小麦霉菌侵染程度电子鼻快速检测方法的初步研究

本研究利用电子鼻气体传感器技术,初步建立了小麦霉菌侵染程度定性定量同步分析方法。小麦样品经辐照杀菌后接种5种谷物中常见有害霉菌,于85%相对湿度和28℃的环境中储藏至重度霉变。在样品储藏的不同阶段,选取时间节点0、1、3、5和7 d采集其电子鼻气味响应信息,建立了其响应信号和霉菌侵染程度的相关关系模型。结果显示,依据带菌量的不同,基于电子鼻信号的主成分分析法(PCA)可成功区分未霉变[2.7 log(CFU/g)]、轻度霉变[2.7～4 log(CFU/g)]与重度霉变[4 log(CFU/g)]的小麦样品;线性判别分析(LDA)对受单一霉菌侵染的小麦样品霉变程度的识别率达90.0%以上,对所有小麦样品的识别率达84.0%。偏最小二乘回归模型(PLSR)对小麦菌落总数的模型决定系数(R_p~2)和预测误差(RMSEP)及相对分析偏差(RPD)分别为0.852,0.504 log(CFU/g)和2.30。结果表明,利用电子鼻技术实现小麦霉菌侵染程度的快速识别是可行的。下一步应不断补充不同来源的小麦样品,以不断提高模型的精度和适用性。     

不同生产流通环节花椒霉菌污染情况调查研究

对来源于不同生产流通环节花椒样品的霉菌污染情况和毒素残留情况进行了分析。结果表明:实验所采集的25个样品中,68%存在霉菌总数超标,粉末样霉菌污染程度明显高于颗粒样,菌落总数达3.4×103 cfu/g;塑料密闭包装条件下,4℃冷藏样品污染霉菌菌落总数较常温储藏的高2~10倍,达2.4~6.6×103 cfu/g;样品中黄曲霉素和赭曲霉素含量与霉菌污染程度存在一定的正相关性,辐照处理能够有效减少花椒中活菌数目,但对霉菌毒素含量影响较小。     

霉变玉米气体传感器阵列快速检测

玉米易受霉菌感染发生霉变,影响食用安全。快速测定玉米霉变程度是控制其危害的前提。本研究拟利用基于气体传感器阵列的电子鼻技术,获取不同霉变程度玉米的特征气味信息,建立玉米霉变程度快速检测方法。辐照灭菌玉米分别接种5种谷物中常见有害霉菌,并于28 ℃和85%相对湿度环境中储藏15 d直至严重霉变。在第0、6、9、12和15 d,采集样品的气味信息的电子鼻特征响应信号,建立了玉米霉变程度的定性定量模型。结果表明,主成分分析(PCA)法可成功区分不同霉变程度的玉米样品。线性判别分析(LDA)对受单一霉菌侵染的不同霉变程度玉米样品的平均识别率达93.3%以上,全部样品达76.7%。样品中菌落总数的偏最小二乘回归分析(PLSR)模型的预测决定系数(R_p2)达0.777,预测均方根误差和相对分析偏差(RPD)分别为0.981 log CFU/g和2.12。结果表明,应用电子鼻技术快速检测玉米霉变具有一定可行性,下一步需要不断扩大样本量以提高方法的精度和可靠性。     

低盐固态酿造酱油生产过程中黄曲霉毒素B_1和微生物的动态变化

以低盐固态酿造酱油为研究对象,跟踪监测了酱油酿造过程中水分含量、水分活度、氨基态氮、总酸、微生物(菌落总数、霉菌、酵母菌、产黄曲霉毒素B1的霉菌)、黄曲霉毒素B1(AFB1)的动态变化,结果发现成品酱油中的AFB1 50％来源于原料,50％源于制曲过程中污染的产毒菌在发酵前期产毒;蒸煮、制曲、发酵、淋油四阶段均对AFB1有一定的去除作用,但生产结束后,仍有52.04％的AFB1会从酱醅中迁移到成品酱油中,所以需针对污染源采取相应措施控制酿造酱油中AFB1的污染.     

谷物霉菌挥发性物质的电子鼻与GC-MS检测研究

为建立粮食受霉菌污染的快速检测方法,本研究利用电子鼻与气相色谱质谱联用(GC-MS)技术对6种谷物中常见霉菌在不同生长阶段(1、2、5、13 d)的特征挥发性气味物质进行了检测分析。GC-MS结果显示不同霉菌的挥发性物质成分存在差异,且在生长后期差异更加显著。基于电子鼻信号的主成分分析(PCA)法能够有效区分生长中后期(5、13 d)不同菌属的霉菌样品。线性判别分析(LDA)和偏最小二乘判别分析(PLS-DA)模型对黄曲霉类、寄生曲霉类和青霉类样品的整体判别正确率分别达到100%和97.4%。结果表明,运用电子鼻与GC-MS技术对粮食霉菌污染情况进行快速鉴定具有一定可行性。     

基于光谱和气味特征信息的霉变大米无损检测

为快速鉴定大米霉变程度,本研究运用近/中红外光谱和电子鼻分析技术,建立了大米有害霉菌侵染种类与霉变程度的同步识别方法。首先,将4种谷物中常见有害霉菌分别接种在灭菌大米样品上,将样品于28℃和80%RH环境条件下储藏10 d。其次,样品从接种霉菌起,选取时间节点0、2、4、7、10 d,获得其近/中红外光谱和电子鼻气味特征信息。结果显示,受不同霉菌侵染大米样品的光谱和气味整体信息存在差异,到储藏后期差异更加显著。结合主成分分析和线性判别分析法,近/中红外光谱和电子鼻对受不同霉菌侵染大米样品的整体识别率分别为86.0%、86.0%、92.0%。大米霉变程度随储藏时间逐渐加深,近/中红外光谱和电子鼻对感染单一霉菌样品霉变程度的判别正确率达97.5%、98.75%、100%,多种霉菌感染的判别正确率为80.0%、87.5%、95.0%。结果表明,利用光谱和气味特征信息实现大米霉变的快速检测具有可行性,电子鼻在霉变大米特征挥发性气味的识别方面更具优势。     

2017年上半年我国部分地区饲料及饲料原料中霉菌毒素的污染状况分析

应用酶联免疫吸附法结合高效液相色谱对我国部分地区饲料及原料中黄曲霉毒素B1(AFB1)、玉米赤霉烯酮(ZEN)和脱氧雪腐镰刀菌烯醇(DON)3种霉菌毒素的含量进行检测。结果表明：356份样品中AFB1、ZEN和DON检出率分别是87.8%、95.0%和98.3%,平均含量分别为11.2、689.0和1 855.2 μg/kg,说明我国部分地区饲料及饲料原料霉菌毒素污染比较普遍。玉米、玉米副产物、配合饲料和粕类中ZEN和DON污染较严重,AFB1污染主要存在于粕类中,青贮料及发酵料中3种霉菌毒素的污染程度相对较轻,但污染范围较广,建议饲料生产企业应加强对饲料和饲料原料的品控管理。     

2019年饲料原料霉菌毒素污染状况调查

目的 调查分析2019年饲料原料霉菌毒素污染状况。方法 采用胶体金免疫层析法或上转发光免疫分析(up-conversion immunoassays, UPT)法对安佑集团各分子公司所采购的大宗饲料原料中呕吐毒素、玉米赤霉烯酮和黄曲霉毒素B1含量进行快速检测, 2019年度共检测饲料原料样品20918份。结果 对比安佑集团企业标准, 2019年饲料原料霉菌毒素污染总超标率为3.2%。饲料原料霉菌毒素污染整体情况由重转轻, 上半年污染较重主要是由于麸皮及次粉霉菌毒素污染超标所致, 下半年霉菌毒素污染程度整体较轻, 但9月玉米和玉米干酒糟及其可溶物(distillers dried grains with soluble, DDGS)的玉米赤霉烯酮(zearalenone, ZEN)污染情况较重, 其中DDGS达重度污染; 从产地来源看, 2019年全国各产地麸皮和次粉呕吐毒素(vomitoxin, DON)污染较重; 河南产地米糠黄曲霉毒素B1(aflatoxins B1, AFB1)及四川产地米糠ZEN达重度污染; 山东、江苏、云南、安徽产地玉米AFB1及安徽产地玉米DON达重度污染; 且饲料原料中的霉菌毒素并非单一存在, 多数情况下是多种毒素共存。结论 与2018年饲料原料霉菌毒素污染调查数据(未公开发表)相比, 2019年原料污染程度较轻。     

基于电子鼻技术的糙米黄曲霉毒素污染快速检测方法研究

为验证电子鼻技术用于粮食真菌毒素污染快速检测的可行性,本研究利用Fox3000型电子鼻对受黄曲霉毒素侵染的糙米样品的挥发性物质进行了检测分析,建立了电子鼻响应信号与黄曲霉毒素水平的相关关系模型。结果显示,偏最小二乘判别分析(PLS-DA)法可较好区分不同黄曲霉毒素含量水平的糙米样品,模型的留一交互验证正确率高于80%。PLS回归分析显示电子鼻响应信号与糙米中黄曲霉毒素B_1、B_2、G_1、G_2及总量之间呈现较高相关性,其中对黄曲霉毒素B1的预测精度最高,预测相关系数和均方根误差分别达到0.808和127.3μg/kg。进一步,通过对电子鼻各气体传感器响应信号的载荷分析确定了各传感器贡献率的差异,结合气相色谱-质谱联用(GC-MS)技术揭示了受黄曲霉毒素污染糙米样品的挥发性组分的变化主要体现在酮醛类、醇类、芳香烃类和烷烃类上。结果表明,利用电子鼻对糙米的黄曲霉毒素污染的快速检测具有一定可行性,为粮食真菌毒素污染的早期预警提供一种新思路和新方法。     

河南省市售小麦粉微生物及真菌毒素污染状况研究

为了解河南省市售小麦粉的安全状况,收集整理河南省市售小麦粉。采用Filmplate~(TM)测试片法测定样品的菌落总数、霉菌和酵母菌计数及大肠菌群,采用酶联免疫法(Enzyme–Linked Immuno Sorbent Assay,ELISA)测定样品中呕吐毒素(DON)、黄曲霉毒素B_1(AFB_1)及赭曲霉毒素A(OTA)三种常见真菌毒素的含量。结果显示:小麦粉样品受微生物污染面积较广,但程度可控。菌落总数、霉菌酵母菌数、大肠菌群数主要集中范围分别是10~2~10~4、10~2~10~3、10~2~10~3 CFU/g;DON、AFB_1及OTA含量超限率分别为0.00%、13.85%、7.69%,检出率依次为69.23%、52.31%及84.62%,污染程度不同,污染范围均较为广泛。     

Mycobiota and mycotoxins in Brazilian peanut kernels from sowing to harvest

The total mycobiota and the mycotoxin contamination of peanuts were analyzed in plants collected at different stages of the pod maturity sampled in Junqueirópolis, at S?o Paulo State (Brazil). The prevalent peanut mycobiota were Fusarium spp. and Aspergillus flavus, present in 26% and 17% respectively of the samples analyzed. In soil, the genus Penicillium and Fusarium were most frequently detected, and A. flavus was detected in 8% of the samples. The screening of mycotoxins indicated that aflatoxins and cyclopiazonic acid were present the highest incidence, being detected in 32% of the samples, in concentrations, respectively, from 4.20 microg/kg to 198.84 microg/kg and from 260 microg/kg to 600 microg/kg. Fumonisins were not detected by HPLC. All data were correlated with the occurrence of wind-dispersed fungi and the environmental and soil conditions. Results indicate that good management of the agricultural environment may offer a way to reduce mycotoxins and the toxigenic fungal contamination in peanuts preharvest because the pods are exposed to different environmental conditions during their formation until harvest, and the optimal conditions for mycotoxin production and fungal growth are frequently found in the crop fields.     

衰减全反射-傅里叶变换红外光谱法对花生仁霉变的分析

为快速检测贮藏花生的质量安全,对灭菌后的新鲜花生仁样品分别接种5种常见的有害霉菌,并于26℃、相对湿度80%条件下贮藏9 d。利用衰减全反射-傅里叶变换红外光谱(attenuated total reflectance-Fourier transform infrared spectroscopy,ATR-FTIR)采集不同贮藏阶段花生样品在4 000~600 cm~(-1)的光谱信息,通过权重分析阐述花生中侵染霉菌后光谱特征的变化,并结合偏最小二乘回归(partial least squares regression,PLSR)分析建立样品有害霉菌污染的定量分析模型。结果表明,不同贮藏阶段样品的峰谱出现明显波动,PLSR模型对单一菌株与多种菌株样品菌落总数的预测精度较高,其中对赭曲霉3.6486处理组样品预测模型相对偏优,有效决定系数(R_p~2)为0.915 7、交互验证均方根误差(root mean-square error of cross-validation,RMSECV)为0.208 0(lg(CFU/g))、剩余预测偏差(residual predictive deviation,RPD)为2.52;对多种菌株预测结果R_p~2、RMSECV、RPD分别为0.780 3、0.358 0(lg(CFU/g))与1.76。应用ATR-FTIR技术对花生受霉菌侵染的状况进行快速分析具有可行性。     

我国土榨花生油黄曲霉毒素B1 及圆弧偶氮酸毒素污染调查

为了解我国土榨花生油中黄曲霉毒素B1(AFB1)和圆弧偶氮酸(CPA)的污染状况,采集全国12省20市小作坊生产的土榨花生油126份,购买市售品牌花生油27份,采用高效液相色谱法检测花生油中AFB1和CPA两种真菌毒素的含量。结果表明:27份品牌花生油未检出AFB1和CPA; 126份土榨花生油中,AFB1检出率为44.44%,超标率为11.11%,CPA检出率为7.14%,其中河南、福建、广西和山东土榨花生油AFB1污染较为严重。我国土榨花生油存在真菌毒素污染安全隐患,监管部门应严格把控原料及加工环节,确保土榨花生油的质量和安全。     

Fungi, aflatoxins, and cyclopiazonic acid associated with peanut retailing in Botswana

Peanuts are important food commodities, but they are susceptible to fungal infestation and mycotoxin contamination. Raw peanuts were purchased from retail outlets in Botswana and examined for fungi and mycotoxin (aflatoxins and cyclopiazonic acid) contamination. Zygomycetes were the most common fungi isolated; they accounted for 41% of all the isolates and were found on 98% of the peanut samples. Among the Zygomycetes, Absidia corymbifera and Rhizopus stolonifer were the most common. Aspergillus spp. accounted for 35% of all the isolates, with Aspergillus niger being the most prevalent (20.4%). Aspergillus flavus/parasiticus were also present and accounted for 8.5% of all the isolates, with A. flavus accounting for the majority of the A. flavus/parasiticus identified. Of the 32 isolates of A. flavus screened for mycotoxin production, 11 did not produce detectable aflatoxins, 8 produced only aflatoxins B1 and B2, and 13 produced all four aflatoxins (B1, B2, G1, and G2) in varying amounts. Only 6 of the A. flavus isolates produced cyclopiazonic acid at concentrations ranging from 1 to 55 microg/kg. The one A. parasiticus isolate screened also produced all the four aflatoxins (1,200 microg/kg) but did not produce cyclopiazonic acid. When the raw peanut samples (n = 120) were analyzed for total aflatoxins, 78% contained aflatoxins at concentrations ranging from 12 to 329 microg/kg. Many of the samples (49%) contained total aflatoxins at concentrations above the 20 microg/kg limit set by the World Health Organization. Only 21% (n = 83) of the samples contained cyclopiazonic acid with concentrations ranging from 1 to 10 microg/kg. The results show that mycotoxins and toxigenic fungi are common contaminants of peanuts sold at retail in Botswana.     

米扁虫对玉米中黄曲霉毒素B1含量影响的研究

了解在非霉变和不产毒的储存条件下,原粮中昆虫对真菌毒素含量的影响具有重要生态学意义。测定了含黄曲霉毒素B1(AFB1)的玉米分别接入15、45和135头/kg米扁虫幼虫和成虫后不同存放时间AFB1含量。结果表明,米扁虫幼虫和成虫接入一定时间后均可导致玉米中AFB1含量和霉菌总数显著降低,米扁虫成虫对AFB1含量降低的作用大于幼虫,玉米破碎粒率越低时AFB1含量降低越显著,虫口密度越大、接入时间越长,AFB1含量降低越显著。     

Detection of different stages of fungal infection in stored canola using near-infrared hyperspectral imaging

Near-infrared (NIR) hyperspectral imaging system was used to detect different stages of fungal infections in stored canola. Artificially infected canola seeds (Fungi: Aspergillus glaucus and Penicillium spp) were subjected to hyperspectral imaging in the range between 1000 and 1600 nm at 61 evenly distributed wavelengths. Four wavelengths 1100, 1130, 1250 and 1300 nm were identified as significant wavelengths and were used in statistical discriminant analysis. Pair-wise, two-class and six-class classification models were developed to classify the healthy and different stages of fungal infected samples. Linear, quadratic and Mahalanobis discriminant classifiers were used to classify healthy, five stages of A. glaucus and five stages of Penicillium spp infected canola seeds. All the three classifiers classified healthy and fungal infected canola seeds with a classification accuracy of more than 95% for healthy canola seeds and more than 90% for the initial stages of A. glaucus and Penicillium spp infected canola seeds. The classification accuracy increased to 100% with increase in fungal infection level (length of time since inoculation). All the samples subjected to imaging were tested for seed germination and free fatty acid value (FAV). The germination decreased with increase in amount of fungal infection, whereas FAV increased with increase in amount of fungal infection.     

Detection of fungal infection and Ochratoxin A contamination in stored wheat using near-infrared hyperspectral imaging

A study was done to detect Aspergillus glaucus, and Penicillium spp., infection and Ochratoxin A contamination in stored wheat using a Near-Infrared (NIR) Hyperspectral Imaging system. Fungal-infected samples were imaged every two weeks, and the three dimensional hypercubes obtained from image data were transformed into two dimensional data. Principal component analysis was applied to the two dimensional data and based on the highest factor loadings, 1280, 1300, and 1350 nm were identified as significant wavelengths. Six statistical features and ten histogram features corresponding to the significant wavelengths were extracted and subjected to linear, quadratic and Mahalanobis discriminant classifiers. All the three classifiers differentiated healthy kernels from fungal-infected kernels with a classification accuracy of more than 90%. The quadratic discriminant classifier provided classification accuracy higher than the linear and Mahalanobis classifiers for pair-wise, two-way and six-way classification models. The Ochratoxin A contaminated samples had a unique significant wavelength at 1480 nm in addition to the two significant wavelengths corresponding to fungal infection. The peak at 1480 nm was identified only in the Ochratoxin A contaminated samples. The Ochratoxin A contaminated samples can be detected with 100% classification accuracy using NIR hyperspectral imaging system. The NIR hyperspectral system can differentiate between different fungal infection stages and different levels of Ochratoxin A contamination in stored wheat.     

Aspergillus section Flavi and aflatoxins in dried figs and nuts in Algeria

The presence of Aspergillus section Flavi and aflatoxin (AF) contamination was investigated in 112 samples of peanuts, almonds and dried figs collected in Algeria. The occurrence of aflatoxin B1 (AFB1), B2 (AFB2), G1 (AFG1) and G2 (AFG2) in different commodities has been determined with a sensitive method based on high performance liquid chromatography (HPLC) coupled with fluorescence detection with post-column photochemical derivatisation. Analytical results indicated that 28 samples of peanuts, 16 samples of almonds and 26 samples of dried figs contained detectable levels of AFs. A total of 69 samples (61.6%) were contaminated with AFB1 ranging from the limit of quantification to 174 µg kg^?1. AFB2 was found in 12 samples (10.7%) and varied from 0.18 to 193 µg kg^?1. Seven samples revealed AF concentrations lower than the limit of quantification. Eleven peanut and fourteen dried fig samples exceeded the European maximum limits for AFB1.     

Aspergillus flavus population isolated from soil of Argentina's peanut‐growing region. Sclerotia production and toxigenic profile

The Aspergillus flavus population was evaluated in the period 1998–2001 in soil samples from the peanut‐growing region in Argentina. A total of 369 A flavus isolates were examined for sclerotia, aflatoxin and cyclopiazonic acid production. The L phenotype was isolated in a higher percentage than the S phenotype and represented 59% of the total isolates. Statistical analysis showed significant differences between L, S and non‐sclerotial strains with regard to aflatoxin and cyclopiazonic acid production (p < 0.05). The S strains produced higher mycotoxin levels than the L and non‐sclerotial strains. About 10% of the S strains had an unusual pattern of mycotoxin production because they simultaneously produce aflatoxins B and G and CPA. The S_BG strains isolated in the present study have all morphological and microscopic characteristics of A flavus. These strains are of concern in food safety, as there is a higher probability of aflatoxin contamination in peanuts. Copyright © 2005 Society of Chemical Industry