基于光谱法的特级初榨橄榄油快速鉴伪技术

本文研究了特级初榨橄榄油中掺入不同比例橄榄果榨油(精炼橄榄油)、菜籽油、玉米油和大豆油的光谱特征,采用荧光光谱和紫外光谱,对掺假样品及纯油样品进行了快速检测。结果表明,特级初榨橄榄油的光谱特征与其他植物油之间差异较大,且掺假体积与吸光度之间存在良好的线性关系(R²>0.89),实现了特级初榨橄榄油的定性鉴别与定量检测,建立了特级初榨橄榄油质量控制体系及其掺假检测分析技术,最低检出限为1%,线性范围为5%～100%(v/v)。系统聚类分析将所有特级初榨橄榄油准确地分为一个亚类,也佐证了此方法的稳定性与可靠性。这种简单快捷的检测技术,有助于特级初榨橄榄油实时、在线橄榄油检测分析技术的研发,为我国橄榄油品质鉴定及产业发展提供有利的技术保障。     

初榨橄榄油风味化合物研究进展

阐述了初榨橄榄油风味的主要来源途径即脂氧合酶途径,对影响初榨橄榄油风味特征的若干因素如品种和地理环境,油橄榄果实成熟度,加工工艺,储藏条件等因素进行了讨论和分析.介绍了初榨橄榄油中挥发性化合物的分析检测方法,并且展望了橄榄油风味化合物研究的应用和发展前景.     

国内初榨橄榄油品质特性研究

以国内种植的油橄榄为原料,研究了油橄榄品种、成熟度以及堆放时间对初榨橄榄油脂肪酸组成、酸值、过氧化值及风味的影响。结果表明：不同品种油橄榄的初榨橄榄油中油酸和亚油酸含量差异较大,油酸含量范围65.85%~80.08%,亚油酸含量范围2.61%~17.18%;初榨橄榄油的酸值随油橄榄成熟度的升高而降低,其中鄂植8号酸值（KOH）从0.35 mg/g下降到0.26 mg/g;紫果的初榨橄榄油过氧化值低于青红果和红果;油橄榄堆放时间延长会使初榨橄榄油的过氧化值略有增加,而酸值的增加程度因品种而异。不同形式的油橄榄初榨橄榄油在风味上均能很好地区分。     

四川青川县初榨橄榄油营养成分及油脂特性分析

为摸清四川青川县主栽油橄榄品种初榨橄榄油的脂肪酸组成、营养成分和挥发性物质,利用气相色谱、气质联相色谱对油脂进行检测,结果显示:平均不饱和脂肪酸为82.82%,为豆果83.30%皮削利83.05%鄂植8号82.1%,其中品种间油酸和油酸含量间存在显著差异;平均值维生素E含量为28.78 mg/100 g,为鄂植8号32.7 mg/100 g!皮削利27.5 mg/100 g!豆果24.4mg/100g,品种间α-维生素E存在显著差异;平均值角鲨烯含量为4 512.48 mg/kg,为皮削利6 690.95 mg/kg!鄂植8号4 386.50 mg/kg!豆果2 460.00 mg/kg,品种间角鲨烯存在极显著差异;平均值β-谷甾醇含量为849.00 mg/kg,为鄂植8号1 161.30 mg/kg!皮削利946.35 mg/kg!豆果439.35 mg/kg,品种间β-谷甾醇存在极显著差异。油脂中鉴定出25种挥发性化合物,其中醛类4个,醇类2个,酯类5个,烯烃类7个和萜烯类5个,其他2种;鄂植8号和豆果橄榄油挥发性物质的主要为醛类,占总物质的55.88%和52.58%,皮削利挥发性物质主要为烯烃类物质,占总物质的53.68%。综上所述,青川初榨橄榄油营养物质丰富,挥发性物质独特,香味浓郁,存在明显的地域特征,具有良好的开发价值。     

初榨橄榄油在加热过程中品质变化研究

初榨橄榄油营养丰富且具保健价值,研究初榨橄榄油在烹调加热过程中品质的变化具有重要意义。采用仪器分析和化学分析法研究初榨橄榄油在加热过程中品质指标的变化。研究结果表明,初榨橄榄油在180℃加热过程中,脂肪酸值、过氧化值、羰基值、黏度逐渐增加,饱和脂肪酸和反式脂肪酸含量增加,不饱和脂肪酸含量下降。初榨橄榄油在180℃加热300 min时,过氧化值开始超标;加热480 min时,脂肪酸值、羰基值、反式脂肪酸含量仍未超标或超过推荐量。初榨橄榄油在180℃下加热烹调食品不宜超过240 min。如果要延长烹调加热时间,可以适当降低加热温度。该研究为初榨橄榄油在食品中的煎炸及含初榨橄榄油食品的高温处理提供科学参考。     

基于PCA-SVM结合共聚焦拉曼光谱的特级 初榨橄榄油掺伪压榨菜籽油定量分析

为了促进国内橄榄油市场的健康发展，对掺伪同样存在天然类胡萝卜素的低温压榨菜籽油的特级初榨橄榄油进行了定量鉴别研究。采用共聚焦拉曼光谱技术对不同掺伪浓度油样进行测试，基于密度泛函理论对油样的拉曼光谱峰的归属进行了理论分析，并对拉曼光谱数据进行主成分分析（PCA），然后利用支持向量机（SVM）构建PCA-SVM模型。另外，对PCA-SVM模型的检出限进行了研究。结果表明：特级初榨橄榄油与低温压榨菜籽油的拉曼光谱存在一定差异，最明显的光谱差异主要集中在谱峰1 008、1 161、1 528 cm-1和谱段2 800～3 000 cm-1内，与密度泛函理论对不同油样拉曼光谱峰的分析一致；不考虑类胡萝卜素特征信号建立的PCA-SVM模型决定系数大于0.989，均方根误差小于2.990%，检出限为2%（低温压榨菜籽油体积分数）;在特级初榨橄榄油掺伪定量分析中，考虑类胡萝卜素的特征信号有助于提高模型预测精度，但仅限于掺伪低价植物油中无类胡萝卜素存在的情况;PCA-SVM模型在不考虑类胡萝卜素特征信号的情况下依然具有良好的定量预测效果。综上，所建立的PCA-SVM模型可以用于掺伪2%以上低温压榨菜籽油的特级初榨橄榄油的定量鉴别。     

基于电子鼻技术鉴别陇南初榨橄榄油

为了快速简便地鉴别同一品种不同果实成熟度和不同品种同一果实成熟度的初榨橄榄油,运用电子鼻传感器分析技术结合Loadings负荷加载分析、线性判别分析(LDA)等数据处理技术对结果图谱进行解析,并通过欧氏距离分析(EDA)、相关性分析(CA)、马氏距离分析(MDA)和判别函数分析(DFA)验证模型的准确性.结果显示:电子...     

初榨橄榄油中的微生物群及其对橄榄油品质的影响

初榨橄榄油生产环境相对开放,榨取橄榄油的原料、环境及设备中的微生物群都可能进入初榨橄榄油,对油脂品质产生影响。为全面认识初榨橄榄油中微生物群以及从微生物层面控制初榨橄榄油品质,从食品微生物学研究的视角,综述了初榨橄榄油中酵母菌、细菌和霉菌等主要微生物群,分析了油橄榄枝叶、果实和初榨橄榄油中的微生物群对油脂品质的影响,介绍了采后储存的油橄榄果实及储存期的初榨橄榄油品质与微生物群之间的关系,探讨了对有害微生物群影响初榨橄榄油品质的防控措施。研究认为酵母菌对初榨橄榄油储存期间的品质起主要的影响作用。通过避免采摘和储存过程中油橄榄果实的损伤,保证加工过程中清洗用水和设备的洁净,控制储存环境温度、光照和氧含量等措施,可以有效防控有害微生物对橄榄油品质的负面影响。     

鲜榨山茶油与特级初榨橄榄油营养价值的比较

以鲜榨山茶油和特级初榨橄榄油为研究对象,对其理化指标、脂肪酸组成和营养成分进行测定并比较。结果表明:鲜榨山茶油在理化指标上与特级初榨橄榄油相当,脂肪酸组成与特级初榨橄榄油相似,但油酸含量高于特级初榨橄榄油,棕榈酸和硬脂酸含量低于特级初榨橄榄油;在维生素E、角鲨烯、植物甾醇等天然生物活性物质方面媲美特级初榨橄榄油。     

风味和功能性特级初榨橄榄油的研制

以特级初榨橄榄油为基础油,分别添加橘子、橙子、柠檬、辣椒、花椒天然风味香料进行调味,或添加植物甾醇酯、茶多酚增加其功能性。通过感官评定确定了橘子、橙子、柠檬3种水果风味香料最佳添加量均为1.3%,辣椒、花椒2种香辛料风味香料最佳添加量分别为0.5%和3.0%,植物甾醇酯、茶多酚添加量分别为1.0%和0.03%。在最佳添加量条件下,风味油和功能性油过氧化值、酸值稳定性良好;水果风味油p-茴香胺值上升比较明显,其他风味油和功能性油与特级初榨橄榄油的p-茴香胺值基本持平。     

反向传播神经网络算法结合拉曼荧光光谱法定量检测特级初榨橄榄油掺假

目的 建立基于反向传播神经网络算法结合拉曼荧光光谱技术定量检测低等级橄榄油掺假特级初榨橄榄油的分析方法。方法 制备11种不同掺伪浓度的特级初榨橄榄油混合油样各10份,在相同时间、空间及目标的前提下,使用同台光谱探测系统,采集样品的拉曼光谱和荧光光谱。经过卷积神经网络去除拉曼光谱的基线,实现拉曼光谱和荧光光谱的数据预处理。根据分子光谱与电子光谱的特征差异,人为干预并设定拉曼光谱的权重,建立低等级橄榄油掺假特级初榨橄榄油的反向传播神经网络回归模型。结果 综合评估了反向传播神经网络回归模型的评价参数,特级初榨橄榄油掺假的反向传播神经网络模型的测试集决定系数为0.9716,均方根误差为0.0569,模型预测效果较好。结论 本研究提出的反向传播神经网络算法结合拉曼光谱与荧光的探测方法,满足快速检测低等级橄榄油掺假特级初榨橄榄油的定量分析需求,为评价或跟踪特级初榨橄榄油的品质提供了一种无损伤、高效率、低成本的新检测思路。     

Rapid assessment of the adulteration of virgin olive oils by other seed oils using pyrolysis mass spectrometry and artificial neural networks

Curie-point pyrolysis mass spectra were obtained from a variety of extra-virgin olive oils, prepared from various cultivars using several mechanical treatments. Some of the oils were adulterated (according to a double-blind protocol) with different amounts of seed oils (50–500 ml of soya, sunflower, peanut, corn or rectified olive oils per litre of mixed oil). Canonical variates analysis indicated that the major source of variation between the pyrolysis mass spectra was due to differences between the cultivars. rather than whether the oils had been adulterated. However, artificial neural networks could be trained (using the back-propagation algorithm) successfully to distinguish virgin oils from those which had been adulterated.     

基于拉曼光谱和CNN算法的特级初榨 橄榄油的掺假量化

旨在为特级初榨橄榄油掺假快速定量分析提供参考,以掺假菜籽油的特级初榨橄榄油为例,采用激光拉曼光谱实验系统获取油样的拉曼光谱数据,运用基于Inception V2结构的卷积神经网络（CNN）算法提取拉曼光谱特征并完成光谱特征与掺假量的非线性关系映射。结果表明：特级初榨橄榄油与菜籽油的拉曼光谱存在较大的差异,其中类胡萝卜素、碳碳双键、甲基和亚甲基产生的拉曼特征峰是引起差异的主要因素;所建立的CNN模型效果较好,训练集、验证集、测试集的决定系数均大于099,均方根误差均小于0.026;在低剂量掺假中,模型的预测结果仍具有一定的参考价值。综上,拉曼光谱结合基于Inception V2结构的CNN算法所建立的模型可以满足特级初榨橄榄油掺假量的快速检测。     

Authentication of extra virgin olive oils by Fourier-transform infrared spectroscopy

Fourier-transform infrared spectroscopy (FTIR), followed by multivariate treatment of the spectral data, was used to classify vegetable oils according to their botanical origin, and also to establish the composition of binary mixtures of extra virgin olive oil (EVOO) with other low cost edible oils. Oil samples corresponding to five different botanical origins (EVOO, sunflower, corn, soybean and hazelnut) were used. The wavelength scale of the FTIR spectra of the oils was divided in 26 regions. The normalized absorbance peak areas within these regions were used as predictors. Classification of the oil samples according to their botanical origin was achieved by linear discriminant analysis (LDA). An excellent resolution among all categories was achieved using an LDA model constructed with eight predictors. In addition, multiple linear regression models were used to predict the composition of binary mixtures of EVOO with sunflower, corn, soybean and hazelnut oils. For all the binary mixtures, models capable of detecting a low cost oil content in EVOO as low as 5% were obtained.     

Contribution of polyphenols to the oxidative stability of virgin olive oil

Stability, polyphenol, orthodiphenol, tocopherol, oleic/linoleic ratio, chlorophyll, carotenoid, peroxide and acidity values, K₂₃₂, K₂₇₀ and overall sensory score of virgin olive oils from Hojiblanca and Picual cultivars were determined during two consecutive seasons. Changes due to cultivar and season were evaluated, correlations between the changes were studied and their contribution to stability was investigated by multiple regression techniques. Removal of polyphenols from the original samples without altering other antioxidant components has permitted estimating, for the first time, the contribution of these compounds to virgin olive oil. Approximately 50% of the stability is contributed by polyphenols. © 2001 Society of Chemical Industry     

基于近红外光谱的橄榄油中玉米油掺杂量检测

利用近红外光谱和模式识别技术建立了橄榄油中掺杂玉米油的快速鉴别方法。对191个橄榄油样本及混合油样本（玉米油和橄榄油）进行近红外光谱扫描,并对近红外光谱进行一阶导数和平滑处理,利用主成分分析法（PCA）对数据进行降维,通过前三个主成分的载荷图确定了相关性较大的特征波段（7520⁶927cm-1、6270⁵440cm-1和4970⁴400cm-1）,分别在3个波段内利用偏最小二乘回归（PLS）方法建立了玉米油含量的预测模型。结果表明在6270⁵440cm-1波段内,因子数为7,建立的模型精密度和稳定性最好,在玉米油质量分数为0.5%¹00%的范围内,校正集样本和检验集样本的R2均能达到0.9999,标准偏差在0.126⁰.139之间。因此,利用近红外光谱可以实现橄榄油品质的快速无损分析,以合频波段（6270⁵440cm-1）为建模区域可以得到更好的预测效果。      

Heat-oxidation stability of palm oil blended with extra virgin olive oil

Rancimat induction time of palm oil (PO), several extra virgin olive oils (EV) and their binary blends have been determined at three different temperatures (120, 130 and 140°C). Analytical composition and oxidation stability of PO/EV blends were found to be a linear combination of the oil partners. Induction time of pure PO was always higher than those of EV oils and blends, in which induction time increased proportionally with the percentage of PO. However, induction time of 80% PO blend was similar to that of pure PO. Fatty acid composition appeared to be the most important factor affecting heat-oxidation stability and a saturated/unsaturated ratio near 1 was the optimally stable composition. Conversely, total phenols had a zero or negative role on the oxidative stability of the blends. Finally, in heat-oxidised oils significant losses of polyunsaturated fatty acids and formation of short-chain fatty acids were recorded.