制备, 强化水凝胶SERS开发应用。
(4)开发基于智能水凝胶的智慧检测平台。结合大数据与便携设备发展, 开发微型化、可穿戴智能装备及连续动态实时检测装置, 满足现场实时检测与快速监管需求; 强化与手机等智能设备结合, 推动其广泛应用于农产品安全控制, 实现对风险物的精准识别及其浓度动态追踪, 结合云平台数据处理, 为农产品安全智慧检测提供技术手段。
  • 国家重点研发计划项目(2022YFF0607903)
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2025年第16卷第13期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20250324005
  • 接收时间:2025-03-24
  • 首发时间:2026-01-12
  • 出版时间:2025-07-15
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  • 收稿日期:2025-03-24
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国家重点研发计划项目(2022YFF0607903)
作者信息
    1 天津农学院动物科学与动物医学学院, 天津 300392
    2 中国农业科学院农业质量标准与检测技术研究所, 北京 100081
    3 北大荒农垦集团有限公司宝泉岭分公司, 鹤岗 154211
    4 天津师范大学生命科学学院, 天津 300387

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*李海花(1981—), 女, 博士, 教授, 主要研究方向为兽医微生物学与免疫学。E-mail: ;
张维(1982—), 男, 博士, 副研究员, 主要研究方向为饲料质量安全分析与毒理学。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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