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基于质量标准的油茶籽油和橄榄油比较分析Comparison of oil-tea camellia seed oil and olive oil based on quality standards
Zhongguo youzhi, 2022 基于质量标准对油茶籽油和橄榄油进行比较分析。结果表明：油茶籽油与橄榄油的特征指标和质量指标相似，油茶籽油具有碘值低、抗氧化能力强、稳定性好、烟点高等特性；油茶籽油与橄榄油中不饱和脂肪酸含量均高，油酸均是最主要的脂肪酸，油茶籽油中油酸含量甚至比橄榄油的高；油茶籽油中饱和脂肪酸含量约10%，比橄榄油的低；油茶籽油中含有多酚、黄酮等活性营养成分，营养价值高。另外，指出了现行油茶质量标准体系亟待完善的问题，为油茶籽油的深度开发利用提供参考。 The oil-tea camellia seed oil and ...
程明焱1,2, 王玫1,2, 张远聪1,2, 赖小燕1,2, 张磊1,2, 沈乐丞1,2 CHENG Mingyan1,2, WANG Mei1,2, ZHANG Yuancong1,2, LAI Xiaoyan1,2, ZHANG Lei1,2, SHEN Lecheng1,2
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Preparation and volatile compounds analysis of Camellia seed oil with Zanthoxylum flavor
Shipin yu jixie, 2023 Objective: In order to improve the special smell of Camellia oleifera seed oil, the Zanthoxylum flavor Camellia oleifera seed oil was developed with camellia oleifera seed oil and prickly ash as the raw materials. Methods: The peroxide value, acid value,
LI Dong +4 more
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Zhongguo youzhi, 2023 为了解决风味（原香和烤香）油茶籽油掺伪浸出油茶籽油的定性判别问题，设计高、低两个掺伪梯度，基于挥发性成分构建并对比分析了定性判别风味油茶籽油掺伪浸出油茶籽油的主成分分析（PCA）模型和逻辑回归模型。结果表明：逻辑回归模型定性判别风味油茶籽油掺伪浸出油茶籽油的能力较强，优于PCA模型；高掺伪梯度下定性判别原香和烤香油茶籽油掺伪浸出油茶籽油，PCA模型的最低检出限分别为20%和60%，而逻辑回归模型的最低检出限均为10%；低掺伪梯度下定性判别原香和烤香油茶籽油掺伪浸出油茶籽油，PCA模型的判别不准确 ...
孙婷婷1,2，陈志清1,2，刘剑波3，任佳丽1,2，钟海雁1,2，周波1,2 SUN Tingting1,2, CHEN Zhiqing1,2, LIU Jianbo3, REN Jiali1,2, ZHONG Haiyan1,2, ZHOU Bo1,2
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The physicochemical properties and fatty acid composition of two new woody oil resources: Camellia hainanica seed oil and Camellia sinensis seed oil [PDF]
CyTA - Journal of Food, 2021 Woody plants are important source of edible oil, and Camellia hainanica and Camellia sinensis are two new option. The physicochemical properties and fatty acid composition were determined in both species. The oil content of C. hainanica was 37.60–41.60%, and that of C. sinensis was 31.04–33.20%.
Xu Zhenggang +6 more
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Plants, 2023 Camellia seed oil is a top-end quality of cooking oil in China. The oil quality and quantity are formed during seed maturation and desiccation. So far, it remains largely unresolved whether lipid degradation occurs and contributes to Camellia oil traits.
Mingjie Chen +4 more
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Zhongguo youzhi, 2023 海南岛油茶籽油品质独特，为促进海南岛油茶资源开发利用并为油茶籽油品质性状育种提供参考依据，选取海南岛不同油茶主产区的油茶籽，对油茶种仁含油率及油茶籽油理化指标、无机元素含量、脂肪酸组成和生物活性物质含量进行测定，并对考察指标进行相关分析、品质综合评价和聚类分析。结果表明：海南岛油茶籽种仁平均含油率为49.13%；油茶籽油无机元素含量丰富，不饱和脂肪酸含量在90%左右，角鲨烯含量为78.33~96.23 mg/kg,茶多酚含量为64.78~77.36 mg/kg,维生素E含量为430.7~484.4 mg/
夏腾飞1,2，陈加利1,2，熊子君3，孙秀秀1,2，马光耀2，王春梅2， 梁振儒2，冯依欣2， 郑道君1,2 XIA Tengfei1,2, CHEN Jiali1,2, XIONG Zijun3, SUN Xiuxiu1,2, MA Guangyao2, WANG Chunmei2, LIANG Zhenru2, FENG Yixin2, ZHENG Daojun1,2
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Zhongguo youzhi, 2022 为了探索基于近红外光谱技术快速无损鉴别掺假油茶籽油的可行性，以赣南茶油为研究对象，通过掺入不同植物油如玉米油、花生油、菜籽油、葵花籽油和大豆油等制备掺假油茶籽油，应用近红外光谱技术采集其光谱特征信息，对比不同预处理方法和主成分数，并结合线性和非线性建模方法建立油茶籽油掺假鉴别模型，以识别准确率(纯油茶籽油样品和掺假油茶籽油样品被正确判别的比例）、灵敏度（纯油茶籽油样品被正确判别为纯油茶籽油的比例）、特异性（掺假油茶籽油样品被正确判别为掺假油茶籽油的比例）作为模型的评价指标，优选出最佳模型。结果表明 ...
沈乐丞，曾秀英，温志刚，张远聪，刘贤标，王玫，刘婷，范伟华，邹辉SHEN Lecheng, ZENG Xiuying, WEN Zhigang, ZHANG Yuancong, LIU Xianbiao, WANG Mei， LIU Ting, FAN Weihua, ZOU Hui
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红外与微波预处理油茶籽对其原油 DPPH自由基清除能力的影响
Zhongguo youzhi, 2023 为了研究油茶籽油氧化稳定性机制，了解不同预处理方式对油茶籽油抗氧化能力的影响，以DPPH自由基清除能力为指标，对油茶籽分别经红外与微波预处理后得到的油茶籽原油及其极性组分和非极性组分抗氧化能力进行分析。结果表明：油茶籽分别经红外和微波预处理后，得到的油茶籽原油及其极性、非极性组分DPPH自由基清除能力变化显著；红外预处理的油茶籽所制油茶籽原油及其非极性组分的DPPH自由基清除能力高于相应微波预处理，其最大值分别高3.53 μg/g和6.47 μg/g ...
王龙祥1，2，罗凡1，钟海雁2，方学智1，杜孟浩1，胡立松1 WANG Longxiang1,2，LUO Fan1，ZHONG Haiyan2， FANG Xuezhi1， DU Menghao1，HU Lisong1
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Frontiers in Nutrition, 2022 Camellia oil is one of the four major woody oils in the world and has high nutritional value due to its richness in monounsaturated fatty acids (MUFAs) and bioactive substances. In order to compare the effects of pretreatments of camellia seeds on the quality, phenolic profile, and antioxidant capacity of camellia oil, three different pretreatment ...
Mei Wang +12 more
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Rapid identification of adulterated camellia seed oil by e-nose combined with chemometrics
Shipin yu jixie, 2023 Objective： To establish a rapid qualitative and quantitative method for the adulteration of Camellia seed oil. Methods： The electronic nose technology combined with chemometrics was used to screen the difference variables based on one-way ANOVA.
GUAN-ZHAO Yi-zhu +5 more
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