Article(id=1152687442785125095, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1152687434774000221, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20241107004, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1730908800000, receivedDateStr=2024-11-07, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1752751702257, onlineDateStr=2025-07-17, pubDate=1747238400000, pubDateStr=2025-05-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752751702257, onlineIssueDateStr=2025-07-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752751702257, creator=13701087609, updateTime=1752751702257, updator=13701087609, issue=Issue{id=1152687434774000221, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='9', pageStart='1', pageEnd='324', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752751700342, creator=13701087609, updateTime=1756708585928, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1169283815848555430, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1152687434774000221, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1169283815848555431, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1152687434774000221, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=82, endPage=91, ext={EN=ArticleExt(id=1152687443523322619, articleId=1152687442785125095, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Process optimization of microwave-assisted blended cold pressing for preparation of polyunsaturated fatty acids equilibrium oil, columnId=1152687436694995508, journalTitle=Journal of Food Safety & Quality, columnName=Special Topic: Grain and Oil Processing and Quality Safety, runingTitle=null, highlight=null, articleAbstract=

Objective To explore the mixing ratio of different oil seeds in microwave-assisted blended cold pressing process, and develop polyunsaturated fatty acid balanced oil that meets the recommended dietary intake ratio. Methods The safflower seed and flaxseed were used as raw materials. The process parameters were optimized by single factor experiment (microwave treatment time, pressing temperature and moisture content of oil seed) and Box-Behnken response surface experiment. The oxidation characteristics of blended cold pressed oil were compared and analyzed. Results The mass ratio method determined that the blended mass ratio range was 1.8-2.4 (safflower seed:flaxseed, Ws:Wf). This method was simple and the results did not need to be verified, but it had the disadvantages of large demand for raw materials and low accuracy of boundary value. The mixing ratio range determined and verified by the fatty acid ratio method was 1.66-2.59 (Ws:Wf). This method had less raw material demand and high accuracy near the boundary value. However, due to the interaction of oil seeds, verification experiments needed to be carried out. Response surface methodology was used to optimize the process parameters of microwave-assisted blended cold pressing. The optimal extraction conditions were as follows: Microwave (800 W) treatment time 1.5 min, cold pressing temperature 64 °C, oil seed moisture content 6.7%, oil extraction rate 19.83%±0.21 %, which was 17.2% higher than that before optimization. The basic physical and chemical indexes of blended cold-pressed oil and traditional cold-pressed blend oil were compared and analyzed. The oil oxidation degree was lower under the condition of microwave-assisted blended cold-pressed process. Conclusion Microwave-assisted blended cold pressing oil has lower primary and secondary oxidation product indexes than traditional cold-pressed blended oil. The results can provide a theoretical basis for the preparation of polyunsaturated fatty acid equilibrium oil and the application of microwave-assisted blended cold pressing process in the field of grain and oil processing.

, correspAuthors=Chang-Qing WEI, 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=Gao-Qian ZHANG, Xin-Wen XU, Liu-Feng YANG, Yi-Yuan ZHANG, Jing WANG, Chang-Qing WEI), CN=ArticleExt(id=1152687465459532128, articleId=1152687442785125095, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=微波辅助混合冷榨制备多不饱和脂肪酸均衡油的工艺优化, columnId=1152687437265420855, journalTitle=食品安全质量检测学报, columnName=本期专题:粮油加工与质量安全, runingTitle=null, highlight=null, articleAbstract=

目的 探究微波辅助混合冷榨工艺中不同油籽的混合比例, 开发符合膳食推荐摄入比例的多不饱和脂肪酸均衡油。方法 以红花籽和亚麻籽为原料, 通过单因素实验(微波处理时间、入榨温度和油籽水分含量)及Box-Behnken响应面实验优化工艺参数条件, 对比分析混合冷榨油的氧化特性。结果 质量比值法确定混合质量比例范围为1.8~2.4 (红花籽:亚麻籽, Ws:Wf), 此法操作简单且结果无需验证, 但存在对原料需求量较大、边界值精确度较低等弊端; 脂肪酸比值法确定并验证的混合比例范围为1.66~2.59 (Ws:Wf), 此法原料需求量较低且边界值附近精确度较高, 但由于油籽交互作用的影响, 需进行验证实验; 利用响应面法对微波辅助混合冷榨工艺参数进行优化, 得到最优提取条件为: 微波(800 W)处理时间1.5 min, 冷榨温度64 ℃, 油籽水分含量6.7%, 提油率为19.83%±0.21%, 较优化前提高了17.2%; 对比分析混合冷榨油和传统冷榨调和油基本理化指标, 微波辅助混合冷榨工艺条件下油氧化程度更低。结论 混合冷榨油在初级和次级氧化产物指标上均低于传统冷榨调和油, 该结果可为粮油加工领域中多不饱和脂肪酸均衡油的制备和微波辅助混合冷榨工艺的应用提供一定理论依据。

, correspAuthors=魏长庆, authorNote=null, correspAuthorsNote=
* 魏长庆(1981—), 男, 博士, 教授, 主要研究方向为脂质科学与技术。E-mail:
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张高虔(1998—), 男, 硕士研究生, 主要研究方向为粮食、油脂与植物蛋白工程。E-mail:

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Science and Technology of Cereals, Oils and Foods, 2015, 23(4): 40-43., articleTitle=Effect of microwave treatment on the oil yield of sesame oil and its quality, refAbstract=null)], funds=[Fund(id=1169272789811867969, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1152687442785125095, awardId=2022NC185, language=CN, fundingSource=新疆维吾尔自治区乡村振兴产业发展科技行动项目(2022NC185), fundOrder=null, country=null), Fund(id=1169272789878976834, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1152687442785125095, awardId=YZ2022B023, language=CN, fundingSource=伊犁哈萨克自治州科技计划项目(YZ2022B023), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1169272785051332857, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1152687442785125095, xref=null, ext=[AuthorCompanyExt(id=1169272785059721466, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1152687442785125095, companyId=1169272785051332857, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. 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Factors and levels of response surface experiment design

, figureFileSmall=null, figureFileBig=null, tableContent=
因素 编码 水平
-1 0 +1
微波处理时间/min X1 1 2 3
冷榨温度/℃ X2 60 65 70
油籽水分含量/% X3 5 6 7
), ArticleFig(id=1169272788796846392, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1152687442785125095, language=CN, label=表1, caption=

响应面实验设计因素与水平

, figureFileSmall=null, figureFileBig=null, tableContent=
因素 编码 水平
-1 0 +1
微波处理时间/min X1 1 2 3
冷榨温度/℃ X2 60 65 70
油籽水分含量/% X3 5 6 7
), ArticleFig(id=1169272788901703993, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1152687442785125095, language=EN, label=Table 2, caption=

Standard curve equations and correlation coefficients of 5 kinds of fatty acids

, figureFileSmall=null, figureFileBig=null, tableContent=
脂肪酸 标准曲线方程 r2
LA Y=6056.6X+45264 0.9908
ALA Y=20015X-546853 0.9919
OA Y=5913.4X+5668.5 0.9901
PA Y=21222X-4357.8 0.9900
SA Y=134074X-3057 0.9909
), ArticleFig(id=1169272788960424250, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1152687442785125095, language=CN, label=表2, caption=

5种脂肪酸的标准曲线方程及相关系数

, figureFileSmall=null, figureFileBig=null, tableContent=
脂肪酸 标准曲线方程 r2
LA Y=6056.6X+45264 0.9908
ALA Y=20015X-546853 0.9919
OA Y=5913.4X+5668.5 0.9901
PA Y=21222X-4357.8 0.9900
SA Y=134074X-3057 0.9909
), ArticleFig(id=1169272789086253371, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1152687442785125095, language=EN, label=Table 3, caption=

Design scheme and results of response surface optimization

, figureFileSmall=null, figureFileBig=null, tableContent=
序号 因素 提油率/%
X1 X2 X3 实验值 预测值
1 1 0 1 16.04 16.08
2 0 0 0 19.55 19.60
3 -1 0 -1 17.98 17.95
4 0 1 1 19.33 19.20
5 0 0 0 19.56 18.18
6 0 0 0 19.94 19.60
7 -1 -1 0 18.86 18.77
8 0 -1 1 19.36 19.18
9 0 0 0 19.27 19.60
10 1 1 0 16.51 16.60
11 1 0 -1 16.49 16.22
12 -1 0 1 19.26 19.53
13 0 0 0 19.70 19.60
14 -1 1 0 19.40 19.26
15 0 1 -1 18.71 18.89
16 1 -1 0 16.11 16.25
17 0 -1 -1 17.94 18.01
), ArticleFig(id=1169272789178528060, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1152687442785125095, language=CN, label=表3, caption=

响应面优化设计方案及结果

, figureFileSmall=null, figureFileBig=null, tableContent=
序号 因素 提油率/%
X1 X2 X3 实验值 预测值
1 1 0 1 16.04 16.08
2 0 0 0 19.55 19.60
3 -1 0 -1 17.98 17.95
4 0 1 1 19.33 19.20
5 0 0 0 19.56 18.18
6 0 0 0 19.94 19.60
7 -1 -1 0 18.86 18.77
8 0 -1 1 19.36 19.18
9 0 0 0 19.27 19.60
10 1 1 0 16.51 16.60
11 1 0 -1 16.49 16.22
12 -1 0 1 19.26 19.53
13 0 0 0 19.70 19.60
14 -1 1 0 19.40 19.26
15 0 1 -1 18.71 18.89
16 1 -1 0 16.11 16.25
17 0 -1 -1 17.94 18.01
), ArticleFig(id=1169272789333717309, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1152687442785125095, language=EN, label=Table 4, caption=

Analysis of variance

, figureFileSmall=null, figureFileBig=null, tableContent=
方差来源 平方和 均方 自由度 F P 显著性
模型 29.12 3.24 9 42.36 <0.0001 **
X1 13.39 13.39 1 175.32 <0.0001 **
X2 0.35 0.35 1 4.62 0.0687
X3 1.03 1.03 1 13.48 0.0079 **
X1X2 4.900E-003 4.900E-003 1 0.064 0.8073
X1X3 0.75 0.75 1 9.80 0.0166 *
X2X3 0.16 0.16 1 2.09 0.1911
X12 11.30 11.30 1 147.95 <0.0001 **
X22 0.25 0.25 1 3.33 0.1108
X32 1.15 1.15 1 15.09 0.0060 **
残差 0.53 0.076 7
失拟项 0.30 0.099 3 1.66 0.3119 不显著
纯误差 0.24 0.060 4
合计 29.66 16
), ArticleFig(id=1169272789451157822, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1152687442785125095, language=CN, label=表4, caption=

方差分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
方差来源 平方和 均方 自由度 F P 显著性
模型 29.12 3.24 9 42.36 <0.0001 **
X1 13.39 13.39 1 175.32 <0.0001 **
X2 0.35 0.35 1 4.62 0.0687
X3 1.03 1.03 1 13.48 0.0079 **
X1X2 4.900E-003 4.900E-003 1 0.064 0.8073
X1X3 0.75 0.75 1 9.80 0.0166 *
X2X3 0.16 0.16 1 2.09 0.1911
X12 11.30 11.30 1 147.95 <0.0001 **
X22 0.25 0.25 1 3.33 0.1108
X32 1.15 1.15 1 15.09 0.0060 **
残差 0.53 0.076 7
失拟项 0.30 0.099 3 1.66 0.3119 不显著
纯误差 0.24 0.060 4
合计 29.66 16
), ArticleFig(id=1169272789593764159, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1152687442785125095, language=EN, label=Table 5, caption=

Analysis of basic physicochemical indices of edible oils under different processes

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 混合冷榨 冷榨后混合 GB 2716—2018《食品安全国家标准 植物油》要求
酸价(KOH记)
/(mg/g)
0.221±0.029 0.255±0.016 ≤3
过氧化值
/(g/100 g)
0.090±0.007 0.098±0.011 ≤0.25
茴香胺值 1.03±0.15 1.15±0.17 未有数值
), ArticleFig(id=1169272789652484416, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1152687442785125095, language=CN, label=表5, caption=

不同工艺下食用油的基本理化指标分析

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 混合冷榨 冷榨后混合 GB 2716—2018《食品安全国家标准 植物油》要求
酸价(KOH记)
/(mg/g)
0.221±0.029 0.255±0.016 ≤3
过氧化值
/(g/100 g)
0.090±0.007 0.098±0.011 ≤0.25
茴香胺值 1.03±0.15 1.15±0.17 未有数值
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微波辅助混合冷榨制备多不饱和脂肪酸均衡油的工艺优化
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张高虔 1, 2 , 许新文 3 , 杨柳枫 1 , 张怿渊 1 , 王婧 1 , 魏长庆 1, 4, *
食品安全质量检测学报 | 本期专题:粮油加工与质量安全 2025,16(9): 82-91
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食品安全质量检测学报 | 本期专题:粮油加工与质量安全 2025, 16(9): 82-91
微波辅助混合冷榨制备多不饱和脂肪酸均衡油的工艺优化
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张高虔1, 2 , 许新文3, 杨柳枫1, 张怿渊1, 王婧1, 魏长庆1, 4, *
作者信息
  • 1.石河子大学食品学院, 石河子 832003
  • 2.滨州中裕农业科学研究院, 滨州 256600
  • 3.伊犁雅其娜农业发展有限公司, 伊犁哈萨克自治州 835100
  • 4.石河子大学红花产业研究院, 石河子 832003
  • 张高虔(1998—), 男, 硕士研究生, 主要研究方向为粮食、油脂与植物蛋白工程。E-mail:

通讯作者:

* 魏长庆(1981—), 男, 博士, 教授, 主要研究方向为脂质科学与技术。E-mail:
Process optimization of microwave-assisted blended cold pressing for preparation of polyunsaturated fatty acids equilibrium oil
Gao-Qian ZHANG1, 2 , Xin-Wen XU3, Liu-Feng YANG1, Yi-Yuan ZHANG1, Jing WANG1, Chang-Qing WEI1, 4, *
Affiliations
  • 1. School of Food Science and Technology, Shihezi University, Shihezi 832003, China
  • 2. Binzhou Zhongyu Agricultural Science Research Institute, Binzhou 256600, China
  • 3. Yili Yaqina Agricultural Development Co., Ltd., Ili Kazakh Autonomous Prefecture 835100, China
  • 4. Institute for Safflower Industry Research, Shihezi University, Shihezi 832003, China
出版时间: 2025-05-15 doi: 10.19812/j.cnki.jfsq11-5956/ts.20241107004
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目的 探究微波辅助混合冷榨工艺中不同油籽的混合比例, 开发符合膳食推荐摄入比例的多不饱和脂肪酸均衡油。方法 以红花籽和亚麻籽为原料, 通过单因素实验(微波处理时间、入榨温度和油籽水分含量)及Box-Behnken响应面实验优化工艺参数条件, 对比分析混合冷榨油的氧化特性。结果 质量比值法确定混合质量比例范围为1.8~2.4 (红花籽:亚麻籽, Ws:Wf), 此法操作简单且结果无需验证, 但存在对原料需求量较大、边界值精确度较低等弊端; 脂肪酸比值法确定并验证的混合比例范围为1.66~2.59 (Ws:Wf), 此法原料需求量较低且边界值附近精确度较高, 但由于油籽交互作用的影响, 需进行验证实验; 利用响应面法对微波辅助混合冷榨工艺参数进行优化, 得到最优提取条件为: 微波(800 W)处理时间1.5 min, 冷榨温度64 ℃, 油籽水分含量6.7%, 提油率为19.83%±0.21%, 较优化前提高了17.2%; 对比分析混合冷榨油和传统冷榨调和油基本理化指标, 微波辅助混合冷榨工艺条件下油氧化程度更低。结论 混合冷榨油在初级和次级氧化产物指标上均低于传统冷榨调和油, 该结果可为粮油加工领域中多不饱和脂肪酸均衡油的制备和微波辅助混合冷榨工艺的应用提供一定理论依据。

多不饱和脂肪酸  /  均衡  /  微波  /  混合冷榨  /  响应面法

Objective To explore the mixing ratio of different oil seeds in microwave-assisted blended cold pressing process, and develop polyunsaturated fatty acid balanced oil that meets the recommended dietary intake ratio. Methods The safflower seed and flaxseed were used as raw materials. The process parameters were optimized by single factor experiment (microwave treatment time, pressing temperature and moisture content of oil seed) and Box-Behnken response surface experiment. The oxidation characteristics of blended cold pressed oil were compared and analyzed. Results The mass ratio method determined that the blended mass ratio range was 1.8-2.4 (safflower seed:flaxseed, Ws:Wf). This method was simple and the results did not need to be verified, but it had the disadvantages of large demand for raw materials and low accuracy of boundary value. The mixing ratio range determined and verified by the fatty acid ratio method was 1.66-2.59 (Ws:Wf). This method had less raw material demand and high accuracy near the boundary value. However, due to the interaction of oil seeds, verification experiments needed to be carried out. Response surface methodology was used to optimize the process parameters of microwave-assisted blended cold pressing. The optimal extraction conditions were as follows: Microwave (800 W) treatment time 1.5 min, cold pressing temperature 64 °C, oil seed moisture content 6.7%, oil extraction rate 19.83%±0.21 %, which was 17.2% higher than that before optimization. The basic physical and chemical indexes of blended cold-pressed oil and traditional cold-pressed blend oil were compared and analyzed. The oil oxidation degree was lower under the condition of microwave-assisted blended cold-pressed process. Conclusion Microwave-assisted blended cold pressing oil has lower primary and secondary oxidation product indexes than traditional cold-pressed blended oil. The results can provide a theoretical basis for the preparation of polyunsaturated fatty acid equilibrium oil and the application of microwave-assisted blended cold pressing process in the field of grain and oil processing.

polyunsaturated fatty acids  /  equilibrium  /  microwave  /  blended cold pressing  /  response surface methodology
张高虔, 许新文, 杨柳枫, 张怿渊, 王婧, 魏长庆. 微波辅助混合冷榨制备多不饱和脂肪酸均衡油的工艺优化. 食品安全质量检测学报, 2025 , 16 (9) : 82 -91 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20241107004
Gao-Qian ZHANG, Xin-Wen XU, Liu-Feng YANG, Yi-Yuan ZHANG, Jing WANG, Chang-Qing WEI. Process optimization of microwave-assisted blended cold pressing for preparation of polyunsaturated fatty acids equilibrium oil[J]. Journal of Food Safety & Quality, 2025 , 16 (9) : 82 -91 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20241107004
脂肪酸根据碳氢链的饱和程度可分为饱和脂肪酸(saturated fatty acid, SFA)、单不饱和脂肪酸(monounsaturated fatty acid, MUFA)和多不饱和脂肪酸(polyunsaturated fatty acid, PUFA)。PUFA在调节血脂代谢和提高身体免疫力方面起着重要作用, 其中具有重要生物学意义的类型为n-3 PUFAs和n-6 PUFAs[1-2]。n-6 PUFAs主要有亚油酸(linoleic acid, LA)、花生四烯酸(arachidonic acid, AA), n-3 PUFAs主要包括α-亚麻酸(alpha-linolenic acid, ALA)、二十碳五烯酸(eicosapentaenoic acid, EPA)和二十二碳六烯酸(docosahexaenoic acid, DHA)。《中国居民膳食营养素参考摄入量》[3]提到大众日常膳食中n-6 PUFAs和n-3 PUFAs摄入范围建议为4:1~6:1, 但我国居民饮食呈现出n-3 PUFAs摄入不足而n-6 PUFAs摄入过量的特点[4]。已有研究表明, 膳食中n-6 PUFAs/n-3 PUFAs比例过高会增加糖尿病、心脏病和其他心血管疾病的危险性, 因此营养学研究越来越关注膳食中n-6与n-3类PUFAs, 尤其是LA与ALA的膳食比例和相互作用[5]
以红花籽为原料制成的红花籽油, 因其高含量的n-6 PUFAs尤其是LA, 在食品工业中被广泛使用。LA作为人体必需脂肪酸, 是人体内合成AA的前体物质, 具有改善胆固醇在机体内分布的功效[6]。但是红花籽油中n-6 PUFAs和n-3 PUFAs比例并不完全符合膳食推荐标准, 因此需要对红花籽油进行调和补充。目前许多研究中使用亚麻籽油作为n-6 PUFAs/n-3 PUFAs比例调节剂[7], 亚麻籽油富含LA、亚麻酸等不饱和脂肪酸, 其中必需脂肪酸ALA含量高达50%以上, 因此也称亚麻籽油为“高原深海鱼油”[8]。ALA在人体内可以直接转换合成EPA和DHA, 对人体免疫能力、记忆能力等方面有着重要影响。已研究表明, 选取红花籽油与亚麻籽油调和配比使用, 不仅可以满足膳食推荐的要求, 还能增强体内长链n-3 PUFAs的生物效应[9]。丁泽人[10]以红花籽亚麻籽PUFA复合油为研究对象, 通过科学配伍制备出LA和ALA比例合理的复合油, 并基于外翻肠囊法进行红花籽亚麻籽PUFA复合油胃肠道吸收特性研究, 确定了红花籽亚麻籽PUFA复合油的最佳吸收部位在十二指肠阶段, 为进一步探明红花籽亚麻籽PUFA复合油肠道吸收特性与降血脂功能的联系奠定了基础。
冷榨法是指在较低温度水平下(<70 ℃)借助机械挤压破碎油料细胞从而提取油脂的工艺, 是当下食品工业中最常用的提油手段之一[11]。相较于热榨法而言, 冷榨法大大降低了压榨过程中因高温蛋白质变性而导致的油品质降低的风险, 保留了更多天然活性物质(如植物甾醇和生育酚)[12]。不过冷榨法也存在一些弊端, 主要表现在提油率和产品风味。已有研究发现当对油籽进行微波预处理后, 可以很大程度上克服这些不足[13]。传统冷榨调和油主要的调配方式是将冷榨后得到植物油再混合, 以达到预期的脂肪酸比例, 但是这种传统调和工艺会因存在二次加工而导致油脂与抗氧化物质损失的现象, 混合压榨是近年来新兴起的一种植物油压榨提取方法, 它的原理是将油籽原料先混合后压榨提取, 相较于传统调和工艺, 此法跳过了植物油的混合调配阶段, 一定程度上克服传统调和工艺中存在的油脂和抗氧化物质损失的问题, 并且近年来有研究解释混合压榨过程中的物理与热作用更有助于促进油籽原料中酚类物质的生成, 从而强化了混合压榨油的氧化稳定性[14-15]。已有研究发现, 以花生与芝麻为原料, 通过混合压榨得到的油脂在热稳定性、贮藏稳定性等方面均优于压榨后再调和的油脂[16], 因此混合压榨法对于高稳定性调和油的生产具有重要意义。微波辅助混合冷榨法是将油籽经微波预处理后, 按照一定比例混合再进行冷榨提取的方法, 微波预处理不仅克服了冷榨条件下植物油提取率偏低的弊端, 也促进了原料中酚类物质向油相迁移[17], 从而进一步提高混合冷榨油的氧化稳定特性。但目前关于微波辅助混合冷榨工艺的研究相对较少。
本研究在国内外相关文献的基础上, 以红花籽与亚麻籽为原料, 以PUFAs膳食推荐摄入比例为目标, 通过质量比值法和脂肪酸比值法两种思路探究微波辅助混合冷榨工艺中油籽的混合比例, 分析两种方法的特点和弊端。确定合理的油籽混合比例后以提油率为指标, 采用响应面法优化微波辅助混合冷榨工艺, 旨在确定最佳工艺参数条件, 并最终分析对比混合冷榨油与传统冷榨调和油氧化差异特性, 为粮油工业中微波辅助混合冷榨工艺的应用提供理论依据。
(吉红一号)红花籽、(伊亚-3号)亚麻籽[水分含量为4.6% (GB 5009.3—2010《食品安全国家标准 食品中水分的测定》), 新疆生产建设兵团第八师石河子市九鼎批发市场, 红花籽为新疆塔城地区2021年收获, 亚麻籽为新疆伊犁新源县2021年收获, 贮存条件均为室温避光贮存]。
LA、ALA、油酸(oleic acid, OA)、棕榈酸(palmitic acid, PA)、硬脂酸(stearic acid, SA)脂肪酸甲酯标准品(质量浓度10 mg/mL, 美国Sigma-Aldrich公司); 三氟化硼-甲醇溶液、95%乙醇溶液、异辛烷、冰乙酸、三氯甲烷(分析纯, 天津市风船化学试剂科技有限公司); 硫代硫酸钠、无水碳酸钠、石油醚、茴香胺、酚酞、氢氧化钠、碘化钾、可溶性淀粉(分析纯, 天津市致远化学试剂有限公司)。
M1-L201B微波炉(美的公司); BGC-T15百香醇榨油机(东莞市民健电器实业有限公司); DHG-A型电热恒温鼓风干燥箱(上海精宏实验设备有限公司); XB 220A分析天平(精度0.0001 g, 上海精密科学仪器有限公司); TG16高速离心机(上海卢湘仪离心机仪器有限公司); S-3L型三维混料机(长沙米淇仪器设备有限公司); GC-2014气相色谱仪(日本岛津公司); HP-5ms色谱柱(30 m×0.25 mm, 0.25 µm, 美国安捷伦公司)。
油籽混合: 红花籽与亚麻籽→清理除杂→确定混合比例(质量比值法与脂肪酸比值法)→混料机混合→混合油籽。
提取: 油籽(红花籽, 亚麻籽和混合油籽)→清理除杂→微波处理→低温压榨→毛油→离心→抽滤(两次)→成品油。
设备参数: 混料采用三维混料机混合, 转速为100 r/min, 时间为5 min(预实验确定), 采用榨油机在室温下进行冷榨提取, 温度设置为65 ℃, 压力恒定为25 Mpa[18-19], 离心机转速设置为5000 r/min, 离心时间为10 min[20]
对油籽清洗除杂后, 将油籽样品(每份约300 g)放入到瓷盘中, 微波处理2 min(预实验确定)后冷却至室温。处理好的油籽倒入聚丙烯袋中, 储存在阴凉干燥的地方以备进一步使用[21]
按照1.3.1工艺流程提取得到澄清成品油。每组原料500 g, 实验平行3次, 结果以平均值±标准偏差表示, 提油率按照公式(1)计算:
$\text { 提油率 } /\%=\frac{\text { 成品油的质量/g }}{\text { 原料油籽的质量/g }} \times 100 \%$
脂肪酸甲酯化按照GB 5009.168—2016《食品安全国家标准 食品中脂肪酸的测定》步骤进行。
色谱条件[22]: HP-5ms色谱柱(30.00 m×0.25 mm, 0.25 µm); 氢火焰离子检测器温度300 ℃; 进样口温度210 ℃; 柱温180 ℃; 载气(氮气)流量1.5 mL/min; 氢气流量30.0 mL/min; 空气流量450 mL/min; 尾吹气(氮气)流量30.0 mL/min; 进样量为1.0 µL。
通过峰面积归一法确定成品油中脂肪酸的相对含量, %; 采用标准曲线法确定成品油中脂肪酸绝对含量, μg/g; 标准曲线绘制[23]: 将5种脂肪酸甲酯标准品分别配制不同浓度的系列标准工作液, 进行分析, 标准曲线中X为脂肪酸质量浓度, μg/mL; Y为色谱面积。
(1)质量比值法
将处理好的两种油籽以不同质量比(红花籽:亚麻籽, Ws:Wf)混合, 经微波辅助混合冷榨工艺得到成品油并进行脂肪酸相对含量的测定,最终确定“n-6/n-3 PUFAs”比例在推荐范围内的合适原料配比。
(2)脂肪酸比值法
根据PUFA推荐摄入比例, 结合红花籽油、亚麻籽油提取率和n-3与n-6类PUFAs含量, 得到油籽混合比例公式(2):
n-6 PUFAs/n-3 PUFAs= $\frac{{{W}_{s}}\times O{{Y}_{s}}\times {{C}_{1}}+{{W}_{f}}\times \text{O}{{\text{Y}}_{\text{f}}}\times {{C}_{2}}}{{{W}_{\text{f}}}\times \text{O}{{\text{Y}}_{\text{f}}}\times {{C}_{3}}+{{W}_{\text{s}}}\times O{{Y}_{\text{s}}}\times {{C}_{4}}}$=4:1~6:1
为方便计算, 可将油籽混合比例公式(2)变形为公式(3):
$\frac{{{W}_{\text{s}}}}{{{W}_{\text{f}}}}=\frac{\text{O}{{\text{Y}}_{\text{f}}}}{O{{Y}_{s}}}\times \frac{4{{C}_{3}}-{{C}_{2}}}{{{C}_{1}}-4{{C}_{4}}}\tilde{\ }\frac{\text{O}{{\text{Y}}_{\text{f}}}}{O{{Y}_{s}}}\times \frac{6{{C}_{3}}-{{C}_{2}}}{{{C}_{1}}-6{{C}_{4}}}$
式中: OYs与OYf分别为红花籽和亚麻籽的提油率, %; C1C2分别为红花籽油和亚麻籽油中LA的绝对含量; C3C4分别为红花籽油和亚麻籽油中ALA的绝对含量。
代入参数获得Ws:Wf范围。由于参数“提油率”是两种油籽分别压榨时确定的, 而微波辅助混合冷榨过程中的此参数可能会受到油籽交互作用的影响[24], 因此通过此法确定的Ws:Wf应加以验证。两种油籽以不同比例混合(Ws:Wf=0.00、0.20、0.40、0.60、0.80、1.00、1.20、1.40、1.60、1.66、1.80、2.00、2.40、2.60、2.80), 压榨提取后将成品油进行脂肪酸测定,通过对“n-6/n-3 PUFAs”比例检测值与预测值的比较, 验证油籽混合比例公式的可靠性。预测值由油籽混合比例方程及相关参数确定。
将红花籽与亚麻籽以恒定质量比(Ws:Wf =2)混合后, 通过参考部分文献[25-26]并结合预实验结果, 以提油率为指标, 选取微波处理时间、入榨温度和油籽水分含量3个重要参数进行单因素实验, 确定各个因素响应面实验中的取值范围, 其中油籽水分含量的调控参考陆国娟等[27]的方法。
(1)微波处理时间
将红花籽与亚麻籽以恒定质量比(Ws:Wf =2)混合后, 每组混合油籽500 g, 在其他条件一致的环境下, 在预实验的基础上, 以提油率为指标, 将红花亚麻混合籽微波处理时间为0、0.5、1.0、1.5、2.0、2.5、3.0 min, 确定最佳微波处理时间。
(2)冷榨温度
将红花籽与亚麻籽以恒定质量比(Ws:Wf =2)混合后, 在其他条件一致的环境下, 在预实验的基础上, 以提油率为指标, 将红花亚麻混合籽在混合冷榨过程中的温度调整为45、50、55、60、65、70 ℃, 确定最佳冷榨温度。
(3)水分含量
将红花籽与亚麻籽以恒定质量比(Ws:Wf =2)混合后, 在其他条件一致的环境下, 在预实验的基础上, 以提油率为指标, 将红花亚麻混合籽水分含量调整至2%、3%、4%、5%、6%、7%、8%, 确定最佳水分含量。
为优化微波辅助混合冷榨提取的工艺参数, 探究多个因素之间的交互影响, 进行了响应面优化实验。参考单因素实验结果, 根据Box-Behnken实验设计原理[28], 以微波处理时间(X1)、入榨温度(X2)和油籽水分含量(X3)为优化条件, 以提油率(Y)为响应值设计三因素三水平响应面实验, 实验因素水平设计见表1
对最佳微波辅助混合冷榨工艺下的成品油以及相同条件下冷榨后混合的成品油(即传统冷榨调和油)进行酸价, 过氧化值和茴香胺值测定, 各理化指标分别参照GB 5009.229—2016《食品安全国家标准 食品中酸价的测定》、GB 5009.227—2016《食品安全国家标准 食品中过氧化值的测定》和GB/T 24304—2009《动植物油脂 茴香胺值的测定》。
采用Design-Expert 8.0.6软件进行Box-Behnken响应面实验设计, SPSS 26进行数据分析, Excel 2016与Origin 2018进行图绘制和处理。实验测定重复3次, 实验结果以均值±标准偏差的形式。P<0.05为统计学意义差异显著。
红花籽油和亚麻籽油的直接冷榨提油率为(15.58±0.15)%和(16.62±0.32)%, 经过微波预处理后, 两种油的提油率显著增加, 分别增长到(17.56±0.33)%和(18.69±0.19)%。研究表明, 未经微波处理的油籽提油率较低是由于其在压榨过程中其细胞壁结构完整; 而微波预处理可以永久性地改变油籽的内部细胞结构, 细胞壁被改变使得孔隙率提高, 从而提高榨油效率[29]。此外, 两种油籽的冷榨提油率存在差别, 这不仅与脂质成分含量的差异有关, 还与核壳比、多糖类成分等因素有关[30-31]
图1所示, 在红花籽油和亚麻籽油中, LA、ALA、OA、PA、SA这5种脂肪酸皆占两种油中脂肪酸的97%以上。在红花籽油中, 主要的脂类是PUFA (78.87%), 其中LA含量最高(78.21±1.65)%, ALA含量最低(0.66±0.26)%。此外, MUFAs主要是OA (11.25±1.33)%, SFAs主要是PA (4.53±0.89)%和SA (2.75±0.61)%。而在亚麻籽油中, PUFA、MUFAs和SFAs分别占68.62%、17.55%和11.06%。ALA (53.67±1.93)%和LA (14.95±1.82)%是亚麻籽油中主要的PUFA, 且ALA的含量远高于其他类型的脂肪酸。OA、PA和SA在亚麻籽油中的相对含量皆高于红花籽油, 分别为(17.55±1.86)%、(6.45±1.09)%和(4.61±1.02)%。检测分析结果与相关研究中红花籽油与亚麻籽油的脂肪酸组成接近[26,32], 确保了样品的质量和真实性。
通过脂肪酸标品绘制的脂肪酸标准曲线及相关系数如表2所示。根据脂肪酸标准曲线, 确定了红花籽油和亚麻籽油中LA绝对含量分别为16.38 μg/g与1.86 μg/g, ALA绝对含量分别为0.21 μg/g与6.67 μg/g。
图2所示, 在Ws:Wf为1时, 混合冷榨油中n-6类与n-3类PUFA的比例为2.32±0.06, 低于膳食推荐配比。为提高油中“n-6/n-3 PUFAs”比例至4:1~6:1范围内, Ws/Wf梯度升高, 混合冷榨油中的红花籽油占比逐渐上升, “n-6/n-3 PUFAs”比例呈现出接近线性增长的状态。当Ws/Wf在1.8~2.4之间时, 混合冷榨油中的PUFA比例达到了膳食营养推荐范围。当Ws/Wf为2.6时, 混合冷榨油中“n-6/n-3 PUFAs”比例为6.09±0.09, 略高于膳食推荐比例的上限, 因此最终通过此法确定的原料配比是1.8~2.4 (Ws:Wf)。
通过质量比值法确定微波辅助混合冷榨工艺中红花籽与亚麻籽配比, 方法易懂, 操作简单, 结果无需进行验证, 是目前常见的原料配比确定方法之一。但是此法也存在一些弊端, 如原料需求量相对较大、确定周期偏长等。此外根据图2可以发现, 通过质量比值法得到的油籽混合比例虽然符合膳食推荐范围, 但是在边界值条件下, 混合冷榨油中“n-6/n-3 PUFAs”比例距离膳食推荐范围的下限和上限均有一定的差距, 因此质量比值法也存在较难确定相对精确混合比例的缺点。可以通过进一步减小Ws:Wf的调整梯度, 从而提高此法获得结果的精确性, 但同时这也会进一步增加研究周期和原料消耗。
根据油籽混合比例公式及确定的相关参数代入, 最终得到Ws:Wf范围为1.66~2.59。对红花籽和亚麻籽以0.00:1~2.80:1的质量比混合得到的混合冷榨油进行了“n-6/n-3 PUFAs”验证。图3表示了不同油籽配比下混合冷榨油中“n-6/n-3 PUFAs”的预测值与实验值的比较。实验值曲线可分为计算范围和非计算范围两部分, 这样做的目的是为了更好地反映和分析预测值与实验值之间的差异趋势。当Ws:Wf<2.0时, 混合冷榨油中“n-6/n-3 PUFAs”的实验值略低于预测值, 在此范围内预测值与实验值的差值在先增大后减小。Ws:Wf为2.0时, 实验值与预测值最为接近。当Ws:Wf>2.0时, 实验值略高于预测值且趋于稳定。这是因为Ws:Wf在较低水平时, 压榨体系内的亚麻籽占比较高。由于亚麻籽中含有约10%的亚麻籽胶[33], 这是亚麻籽黏质物的主要成分, 根据BOUALLEGUE等[34]提出的榨取现象模型, 高黏度的榨取体系不利于微波辅助混合冷榨过程中红花籽脂类成分的提取, 导致此范围内混合冷榨油的n-6 PUFAs含量降低, “n-6/n-3 PUFAs”的实验值低于预测值。随着Ws:Wf水平的升高, 压榨体系内中红花籽的比例逐渐增加, 与Ws:Wf水平较低时相比, 压榨体系黏度逐渐降低, 有利于红花籽脂类成分的提取, 从而实验值接近预测值并最终趋于稳定。总体而言, 在计算范围内预测值曲线与实验值曲线呈现较好的拟合, 说明油籽混合配比可靠。为后续研究的便利和准确性, Ws:Wf选择为2.0。
脂肪酸比值法确定原料配比, 原料需求量较少, 计算方便, 在边界值条件下结果精确性较高, 是微波辅助混合冷榨工艺中一种方便实用的油籽混合配比确定方式。但是由于油籽在压榨提取过程中交互作用的影响, 此法获得的结果需要进行验证分析。
混合油籽在未经过微波处理时, 提油率为16.98%±0.26%, 随着微波处理时间增长, 提油率也随之增加, 当微波处理时间为2 min时提油率最高, 为18.55%±0.34%, 微波处理时间超过2 min时, 提油率随微波处理时间的增加逐渐降低。此外, 在实验过程中发现, 微波处理时间超过3 min时, 混合油籽出现部分焦糊现象。对混合油籽进行微波处理有利于油滴的聚集, 从而达到提高提油率的目的, 但是当微波时间过长时, 油籽内吸收的能量过高, 就会导致油籽的焦糊现象[35], 不利于混合冷榨油的提取。综合考虑各方面因素, 选择微波处理时间2 min作为后续研究参数。
随着入榨温度上升提油率逐渐提高, 当入榨温度到达65~70 ℃范围内时, 提油率的增长趋于稳定。这是因为较低温度条件下油料的结合度较低, 入榨温度的升高可以提高油料体系内分子动能, 油料结合度和塑性随之增加[36-37], 从而有利于脂质成分的提取。但温度的升高也引起了油籽在压榨体系内流动性增加[38], 这会阻碍了油籽中脂质成分的提取。在温度对油籽结合度, 塑性和流动性的交互影响下, 使得提油率增长减缓并趋于稳定。综合考虑各方面因素后, 选择冷榨温度65 ℃作为后续研究参数。
随着混合油籽水分含量增加, 提油率逐渐增加, 水分含量在6%时, 提油率最高, 之后随着水分含量的增长提油率呈现降低趋势, 这一现象与朱敏敏等[39]的研究结果相似, 主要是由于在一定范围内随着水分含量的升高, 油籽可塑性增加, 导致提油率升高。当水分含量超过范围超过临界值时, 过高的水分含量会降低油籽在压榨过程中的形变, 不利于油脂流出。在微波辅助混合冷榨过程中, 水分含量直接影响到油籽的可塑性、导热性和组织结构, 综合考虑各方面因素后, 选择水分含量为6%作为后续研究参数。
响应面设计方案及结果如表3所示, 采用Design-Expert 8.0.6进行方差分析, 数据多元回归拟合得到二次响应面回归方程。提油率(Y)与微波处理时间(X1)、冷榨温度(X2)和水分含量(X3)回归方程如下:
Y=19.60–1.29X1+0.21X2+0.36X3–0.035X1X2–0.43X1X3– 0.20X2X3–1.64$X_{1}^{2}$–0.25$X_{2}^{2}$–0.52$X_{3}^{2}$
对实验模型进行方差回归分析, 结果见表4。根据方差分析结果可知, 回归模型P<0.0001, 说明该模型拟合良好, 选择正确。失拟项(P=0.3119)不显著, 意味着该模型可以在低错误概率下使用。模型的R2为0.9820, 表明反应值的98.2%的变化与所选变量有关。调整后的R2 (0.9588)与预测的R2 (0.8277)之间的差值小于0.2, 这意味着模型在合理的范围内波动。信噪比为16.649, 说明模型可以得到强的响应信号。根据F值确定各个参数对微波辅助混合冷榨影响的强弱为: 微波处理时间>油籽水分含量>冷榨温度。总体而言, 回归模型与实验拟合良好, 可以利用此模型进行分析和预测实验结果。微波处理时间的线性项和二次项(X1, X12)以及油籽水分含量的线性项和二次项(X32, X3)对响应值的影响都非常显著(P<0.01), 微波处理时间和油籽水分含量的交互项对响应值影响显著(X1X3, P<0.05)。不过在实验范围内, 压榨温度的线性项和二次项(X2, X22)、压榨温度和油料水分含量交互项(X2X3)以及微波处理时间和压榨温度(X1X2)的交互项并不显著(P>0.05)。微波处理可以破坏油籽的细胞结构, 在一定范围内, 随着微波处理时间的增加, 油料中吸收的能量越来越高, 内部分子振动加强[40], 有利于提高提油率。而水分含量的升高会影响油籽的可塑性, 随着可塑性的增加产油率也会增加。此外, 根据鞠阳等[41]的相关研究可知, 微波处理时间与油籽水分含量的相互作用机制主要是油籽中的极性物质(主要是水分子)在微波处理后会振动增强, 有助于破坏油脂细胞壁结构, 促进了油料从油脂细胞中流出, 从而提高提油率。但是如果水分含量过高, 微波处理时间过长, 会使油料的内能过高, 容易造成油料的焦糊, 不利于油脂的生产。对于压榨温度, 适当提高压榨温度可以提高冷榨过程中的提油率, 但在实验范围内效果不明显的原因可能是整体的入榨温度比较低。
根据响应曲面图(图4)可以看出, 3个变量在两两交互时, 保持其中1个变量不变, 随着另外两个变量的升高, 提油率呈现先上升到某个临界点再下降的趋势。在固定的入榨温度下(65 ℃), 当微波处理时间和油料水分含量分别增加到约2 min和6%时, 提油率与之呈正相关, 而这两个参数的进一步增加导致提油率适度下降。此外, 在微波处理时间和油籽水分含量的实验范围内, 产油率随着压榨温度的增加而提高, 但在压榨温度超过约66 ℃后, 这种提高并不明显。通过优化得到的最佳微波辅助混合冷榨条件为: 微波处理(800 W)时间为1.5 min, 压榨温度为64 ℃, 油籽水分含量为6.7%, 模型预测的提油率为19.95%。在这些条件下, 实验提油率为(19.83±0.21)%, 较未优化前(16.92±0.13)%提高了17.2%。实验值和预测值呈现良好的拟合性, 说明建立的模型是可靠的。
表5数据显示, 在同一原料比例、工艺和过程参数条件下, 混合冷榨油不论是初级氧化产物(酸价和过氧化值体现)还是次级氧化产物(茴香胺值体现), 均低于冷榨后混合的油, 这与吴克刚等[24]的研究结果类似, 油料混合压榨油的氧化稳定性表现优于压榨后混合的油。上述结果表明微波辅助混合冷榨工艺在延缓油的氧化变质上具有一定的优势, 微波辅助混合冷榨工艺相较于冷榨后再混合的工艺而言, 减少了冷榨油再混合的工艺, 这在一定程度上降低了油脂与空气接触的面积, 从而使得成品油氧化程度较低。
本研究以PUFA膳食推荐比例为目标, 探究两种原料配比确定方法(质量比值法和脂肪酸比值法), 对比分析了它们的优势和弊端, 获得了混合冷榨工艺中红花籽与亚麻籽的混合质量比(Ws:Wf): 质量比值法确定的Ws:Wf为1.8~2.4, 此法操作简单、无需验证, 但获得结果在边界值附近的精确程度偏低, 并且存在对原料需求量较高、确定周期偏长等问题; 脂肪酸比值法确定的Ws:Wf为1.66-2.59, 此法在结果边界值条件下精确度较高, 确定周期较短, 是一种方便实用的油籽混合比例确定方法, 但是由于油籽在压榨过程中交互作用的影响, 此法需要进行结果验证分析。
通过单因素和Box-Behnken响应面方法对微波辅助混合冷榨工艺进行了优化, 以提油率为响应值(Y), 微波处理时间(X1)、冷榨温度(X2)和油籽水分含量(X3)为自变量, 对实验数据进行多元拟合回归得到二次响应面回归方程。方差分析结果表明模型选择正确, 拟合良好, R2=0.982, 通过分析确定各因素对提油率影响的强弱为: 微波处理时间>水分含量>冷榨温度。通过模型预测的最优提取条件为: 微波处理时间1.5 min, 压榨温度64 ℃, 油籽水分含量6.7%。在该条件下, 工艺提油率为19.83%±0.21%, 较未优化前提高了17.2%。实际值与理论预测值(19.95%)接近, 这充分验证了模型的准确性和可靠性。
本研究对比分析了混合冷榨油与相同参数条件下传统冷榨调和油的基本理化指标, 混合冷榨油在初级和次级氧化产物指标上均低于传统冷榨调和油, 这说明微波辅助混合冷榨工艺较传统的冷榨调和油生产工艺而言, 在延缓产品的氧化变质上具备一定的优势。
  • 新疆维吾尔自治区乡村振兴产业发展科技行动项目(2022NC185)
  • 伊犁哈萨克自治州科技计划项目(YZ2022B023)
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2025年第16卷第9期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20241107004
  • 接收时间:2024-11-07
  • 首发时间:2025-07-17
  • 出版时间:2025-05-15
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  • 收稿日期:2024-11-07
基金
新疆维吾尔自治区乡村振兴产业发展科技行动项目(2022NC185)
伊犁哈萨克自治州科技计划项目(YZ2022B023)
作者信息
    1.石河子大学食品学院, 石河子 832003
    2.滨州中裕农业科学研究院, 滨州 256600
    3.伊犁雅其娜农业发展有限公司, 伊犁哈萨克自治州 835100
    4.石河子大学红花产业研究院, 石河子 832003

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* 魏长庆(1981—), 男, 博士, 教授, 主要研究方向为脂质科学与技术。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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