Advances in Research of Identification of Cnidii Fructus and Its Adulterants

In this paper,the traditional identification and modern identification technology of Cnidii Fructus and its adulterant were reviewed,and their advantages,disadvantages and practicability were summarized,to provide a reference for the rapid and accurate identification and quality evaluation of Cnidii Fructus.

Alkylene-functionality in bridged and fused nitrogen-rich poly-cyclic energetic materials:Synthesis,structural diversity and energetic properties

From the standpoint of chemical structures,the organic backbones of energetic materials can be classified into aromatic rings,nonaromatic rings,and open chains.Although the category of aromatic energetic compounds exhibits several advantages in the regulation of energetic properties,the nonaromatic heterocycles,assembling nitramino explosophores with simple alkyl bridges,still have prevailed in benchmark materials.The methylene bridge plays a pivotal role in the constructions of the classic nonaromatic heterocycle-based energetic compounds,e.g.,hexahydro-1,3,5-trinitro-1,3,5-triazine(RDX)and octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine(HMX),whereas ethylene bridge is the core moiety of state-of-the-art explosive 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane(CL-20).In this context,it is of great interest to employ simple and practical bridges to assemble aromatic and nonaromatic nitrogen-rich heterocycles,thereby expanding the structural diversity of energetic materials,e.g.,bridged and fused nitrogen-rich poly-heterocycles.Furthermore,alkyl-bridged poly-heterocycles highlight the potential for the open chain type of energetic materials.In this review,the development of alkyl bridges in linking nitrogen-rich heterocycles is presented,and the perspective of the newly constructed energetic backbones is summarized for the future design of advanced energetic materials.

Quantification of the adulteration concentration of palm kernel oil in virgin coconut oil using near-infrared hyperspectral imaging

The adulteration concentration of palm kernel oil(PKO)in virgin coconut oil(VCO)was quantified using near-infrared(NIR)hyperspectral imaging.Nowadays,some VCO is adulterated with lower-priced PKO to reduce production costs,which diminishes the quality of the VCO.This study used NIR hyperspectral imaging in the wavelength region 900-1,650 nm to create a quantitative model for the detection of PKO contaminants(0-100%)in VCO and to develop predictive mapping.The prediction equation for the adulteration of VCO with PKO was constructed using the partial least squares regression method.The best predictive model was pre-processed using the standard normal variate method,and the coefficient of determination of prediction was 0.991,the root mean square error of prediction was 2.93%,and the residual prediction deviation was 10.37.The results showed that this model could be applied for quantifying the adulteration concentration of PKO in VCO.The prediction adulteration concentration mapping of VCO with PKO was created from a calibration model that showed the color level according to the adulteration concentration in the range of 0-100%.NIR hyperspectral imaging could be clearly used to quantify the adulteration of VCO with a color level map that provides a quick,accurate,and non-destructive detection method.

Adulteration detection of plant protein beverages by UPLC-MS/MS based on signature peptide of allergen

Plant protein beverage adulteration occurs frequently,which may cause health problems for consumers due to the hidden allergens.Hence,a novel method was developed for authentication by ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS).Almond,peanut,walnut and soybean were hydrolyzed,followed by separation by NanoLC-Triple TOF MS.The obtained fingerprints were identified by ProteinPilotTM combined with Uniprot,and 16 signature peptides were selected.Afterwards,plant protein beverages treated by trypsin hydrolysis were analyzed with UPLC-MS/MS.This method showed a good linear relationship with R2>0.99403.The limit of quantification(LOQ)were 0.015,0.01,0.5 and 0.05 g/L for almond,peanut,walnut and soybean,respectively.Mean recoveries ranged from 84.77%to 110.44%with RSDs<15%.The developed method was successfully applied to the adulteration detection of 31 plant protein beverages to reveal adulteration and false labeling.Conclusively,this method could provide technical support for authentication of plant protein beverages to protect the rights and health of consumers.

Split Addition of Nitrogen-Rich Substrate at Thermophilic and Mesophilic Stages of Composting: Effect on Green House Gases Emission and Quality of Compost

Composting as a solution to the increasing generation of municipal solid waste (MSW), also contribute to GHGs emission when not controlled and could lack some basic nutrients, especially nitrogen. This study assessed the split-additions of nitrogen-rich substrate to composting materials and their effect on GHGs emissions as well as the quality of the composts. Nitrogen-rich substrates formulated from pig and goat manure were co-composted with MSW for a 12-weeks period by split adding at mesophilic (˚C) and thermophilic (>50˚C) stages in five different treatments. Representative samples from the compost were taken from each treatment for physicochemical, heavy metals and bacteriological analysis. In-situ CH4, CO2, N2O gas emissions were also analyzed weekly during composting. It was observed that all the treatments showed significant organic matter decomposition, reaching thermophilic temperatures in the first week of composting. The absence affects the suitable agronomic properties. All nitrogen-rich substrate applied at thermophilic stage (Treatment two) recorded the highest N, P and K concentrations of 1.34%, 0.97% and 2.45%, respectively with highest nitrogen retention. In terms of GHG emissions, CO2 was highest at the thermophilic stage when N-rich substrate was added in all treatment, while CH4 was highest in the mesophilic stage with N-rich substrate addition. N2O showed no specific trend in the treatments. Split addition of the N-rich substrate for co-composting of MSW produced compost which is stable, has less nutrient loss and low GHG emissions. Split addition of a nitrogen-rich substrate could be an option for increasing the fertilizer value of MSW compost.

A Pharmacognostical Study on Ardisia gigantifolia and Its Adulterants

[Objectives]The research aimed to study the characteristics of Ardisia gigantifolia and its adulterants Embelia scandens and Mappianthus iodoides for identification. [Methods] Through the trait identification method,powder microscopic identification method,TLC,inclusions detection and content determination,A. gigantifolia and its adulterants were contrasted. [Results]The morphological and histological characteristics of A. gigantifolia,E. scandens and M. iodoides were different from each other. Containing water,total ash,acid insoluble ash and other inclusions also had difference; the total triterpenoid saponins were respectively 122. 90 mg/g of A. gigantifolia,147. 052 mg/g of E. scandens,and 63. 06 mg/g of M. iodoides. [Conclusions] These methods are accurate and reliable,which could be used for the identification of A. gigantifolia and its adulterants.

Molecular Identification of Chinese Materia Medica and Its Adulterants Using ITS2 and <i>psbA-trnH</i>Barcodes: A Case Study on Rhizoma Menispermi

Rhizoma Menispermi, derived from the rhizoma of Menispermum dauricum DC., is one of the most popular Chinese medicines. However Rhizoma Menispermi is often illegally mixed with other species in the herbal market, including Aristolochia mollissimae Hance, which is toxic to the kidneys and potentially carcinogenic. The use of DNA barcoding to authenticate herbs has improved the management and safety of traditional medicines. In this paper, 49 samples belonging to five species, including 34 samples of M. dauricum, from different locations and herb markets in China were collected and identified using DNA barcoding. The sequences of all 34 samples of Rhizoma Menispermi are highly consistent, with only one site variation in internal transcribed spacer 2 (ITS2) of nuclear ribosomal DNA and no variations in the psbA-trnH region. The intra-specific genetic distance is much smaller than inter-specific one. Phylogenetic analysis shows that both sequences allow the successful identification of all species. Nearest distance and BLAST1 methods for the ITS2 and psbA-trnH regions indicate 100% identification efficiency. Our research shows that DNA barcoding can effectively distinguish Rhizoma Menispermi from its adulterants from both commercial and original samples, which provides a new and reliable way to monitor commercial herbs and to manage the modern medicine market.

Drug adulteration analysis based on complexation with cyclodextrin and metal ions using ion mobility spectrometry

Drug adulteration and contamination are serious threats to human health therefore,their accurate monitoring is very important.Allopurinol(Alp)and theophylline(Thp)are commonly used drugs for the treatment of gout and bronchitis,while their isomers hypoxanthine(Hyt)and theobromine(Thm)have no effect and affect the efficacy of the drug.In this work,the drug isomers of Alp/Hyt and Thp/Thm are simply mixed withα-,β-,γ-cyclodextrin(CD)and metal ions and separated using trapped ion mobility spectrometry-mass spectrometry(TIMS-MS).TIMS-MS results showed that Alp/Hyt and Thp/Thm isomers could interact with CD and metal ions and form corresponding binary or ternary complexes to achieve their TIMS separation.Different metal ions and CDs showed different separation effect for the isomers,among which Alp and Hyt could be successfully distinguished from the complexes of[Alp/Hyt+γ-CD+Cu–H]^(+)with separation resolution(RP–P)of 1.51;whereas Thp and Thm could be baseline separated by[Thp/Thm+γ-CD+Ca–H]^(+)with RP–P of 1.96.Besides,chemical calculations revealed that the complexes were in the inclusion forms,and microscopic interactions were somewhat different,making their mobility separation.Moreover,relative and absolute quantification was investigated with an internal standard to determine the precise isomers content,and good linearity(R^(2)>0.99)was obtained.Finally,the method was applied for the adulteration detection where different drugs and urine were analyzed.In addition,due to the advantages of fast speed,simple operation,high sensitivity,and no chromatographic separation required,the proposed method provides an effective strategy for the drug adulteration detection of isomers.

熟驴肉掺假近红外定性及定量检测

驴肉风味绝佳、营养丰富,价格高昂且供应量低。驴肉火烧等熟驴肉中掺假马肉、骡子肉等其他肉类的问题亟待解决。为实现熟驴肉样品在不同掺假比例下的定性定量分析,以10%为梯度,分别制备驴肉含量为0%~100%的驴马掺假和驴骡掺假样品,并在4000~12500 cm^(-1)光谱范围采集样品光谱。针对熟驴肉掺假问题,采用线性判别分析、支持向量机以及广义回归神经网络的方法结合平滑算法(5点、15点、25点)、多元散射校正(MSC)、标准正态变量变换(SNV)、基线校正(Baseline)、归一化和去趋势化(Detrend)等预处理方法建立了近红外鉴别模型。采用偏最小二乘回归(PLSR)、反向传播神经网络(BP)方法结合以上预处理方法分别对熟驴肉掺假样品建立定量模型检测驴肉含量。SNV预处理结合支持向量机对熟肉碎掺假样品鉴别模型结果较优,校正集和预测集判别正确率为98.70%和94.78%;Detrend预处理结合线性判别分析的熟肉糜掺假样品鉴别模型结果较优,校正集和预测集的判别正确率分别达到98.47%和96.23%。建立定量模型进行掺假样品中驴肉含量的检测,BP模型相较于PLSR模型均取得较好的结果,具有较高的决定系数(R^(2))、相对分析误差(RPD)和较低的均方根误差(RMSE)。对于熟肉碎掺假样品,驴骡掺假样品集在Detrend处理后的BP模型结果较好,交叉验证集以及预测集的R^(2)、RMSE、RPD分别为0.971、0.067、5.844,0.980、0.086、6.984;驴马掺假样品集在归一化预处理后BP模型结果较好,各项参数分别为0.997、0.032、18.026,0.982、0.089、7.454。对于熟肉糜掺假样品,经Detrend预处理的BP模型结果均较优,驴骡掺假样品最佳定量模型的参数分别为0.982、0.041、7.470,0.986、0.103、8.452;驴马掺假最佳模型参数分别为0.986、0.036、8.348,0.961、0.101、5.044。结果表明,近红外光谱结合不同的建模算法实现了不同比例掺假的熟驴肉样品快速无损检测和鉴别,能够用于此后熟驴肉掺假的定性、定量分析。

肉制品中马源性成分重组酶介导链置换等温扩增实时检测方法的建立及应用

目的:建立一种快速鉴定肉及肉制品中马源性成分的重组酶介导链置换等温扩增实时检测方法。方法:以马源性ATpase 6基因为靶基因设计多组特异性引物和Exo探针,通过引物筛选及反应参数优化,建立一种采用重组酶介导链置换等温扩增技术检测马源性成分的方法,并对该方法进行特异性、灵敏度和稳定性验证,同时通过对不同掺入比例混合样品、不同加工工艺模拟样品和市售样品进行检测,分析方法的检出限、适用性和准确性。结果:该方法反应迅速、特异性强、灵敏度高。可在39℃恒温条件下16min内完成反应;对23种非目标源性具有良好特异性;目标DNA的检测灵敏度可达到1.8copies/μL水平;对生肉的检出限为0.01%(质量分数,下同),对熟肉制品的检出限为0.1%;对90份市售样品进行检测,结果与标准方法一致。结论:建立的重组酶介导链置换等温扩增方法可用于肉及肉制品中马源性成分的掺假鉴别检测。

酸枣仁中掺理枣仁的高效液相色谱法鉴别方法研究

目的 建立测定酸枣仁和理枣仁中6’’’-芥子酰斯皮诺素含量的高效液相色谱法(HPLC),以鉴别酸枣仁中掺伪理枣仁。方法 2020年12月至2022年12月,采用HPLC法,选用Agela Venusil ASB C18柱(4.6 mm×200 mm,5μm);以乙腈-0.2%冰醋酸水溶液为流动相梯度洗脱,对酸枣仁及理枣仁中6’’’-芥子酰斯皮诺素的含量进行分析测定;检测波长:335 nm;体积流量:1.0 mL/min,柱温为30℃。结果 6’’’-芥子酰斯皮诺素在2.32~138.96μg/L(r=1)内呈良好的线性关系。理枣仁平均加样回收率为97.5%,相对标准偏差(RSD)为1.5%。酸枣仁平均加样回收率为97.8%,RSD为1.7%。6’’’-芥子酰斯皮诺素在酸枣仁中含量范围为0.003 3%~0.005 1%,在理枣仁中含量范围为0.050 6%~0.066 0%。结论 建立的6’’’-芥子酰斯皮诺素HPLC含量测定分析方法灵敏度高、专属性强、重现性好,可用于酸枣仁中掺伪理枣仁的鉴别研究。

基于特级初榨橄榄油两种不同特性的DSC掺假分析方法研究

该文基于油脂物理特性与氧化稳定性2种特性,利用差示扫描量热法(differential scanning calorimetry,DSC)对市面上常见的特级初榨橄榄油(extra virgin olive oil,EVOO)中大豆油掺假问题进行研究。在物理特性方面,采用DSC冷却曲线来分析EVOO掺假。随着大豆油掺假比例升高,油样在-40~-60℃结晶焓值ΔH由EVOO的29.78 J/g减小为40%掺假混合油的6.133 J/g,对EVOO质量比构建的一元回归方程Y=57.556X-28.44(R2=0.997)。在氧化稳定性方面,氧化温度160℃下,不同油样诱导氧化时间随大豆油掺假比例上升逐渐变短,由EVOO的25.8 min逐渐减小为40%掺假混合油的17.8 min,Y=-19.4X+25.64(R^(2)=0.996),掺假模型相关性较好。这2种DSC检验掺假分析方法都能有效鉴别EVOO中大豆油的掺假且各有特点,可根据实际情况选取合适的方法更好处理EVOO掺假问题。

紫外光谱结合BP神经网络算法建立食用油掺伪煎炸油的快速鉴定模型

为建立一种快速食用油掺伪煎炸油检测方法,采用紫外光谱法鉴别其掺伪,本研究选取大豆油、玉米油和葵花籽油为代表分别煎炸,在纯油中掺入相应煎炸时间0~6 h及掺假梯度0%~90%的煎炸油制备掺伪油样,进行紫外光谱及二阶导数预处理,经处理后的光谱特征峰与BP(Backpropagation)神经网络算法结合建立食用油掺伪煎炸油模型,对掺入煎炸油类别、煎炸时间和煎炸油含量进行鉴别分析。结果表明二阶导数预处理后掺伪煎炸油的光谱特征峰中大豆油为446、462 nm、玉米油为268、274 nm、葵花籽油为280、288 nm,根据其特征峰位与峰值建立Levenberg–Marquardt算法(LMA)、动量梯度下降法(MGD)及弹性梯度下降法(EGD)掺伪模型识别率分别为98.15%、91.67%、95.52%。

气相色谱法测定五加皮中7种掺伪香精

目的建立气相色谱法测定五加皮中7种香精成分的分析方法。方法对提取溶剂、分流比及色谱柱型号等参数进行考察,利用氢火焰离子化检测器(flame ionization detector,FID)检测,采用外标法定量分析。结果将乙酸乙酯作为提取溶剂,CD624毛细管色谱柱分离,分流比为5∶1条件最优,7种香精成分能实现完全分离,线性关系良好,相关系数r均大于0.999。平均加标回收率为87.33%~93.66%,相对标准偏差(n=6)均低于5%。结论该方法简单、快速、准确,可满足五加皮中7种香精成分的检测。

拉曼光谱对茶油三元体系掺伪检测研究

该研究采用拉曼光谱技术对茶油三元体系掺伪进行定量检测研究,通过对比不同预处理方法、建模方法及优化算法的优劣,确定最优的大豆油、玉米油、茶油的多元掺伪检测模型。利用一阶微分、二阶微分、多元散射矫正、标准正态变换等不同预处理方法消除外界因素对光谱的影响,竞争性自适应重加权算法提取特征光谱波段,通过偏最小二乘回归和支持向量机建立茶油掺伪检测模型,分别采用网格搜索法和粒子群算法对支持向量机进行优化。基于标准正态变换预处理后所建立模型效果最佳,大豆油和茶油的最佳预测模型为基于粒子群算法优化的支持向量机,玉米油的最佳预测模型为基于网格搜索法优化的支持向量机,大豆油、玉米油和茶油的预测集决定系数R2和预测均方根误差分别为0.9986、0.9994、0.9999和2.73%、1.62%、0.40%。该研究确定了最优的大豆油、玉米油、茶油的多元掺伪检测模型,针对市场茶油的掺伪检测,基于拉曼光谱分析和优化算法的支持向量机模型为茶油的无损快速定量检测提供了一定的参考和借鉴。

红外与拉曼光谱技术对食用油掺伪检测研究进展

食用油是人们日常饮食中的必需品,因种类、产地和营养成分等因素不同而价格差异悬殊。不法商家为追求经济利益,将廉价食用油以次充好掺入优质食用油中,损害了消费者合法权益,因此研究食用油掺伪的快速检测方法至关重要。近些年,光谱技术以其简便、快速、无损、低成本等优点成为食用油掺伪的重要检测技术。文章基于近红外、中红外光谱法和拉曼光谱法的基本原理、优缺点以及互补关系,综述了近年来红外和拉曼光谱技术在橄榄油、山茶油等食用油掺伪检测中的研究进展,总结了几种光谱技术在食用油掺伪检测方面存在的问题,并对未来的检测发展方向进行了展望。

基于多尺度与注意力机制的毛尖茶分类及掺假程度

针对消费者在生活中难以区分毛尖茶品种及掺假程度多少的问题,提出了一种基于多尺度特征提取与高效通道注意力机制相结合的网络模型.在DenseNet121的基础上使用多尺度特征提取结构替换原来单一的卷积核,丰富特征层信息,在模型的密集连接块中引入ECA-Net注意力机制,增强有效特征信息的传递,而后,对模型的参数进行调优,进一步提高模型的识别性能.结果表明:改进后的MS-ECA-DenseNet121-C分类模型在收集的8个类别的毛尖种类及掺假种类数据集上的识别准确率达到了96.95%,可以有效鉴别毛尖茶品种的真实性,且改进后的模型大小仅为27.3 MB,便于部署于手机端,在茶叶识别领域具有一定的应用价值.

高光谱技术在牛肉丸复合掺假类型鉴别中的应用

肉制品加工过程的复杂性给肉制品掺假检测带来了巨大的挑战。基于高光谱技术,对不同比例的猪肉-鸡肉复合掺假牛肉丸进行了掺假类别判别分析,尤其首次提出了对熟牛肉丸复合掺假的快速检测。为建立模型,分别在牛肉糜中加入不同比例(20%、40%和80%)的猪肉/鸡肉,获得单一掺假样品。并将猪肉和鸡肉按2∶8、5∶5和8∶2的比例混合,在20%、40%和80%比例下进行复合掺假。此外,还制备了油炸掺假牛肉丸,以检验分类模型的适用性。对采集的掺假样本高光谱数据,经五种方法预处理后建立基于极限学习机分类(ELMC)和支持向量分类(SVC)的掺假鉴别模型。此外利用连续投影算法(SPA)、竞争性自适应重加权算法(CARS)分别提取特征波长并建立相应简化模型。研究表明:基于全波长建立的生/熟牛肉丸掺假类别检测模型SVC性能均优于ELMC。而基于特征波长建立的简化模型ELMC性能优于SVC。对生牛肉丸分类判别,利用SPA筛选出的44个特征波长建立的ELMC模型性能最优,其校正集和预测集的分类准确率均为97.17%。基于CARS筛选出的38个特征波长建立的ELMC模型对熟牛肉丸具有最高的分类性能,其校正集和预测集的分类准确率分别为97.17%和96.23%。因此高光谱技术可以对生肉和熟肉的复合掺假类型进行有效、快速、准确的鉴别,为便携式检测设备的研制奠定了理论基础。

基于贝叶斯优化的JADE-SVM中红外食品掺伪判别模型

开展了独立成分分析(independent component analysis, ICA)联合支持向量机(support vector machine, SVM)模型对食品掺伪的判别.通过傅里叶变换红外光谱仪获得食用植物油(正品油、掺伪油和炸货油)以及奶粉(纯奶粉和掺三聚氰胺奶粉)的中红外光谱,首先,探究不同的光谱预处理方法对所建立模型的影响,经考察选取归一化结合移动平滑对光谱进行预处理;然后采用特征矩阵联合近似对角化(joint approximate diagonalization of eigenmatrices, JADE)方法提取光谱特征信息,其结果优于主成分分析对特征信息的提取效果;通过Kennard-Stone算法划分训练集和测试集,利用贝叶斯优化(Bayesian optimization, BO)对SVM模型参数进行优化.经考察,所构建的JADE-BO-SVM模型对掺伪食品的识别准确度达到100%,该法可为食品掺伪的高效、准确鉴别提供新的途径和思路.

基于同步荧光技术的牛肉中掺杂猪肉鉴别方法研究

牛肉是我国重要的食用肉品类,近年来随着人们对牛肉需求的不断增加,将猪肉冒充或添加在牛肉中出售的现象也日益严重,亟需简单、快速的检测肉品掺假的方法。首先分析了牛肉和猪肉的三维荧光光谱特征差异,确定同步荧光的波长差;采用激发-发射固定波长差为160 nm的同步荧光光谱,对牛肉掺杂猪肉的情况进行了定性判别和定量分析。以测试集、验证集和预测集样本的判别正确率作为定性判别模型的评价指标;以相关系数(r)、校正均方根误差(RMSEC)和预测均方根误差(RMSEP)作为定量分析模型的评价指标。实验结果表明:牛肉和猪肉的三维荧光光谱有显著差异,牛肉在Ex/Em为270/320、330/400、350/500、430/515和410/570 nm处有荧光峰,猪肉的三个荧光峰分别在Ex/Em为270/320、330/400和430/515 nm处。设置同步荧光波长差为160 nm,能采集到牛肉的3个荧光峰,且其中两个位于峰顶。牛肉、猪肉、掺假肉SVM定性判别模型的校正集准确率为97.56%,预测准确率可达92.31%。对比了无处理、MSC处理和SNV处理的牛肉中猪肉掺加量PLS预测模型,无处理的PLS模型最优,其rc、rp、RMSEC和RMSEP分别达到0.9786、0.9590、0.0597和0.0927。基于同步荧光技术结合SVM和PLS的牛肉掺假猪肉定性判别和定量分析检测模型具有较高识别率和检测精度,可以较为准确、快速地检测牛肉中是否掺杂猪肉。