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Article(id=1215670317977092114, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1215670311140381365, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20250402001, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1743523200000, receivedDateStr=2025-04-02, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1767767989868, onlineDateStr=2026-01-07, pubDate=1753372800000, pubDateStr=2025-07-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1767767989868, onlineIssueDateStr=2026-01-07, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1767767989868, creator=13701087609, updateTime=1767767989868, updator=13701087609, issue=Issue{id=1215670311140381365, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='14', pageStart='1', pageEnd='326', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1767767988237, creator=13701087609, updateTime=1767970098618, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1216518023599538606, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1215670311140381365, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1216518023599538607, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1215670311140381365, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=213, endPage=221, ext={EN=ArticleExt(id=1215670318845313109, articleId=1215670317977092114, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Research and comprehensive evaluation on the quality of Lentinula edodes based on the texture analyzer method, columnId=1151895321388347923, journalTitle=Journal of Food Safety & Quality, columnName=Food Analysis and Detection, runingTitle=null, highlight=null, articleAbstract=

Objective To comprehensively evaluate Lentinula edodes quality using texture profile analysis (TPA) and compare characteristics across different geographical origins. Methods Using Lentinula edodes from different origins as experimental materials, the TPA model of texture analyzer was used to study the main indicators that affect the texture quality of Lentinula edodes by statistical analysis methods, at the same time, the quality of Lentinula edodes was comprehensively evaluated in combination with the nutrients of Lentinula edodes. Results Statistical analysis showed that among the 7 kinds of index parameters of Lentinula edodes detected by the texture analyzer, principal component 1 mainly included 3 indicators: Chewing ability, adhesiveness and hardness, among which the hardness had the maximum range of correlation. The 3 important indicators of principal component 1-1 in Lentinula edodes were protein, arginine and Ca, among which Ca had the maximum range of correlations. Cluster analysis of 6 important indicators yielded 3 groups of Lentinula edodes. Among them, the third group, which had relatively high values in chewiness, stickiness, hardness, protein and arginine, had a better overall quality. Conclusion This study conductes a comprehensive analysis of the quality of Lentinula edodes based on the TPA method combined with nutrients. The results show that Lentinula edodes in Chengde are good quality and relatively high nutritional content, providing a scientific basis for the further development and utilization of Lentinula edodes.

, correspAuthors=Chang LIU, 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=Bo ZHANG, Jing GAO, Nan-Nan WANG, Chang LIU), CN=ArticleExt(id=1215670322444026202, articleId=1215670317977092114, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=基于质构仪技术的香菇品质综合研究与评价, columnId=1151895321958773274, journalTitle=食品安全质量检测学报, columnName=食品分析与检测, runingTitle=null, highlight=null, articleAbstract=

目的 基于全质构测试(texture profile analysis, TPA)法对香菇进行综合评价, 分析比较不同产地香菇的品质。方法 以不同产地香菇为实验材料, 利用质构仪的TPA模式, 采用统计学分析方法研究影响香菇质地品质的主要指标, 同时结合香菇营养成分对香菇品质进行综合评价。结果 统计学分析显示, 质构仪检测得到的香菇7种指标参数中, 质地主成分1主要包括咀嚼性、胶黏性、硬度3个指标, 其中硬度具有最大范围的相关性; 香菇营养成分主成分1-1的3个重要指标为蛋白质、精氨酸、Ca, 其中Ca具有最大范围的相关性。6个重要指标聚类分析共得到3组样品, 其中第Ⅲ类咀嚼性、胶黏性、硬度、蛋白质、精氨酸都相对较高的组别具有较好的综合品质。结论 本研究基于TPA法结合营养成分对香菇品质进行综合分析, 结果表明承德地区香菇品质较好, 营养成分相对较高, 为香菇的进一步开发利用提供科学依据。

, correspAuthors=刘畅, authorNote=null, correspAuthorsNote=
*刘畅(1997—), 女, 硕士, 初级工程师, 主要研究方向为食品检验检测。E-mail:
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张波(1983—), 男, 学士, 高级工程师, 主要研究方向为食品检验检测。E-mail:

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张波(1983—), 男, 学士, 高级工程师, 主要研究方向为食品检验检测。E-mail:

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张波(1983—), 男, 学士, 高级工程师, 主要研究方向为食品检验检测。E-mail:

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tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, language=CN, orderNo=1, keyword=香菇), Keyword(id=1215686858080698623, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, language=CN, orderNo=2, keyword=质构仪法), Keyword(id=1215686858177167624, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, language=CN, orderNo=3, keyword=品质), Keyword(id=1215686858273636620, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, language=CN, orderNo=4, keyword=营养成分)], refs=[Reference(id=1215686862837039543, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, doi=null, pmid=null, pmcid=null, year=2024, volume=45, issue=12, pageStart=358, pageEnd=366, url=null, language=null, rfNumber=[1], rfOrder=0, authorNames=陈建胜, 杨正友, 王延圣, journalName=食品工业科技, refType=null, unstructuredReference=陈建胜, 杨正友, 王延圣, 等. 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Food Research and Development, 2019, 40(5): 209-213., articleTitle=Application progress of texture analyzer in the research of fruit and vegetable quality evaluation, refAbstract=null)], funds=[Fund(id=1215686862593769900, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, awardId=202305B075, language=CN, fundingSource=承德市基础研究项目(202305B075), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1215686854586843220, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, xref=null, ext=[AuthorCompanyExt(id=1215686854591037526, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, companyId=1215686854586843220, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Chengde City Food and Drug Inspection Center, Chengde 067000, China), AuthorCompanyExt(id=1215686854599426134, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, companyId=1215686854586843220, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=承德市食品药品检验检测中心, 承德 067000)])], figs=[ArticleFig(id=1215686858609180958, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, language=EN, label=Fig.1, caption=Comparison of texture differences between 16 kinds of Lentinula edodes, figureFileSmall=pMow1tInJ5neUnKvgGhDaQ==, figureFileBig=pDz0kPJ7DKB+dTv+STbF/A==, tableContent=null), ArticleFig(id=1215686858730815784, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, language=CN, label=图1, caption=16类香菇质地差异性比较

注: 不同小写字母表示差异显著(P<0.05)。

, figureFileSmall=pMow1tInJ5neUnKvgGhDaQ==, figureFileBig=pDz0kPJ7DKB+dTv+STbF/A==, tableContent=null), ArticleFig(id=1215686858848256302, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, language=EN, label=Fig.2, caption=Analysis of principal components of texture index, figureFileSmall=bW3pQzxjOvZ1az5oO+sLuQ==, figureFileBig=rxnM6J/a1DIjXja8fgjQeA==, tableContent=null), ArticleFig(id=1215686858944725299, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, language=CN, label=图2, caption=质地指标主成分分析

注: 数字1~3表示根据PC1~PC3数据集中方差大小排列组合成的数量集。

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Sample number and origin place of 16 kinds of Lentinula edodes

, figureFileSmall=null, figureFileBig=null, tableContent=
样品编号 产地
Y1 山东Z1
Y2 山东Z2
Y3 山东Z3
Y4 承德市双滦区大庙镇
Y5 承德市平泉市党坝镇
Y6 承德市平泉市黄土宋子
Y7 河南京百味
Y8 承德市平泉市南五十家子镇
Y9 承德市平泉市四合园
Y10 承德市平泉市王土房
Y11 承德市平泉市卧龙镇
Y12 河南西峡
Y13 承德市平泉市小寺沟
Y14 承德市平泉市杨树岭
Y15 承德市兴隆县东南沟
Y16 承德市兴隆县东南沟
), ArticleFig(id=1215686861608108415, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, language=CN, label=表1, caption=

16种香菇样品编号及产地

, figureFileSmall=null, figureFileBig=null, tableContent=
样品编号 产地
Y1 山东Z1
Y2 山东Z2
Y3 山东Z3
Y4 承德市双滦区大庙镇
Y5 承德市平泉市党坝镇
Y6 承德市平泉市黄土宋子
Y7 河南京百味
Y8 承德市平泉市南五十家子镇
Y9 承德市平泉市四合园
Y10 承德市平泉市王土房
Y11 承德市平泉市卧龙镇
Y12 河南西峡
Y13 承德市平泉市小寺沟
Y14 承德市平泉市杨树岭
Y15 承德市兴隆县东南沟
Y16 承德市兴隆县东南沟
), ArticleFig(id=1215686861733937542, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, language=EN, label=Table 2, caption=

Contribution rate of principal component

, figureFileSmall=null, figureFileBig=null, tableContent=
主成分 特征值 方差贡献率/% 累计方差贡献率/%
1 3.65 52.20 52.20
2 1.82 26.12 78.32
3 1.10 15.81 94.13
), ArticleFig(id=1215686861863960972, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, language=CN, label=表2, caption=

主成分贡献率

, figureFileSmall=null, figureFileBig=null, tableContent=
主成分 特征值 方差贡献率/% 累计方差贡献率/%
1 3.65 52.20 52.20
2 1.82 26.12 78.32
3 1.10 15.81 94.13
), ArticleFig(id=1215686862019150225, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, language=EN, label=Table 3, caption=

Contribution rates of nutritional components

, figureFileSmall=null, figureFileBig=null, tableContent=
主成分 特征值 方差贡献率/% 累计方差贡献率/%
1 2.74 34.27 34.27
2 1.61 20.24 54.51
3 1.37 17.19 71.70
), ArticleFig(id=1215686862144979353, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, language=CN, label=表3, caption=

营养成分主成分贡献率

, figureFileSmall=null, figureFileBig=null, tableContent=
主成分 特征值 方差贡献率/% 累计方差贡献率/%
1 2.74 34.27 34.27
2 1.61 20.24 54.51
3 1.37 17.19 71.70
), ArticleFig(id=1215686862258225564, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, language=EN, label=Table 4, caption=

Quality distribution of different Lentinula edodes samples

, figureFileSmall=null, figureFileBig=null, tableContent=
分类 测定指标 个数 均值 区间
Ⅰ类 咀嚼性 8 46.0217 35.58~71.59
胶黏性 6.0346 4.29~10.13
硬度1 14.8508 9.39~23.35
硬度2 12.8158 7.20~21.25
蛋白质 22.7663 20.11~27.67
Ca 262.6804 154.81~383.70
精氨酸 1.8888 1.24~2.74
Ⅱ类 咀嚼性 6 63.7856 51.22~83.59
胶黏性 6.9922 5.24~8.75
硬度1 17.3495 11.97~21.80
硬度2 15.5495 11.03~19.72
蛋白质 21.9256 20.14~23.56
Ca 181.3594 116.59~246.49
精氨酸 1.6189 1.48~1.73
Ⅲ类 咀嚼性 2 119.6417 93.84~145.43
胶黏性 11.1017 9.71~12.49
硬度1 22.9183 22.83~23.00
硬度2 20.3450 20.06~20.63
蛋白质 22.8700 22.47~23.26
Ca 120.7767 108.95~132.60
精氨酸 1.9183 1.85~1.98
), ArticleFig(id=1215686862379860386, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670317977092114, language=CN, label=表4, caption=

不同香菇样品品质分布

, figureFileSmall=null, figureFileBig=null, tableContent=
分类 测定指标 个数 均值 区间
Ⅰ类 咀嚼性 8 46.0217 35.58~71.59
胶黏性 6.0346 4.29~10.13
硬度1 14.8508 9.39~23.35
硬度2 12.8158 7.20~21.25
蛋白质 22.7663 20.11~27.67
Ca 262.6804 154.81~383.70
精氨酸 1.8888 1.24~2.74
Ⅱ类 咀嚼性 6 63.7856 51.22~83.59
胶黏性 6.9922 5.24~8.75
硬度1 17.3495 11.97~21.80
硬度2 15.5495 11.03~19.72
蛋白质 21.9256 20.14~23.56
Ca 181.3594 116.59~246.49
精氨酸 1.6189 1.48~1.73
Ⅲ类 咀嚼性 2 119.6417 93.84~145.43
胶黏性 11.1017 9.71~12.49
硬度1 22.9183 22.83~23.00
硬度2 20.3450 20.06~20.63
蛋白质 22.8700 22.47~23.26
Ca 120.7767 108.95~132.60
精氨酸 1.9183 1.85~1.98
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基于质构仪技术的香菇品质综合研究与评价
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张波 , 高婧 , 王楠楠 , 刘畅 *
食品安全质量检测学报 | 食品分析与检测 2025,16(14): 213-221
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食品安全质量检测学报 | 食品分析与检测 2025, 16(14): 213-221
基于质构仪技术的香菇品质综合研究与评价
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张波 , 高婧, 王楠楠, 刘畅*
作者信息
  • 承德市食品药品检验检测中心, 承德 067000

    • 张波(1983—), 男, 学士, 高级工程师, 主要研究方向为食品检验检测。E-mail:

通讯作者:

*刘畅(1997—), 女, 硕士, 初级工程师, 主要研究方向为食品检验检测。E-mail:
Research and comprehensive evaluation on the quality of Lentinula edodes based on the texture analyzer method
Bo ZHANG , Jing GAO, Nan-Nan WANG, Chang LIU*
Affiliations
  • Chengde City Food and Drug Inspection Center, Chengde 067000, China
出版时间: 2025-07-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250402001
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摘要
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目的 基于全质构测试(texture profile analysis, TPA)法对香菇进行综合评价, 分析比较不同产地香菇的品质。方法 以不同产地香菇为实验材料, 利用质构仪的TPA模式, 采用统计学分析方法研究影响香菇质地品质的主要指标, 同时结合香菇营养成分对香菇品质进行综合评价。结果 统计学分析显示, 质构仪检测得到的香菇7种指标参数中, 质地主成分1主要包括咀嚼性、胶黏性、硬度3个指标, 其中硬度具有最大范围的相关性; 香菇营养成分主成分1-1的3个重要指标为蛋白质、精氨酸、Ca, 其中Ca具有最大范围的相关性。6个重要指标聚类分析共得到3组样品, 其中第Ⅲ类咀嚼性、胶黏性、硬度、蛋白质、精氨酸都相对较高的组别具有较好的综合品质。结论 本研究基于TPA法结合营养成分对香菇品质进行综合分析, 结果表明承德地区香菇品质较好, 营养成分相对较高, 为香菇的进一步开发利用提供科学依据。

香菇  /  质构仪法  /  品质  /  营养成分

Objective To comprehensively evaluate Lentinula edodes quality using texture profile analysis (TPA) and compare characteristics across different geographical origins. Methods Using Lentinula edodes from different origins as experimental materials, the TPA model of texture analyzer was used to study the main indicators that affect the texture quality of Lentinula edodes by statistical analysis methods, at the same time, the quality of Lentinula edodes was comprehensively evaluated in combination with the nutrients of Lentinula edodes. Results Statistical analysis showed that among the 7 kinds of index parameters of Lentinula edodes detected by the texture analyzer, principal component 1 mainly included 3 indicators: Chewing ability, adhesiveness and hardness, among which the hardness had the maximum range of correlation. The 3 important indicators of principal component 1-1 in Lentinula edodes were protein, arginine and Ca, among which Ca had the maximum range of correlations. Cluster analysis of 6 important indicators yielded 3 groups of Lentinula edodes. Among them, the third group, which had relatively high values in chewiness, stickiness, hardness, protein and arginine, had a better overall quality. Conclusion This study conductes a comprehensive analysis of the quality of Lentinula edodes based on the TPA method combined with nutrients. The results show that Lentinula edodes in Chengde are good quality and relatively high nutritional content, providing a scientific basis for the further development and utilization of Lentinula edodes.

Lentinula edodes  /  texture analyzer  /  quality  /  nutrient content
张波, 高婧, 王楠楠, 刘畅. 基于质构仪技术的香菇品质综合研究与评价. 食品安全质量检测学报, 2025 , 16 (14) : 213 -221 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250402001
Bo ZHANG, Jing GAO, Nan-Nan WANG, Chang LIU. Research and comprehensive evaluation on the quality of Lentinula edodes based on the texture analyzer method[J]. Journal of Food Safety & Quality, 2025 , 16 (14) : 213 -221 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250402001
正文
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0 引言
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香菇(Lentinula edodes)是药食同源菌类, 属于担子菌纲、伞菌目、口蘑科。香菇富含蛋白质、脂肪、碳水化合物、粗纤维、微量元素及维生素等营养成分[1], 同时具有增强免疫力、减少炎症、降血压、抑制肿瘤等功效[2-5]。香菇是世界上栽培最广泛的食用菌之一, 而中国则是全球第一大香菇生产国[6], 其中河北省是主栽培香菇品种的产地之一, 全省香菇生产已经覆盖到60多个县市[7-8]。不同产地香菇品质差异的主要因素包括温度、湿度、海拔、光照、土壤与水质及重要栽培技术等[9-13]。承德市独特的气候环境, 早晚温差大, 产出的香菇密度高、弹性大、富集营养成分, 特别是平泉香菇已经成为地理标志产品[14-15]。香菇品质的基本评价指标包括菌盖厚度、菌肉质地、菌产量等, 但随着健康食品要求的日益提高, 香菇内在品质也成为影响栽培者种植和消费者选购的重要因素[16]。但目前针对承德地区香菇的研究主要集中在高产高质栽培技术, 对于香菇内在品质研究较为欠缺。同时, 现行食品标准仅有GB/T 38581—2020《香菇》、GH/T 1013—2015《香菇》、GB/Z 26587—2011《香菇生产技术规范》、NY/T 1061—2006《香菇等级规格》、NY/T 1283—2007《香菇中甲醛含量的测定》, 无法充分贴合不同地区香菇特点进行研究, 缺少地缘性、综合性的香菇内在品质评价研究, 因此结合基本物理性状来评判研究香菇品质优劣成为重要手段之一。
质构仪作为一种物理性状测试仪, 是公认的物性标准检测仪器[17-19], 目前被广泛应用于对多种不同果实样本进行质地参数检测, 包括梨[20]、桑葚[21]、甜椒果实[22]及草莓果干[23]等。全质构测试(texture profile analysis, TPA)法是一种常用的果实质地分析法, 通过模拟人口腔的咀嚼运动, 对样品分次压缩, 从而得出一系列质地参数, 较为客观地反映果实的质地特性[24]。质地是鲜菇类包括香菇的品质及储藏能力的主要指标之一[25-26], 利用质构仪结合TPA法与传统感官不仅能够对香菇的不同部位进行品质分析评价[27], 也可以对不同种类的香菇质地进行评价筛选[28]。目前, TPA法对于香菇内在品质的研究相对较少, 集中于以传统统计学方法对香菇不同部位、不同种类的质地参数进行研究, 而将香菇营养成分和质地品质结合的综合性分析并不完善, 尚未形成系统性评价香菇综合品质的方法。
本研究基于TPA法, 采用统计学分析方法研究影响不同产地香菇品质的主要指标, 并对样品进行质地和营养成分的系统分析评估, 也为承德地区香菇产业发展提供理论依据。
1 材料与方法
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1.1 材料
供试品种主要为河北承德地区的香菇, 挑选不同产地的香菇共11种, 该地区产出的香菇是知名农产品, 具有品味纯正、干物质含量高等特性。同时还搜集了产地为山东的香菇共3种、产地为河南的香菇2种。所有香菇均在采摘期, 挑选成熟度相似、大小均一且无损伤的作为试样, 取样当天用质构仪测定咀嚼性、硬度等指标参数。16种香菇的编号及详细产地见表1。
1.2 仪器
TMS-PRO型质构分析仪、TMS-PRO型质构分析仪3种探头P/2(柱形, 直径2 mm)、P/5(柱形, 直径5 mm)、P/10(柱形, 直径10 mm)、TMS-Pro/Touch型物性分析软件(美国Food Technology Corporation公司); SCIEX Triple Quad 5500+液相色谱质谱联用仪(美国AB SCIEX公司); KjeltecTM8200凯式定氮仪(瑞典FOSS公司); PE350D电感耦合等离子体质谱(inductively coupled plasma mass spectrometry, ICP-MS)(美国PerkinElmer公司)。
1.3 实验方法
采用质构仪TPA模式对16种不同品种的香菇Y1~Y16进行内在品质分析研究, 主要包含硬度1、黏附性、内聚性、弹性、胶黏度、咀嚼性、硬度2。根据香菇样本的基本形态和特性, 设定本研究的测试速度为60 mm/min, 形变量为50%, 2次压缩停顿时间为0.00 s, 触发力为0.2 N。压缩实验时选择标准圆盘探头, 用于使固体样品变形, 通过质构仪分析, 得出香菇受力随时间变化曲线, 同时计算香菇的硬度、弹性和咀嚼性, 每种样品3个平行样品。
硬度: 感官定义为用牙齿对食品上进行挤压的力量, TPA值=第一次挤压循环的最大力量峰值; 弹性: 感官定义为在食品上施加一定的力量后, 测量样品在一定时间内恢复到原来形状的程度, 以计算出样品的弹性值, TPA值=第一次挤压结束后第二次挤压开始前样品所能回复的高度; 黏附性: 感官定义为克服食品表面同其他物质表面接触之间吸引力所需要的能量, TPA值=第一次挤压的负峰面积, 即探头脱离样品表面所做的功; 内聚性: 感官定义为样品内部的吸缩力, TPA值=第二次压缩环的正峰面积/第一次挤压循环的正峰面积; 胶黏性: 感官定义为食品吞咽前破碎它需要的力量, TPA值=硬度值×内聚性; 咀嚼性: 感官定义为咀嚼固体样品时需要的能量, TPA值=胶黏性×弹性。
香菇中氨基酸的测定参考GB 5009.124—2016《食品安全国家标准 食品中氨基酸的测定》, 采用液相色谱-质谱法进行检测; 香菇中K、Mg、Ca的测定参考GB 5009.268—2025《食品安全国家标准 食品中多元素的测定》, 采用ICP-MS测定; 香菇中蛋白质的测定参考GB 5009.5—2016《食品安全国家标准 食品中蛋白质的测定》, 采用凯式定氮法进行检测。
1.4 数据处理
样品重复测定3次, 实验数据结果采用Origin 2021软件分别对质构参数和营养成分进行方差分析和多重比较, 柱状图绘制差异性分析、主成分分析、相关性分析、聚类分析统计图, 设置P<0.05为显著性差异。
2 结果与分析
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2.1 不同种类香菇质地参数的差异性分析
由图1A分析可知, 承德市平泉的香菇Y5具有最大的咀嚼性, 与其他产地的香菇之间表现差异显著(P<0.05)。山东不同产地的3种香菇之间差异不显著, 其中Y2的咀嚼性在所有样品中最小; 河南不同产地的2种香菇也呈现不显著差异, 咀嚼性大小值居中。整体来看, 承德平泉香菇咀嚼性高的样品数量较多, 山东香菇Y3的咀嚼性在山东3种香菇中最高, 但在所有样品中大小值居中。相比之下, 平泉香菇具有较好的咀嚼性, 整体表现更佳。
针对内聚性分析可知, 山东的香菇内聚性较好, 其中Y1和Y2内聚性差异不显著, 均具有最大内聚性; 河南2种香菇之间差异也不显著, 但与山东香菇Y1和Y2差异显著; 承德香菇内聚性根据不同区县产地有所不同, 其中Y10内聚性最低。在样品中, 承德香菇内聚性总体与其他产地相差数值不大; 双滦区、平泉市、兴隆县与河南地区大部分香菇之间差异不显著(图1B)。
不同产地的香菇所具有的弹性有所不同, 其中承德地区的香菇弹性部分优于其他产地的香菇, 山东香菇分别与承德平泉、双滦、兴隆的部分香菇存在相似的弹性, 河南香菇Y7与承德平泉香菇Y8弹性无显著差异, 河南香菇Y12弹性值高于Y7, 但仍低于平泉香菇Y5和Y14, 且Y5和Y14弹性显著高于其他大部分样品, 其中平泉香菇Y14具有最高的弹性值(图1C)。
承德地区香菇胶黏性表现较好, 其中承德平泉香菇Y5具有最大胶黏性, 且显著高于其他大部分样品。山东香菇Y2具有最小胶黏性; 山东香菇Y1、Y2, 河南香菇Y12与承德地区3种香菇Y9、Y10、Y16具有相似的胶黏性, 同时显著低于承德平泉4种香菇Y5、Y6、Y8、Y11 (P<0.05)(图1D)。
由图1E和1F分析可知, 承德平泉香菇Y5、Y6、Y11硬度1显著高于其他大部分产地的香菇(P<0.05), 而山东香菇Y2硬度1最低, 低于其他产地的香菇; 同时大部分承德地区香菇硬度1与其他产地香菇存在显著差异(P<0.05), 山东香菇2种样品分别与河南香菇、承德香菇大部分样品之间存在显著差异(P<0.05)。承德香菇Y5、Y6、Y11之间, Y10、Y14、Y15之间分别存在相似的硬度1值。与硬度1测定结果一致, 承德平泉香菇Y5、Y6、Y11硬度2显著高于其他大部分产地的香菇, 而山东香菇Y2硬度2最低; 同时大部分承德地区香硬度2与其他产地香菇存在显著差异(P<0.05), 产地相近的香菇硬度2则具有一定的相似性, Y4、Y10、Y16之间, Y5、Y6、Y11之间, Y9与Y12之间, Y14与Y15之间存在相似的硬度2值。硬度1和硬度2综合反映出承德平泉香菇具有较好的抗压能力和形变能力, 口感更佳。
大部分承德地区香菇的黏附性与其他产地香菇黏附性存在显著差异(P<0.05), 同时相同地区样品大部分具有相似性, 承德平泉香菇的黏附性相比其他产地香菇表现更好, 其中承德平泉香菇Y13具有最大黏附性; 山东香菇Y2具有最小黏附性(图1G)。
2.2 不同种类香菇质地参数的主成分分析
特征值大于1的原则, 提取出3个主成分, 从表2和图2可以看出, 7个指标与主成分1 (principal component 1, PC1)均呈现正相关, 按照贡献率指标主要为咀嚼性、胶黏性、硬度, 可作为适口性因子; 主成分2 (principal component 2, PC2)的主要贡献率指标为弹性和内聚性, 可作为内聚因子; 主成分3 (principal component 3, PC3)的主要贡献指标为黏附性, 可作为黏附因子。累计方差贡献率总计为94.13%, PC1占52.20%, PC2占26.12%, PC3占15.81%。因此, 这些香菇的质地参数可通过适口性因子、内聚因子、黏附因子3种依据来评价, 其中适口性因子对于质地参数好坏的评判影响最大。
2.3 不同种类香菇质地指标的相关性分析
由图3可知, 在P为0.05水平下, 咀嚼性与其他指标之间具有正相关性, 与胶黏性之间存在最高正相关性, 硬度具有最大范围相关性, 除与内聚性具有负相关性, 与其他指标均呈现正相关性, 因此可以通过硬度指标来反映香菇的质地品质。由此可见, 咀嚼性、胶黏性和硬度能够更全面地概括出这些香菇的质地参数, 更明确地对这些香菇进行质地品质评判; 因此, 可主要考察香菇这3种参数的TPA值, 对香菇品质进行综合分析。
2.4 不同种类香菇营养成分的差异性分析概述
对香菇样品的营养成分所得数据进行初步比较和差异分析, 主要包括香菇的蛋白质、总糖、脂肪、K、Mg、Ca、氨基酸、谷氨酸。
由图4A知, Y15具有最高的蛋白质含量, 且与其他样品均差异显著(P<0.05); Y1、Y2、Y3与Y7, Y5与Y14, Y6、Y9与Y13分别差异不显著; 不同产地的干香菇中蛋白质含量在19.98%~28.04%之间, 承德地区的蛋白质含量普遍高于其他省份(P<0.05)。
由图4B可得, Y5具有最高的总糖含量, 且与其他样品均差异显著(P<0.05); Y7与Y15, Y3与Y14, Y1与Y4, Y2与Y8分别具有不显著差异; 不同产地的香菇中的总糖含量在33.1%~42.7%之间, 不同产地间的含量相差不大。
相同产地香菇之间的脂肪含量差异不显著, Y1、Y2、Y3、Y6、Y9、Y10与Y14, Y5与Y16, Y7、Y11与Y12, Y8与Y13之间差异不显著; Y1、Y2、Y3、Y6、Y9、Y10、Y14与Y5、Y8、Y13、Y15的脂肪含量差异显著(P<0.05); Y4与Y5、Y7、Y8、Y11、Y12、Y13、Y15、Y16差异显著(P<0.05); 不同产地的干香菇中脂肪含量在1.3%~2.5%之间(图4C)。
承德地区香菇Y13具有最高的K含量, 且与Y8差异不显著(P˃0.05); Y1、Y2、Y10与Y15, Y9、Y14与Y16, Y7与Y12之间差异不显著(P˃0.05)(见图4D)。Y1、Y3、Y13、Y14、Y15与Y16, Y2、Y8与Y11, Y4、Y6、Y9与Y10, Y7与Y12具有相似的Mg含量, 其中, Y7与Y12含量最低; Y5具有最高的Mg含量, 且与其他样品呈显著差异(P<0.05)(图4E)。Y15具有最高的Ca含量, Y16次之, 且分别与其他样品呈显著差异; Y3与Y11, Y4、Y8与Y10, Y7与Y12之间差异不显著(P˃0.05)(图4F); Y6的Ca含量最低。不同产地的香菇中K˃Mg˃Ca的含量, 承德地区香菇中K的含量普遍高于其他省份。
部分相同产地香菇之间氨基酸含量差异不显著; Y15与Y16, Y2、Y3与Y5, Y4与Y8, Y7与Y12, Y9与Y10呈现不显著差异(P˃0.05), 且每组相互之间存在显著差异, 其中承德地区香菇Y15与Y16的精氨酸含量最高(见图4G)。承德地区香菇Y6具有最大的谷氨酸含量, Y11次之, 且分别与其他样品呈显著差异(P<0.05); Y3、Y5、Y9、Y15与Y16, Y4与Y14, Y7与Y12, Y8与Y10呈现不显著差异(P˃0.05)(图4H)。不同产地干香菇中的必需氨基酸和非必需氨基酸中谷氨酸和精氨酸的含量普遍较高。
2.5 不同种类香菇营养成分的主成分分析及相关性分析概述
提取出3个主成分, 特征值均大于1.2, 从表3和图5可以看出, 8个指标与PC1均呈现正相关, 主要贡献指标分别为蛋白质、精氨酸、Ca; PC2主要贡献指标为总糖、精氨酸; PC3主要贡献指标为总糖、脂肪。前3个累计方差贡献率总计为71.70%, PC1占34.27%, PC2占20.24%, PC3占17.19%。由此可见, 香菇营养成分可通过这3种主成分进行评估, 其中主成分1占比最大。
由图6可知, 在0.05显著水平下, 蛋白质与其他指标之间具有正相关性, 且与精氨酸之间具有最高正相关性; Ca离子具有最大范围的相关性, 与谷氨酸和总糖具有负相关, 与其他指标呈正相关性。其中, 承德平泉香菇Y5同时具有最大总糖、Mg含量, 第Ⅲ类承德兴隆香菇同时具有最大蛋白质、K、Ca、精氨酸含量。总体比较可得承德地区香菇营养成分中蛋白质含量普遍高于其他地区, 是相对较佳的食用类型。
2.6 香菇品质聚类分析综合评价
分别选取质地主成分分析PC1的主要贡献指标咀嚼性、胶黏性、硬度, 营养成分主成分PC1-1的主要贡献指标蛋白质、精氨酸、Ca, 共6种进行聚类分析。如图7所示, 16种样品共得到3种大类别, 第Ⅰ类包括Y1、Y2、Y3、Y9、Y10、Y11、Y15、Y16, 第Ⅱ类包括Y4、Y7、Y8、Y12、Y13、Y14, 第Ⅲ类包括Y5、Y6。其中, 第Ⅰ、Ⅱ、Ⅲ类最具代表性的样品分别为Y10、Y14、Y5。
由表4可见, 在这3类中咀嚼性、胶黏性、硬度、蛋白质、Ca、精氨酸均呈现不同的差异。第Ⅰ类的特点是咀嚼性、胶黏性、硬度都相对较低, Ca含量相对较高, 精氨酸居于其他两类之间, 蛋白质组内含量跨度大, 平均含量也居于其他两类之间, 为综合评估较低组。第Ⅱ类的咀嚼性、胶黏性、硬度、Ca都居于其他两类之间, 蛋白质和精氨酸含量相对较低, 为综合评估居中组。第Ⅲ类的咀嚼性、胶黏性、硬度、蛋白质、精氨酸都相对较高, Ca含量相对较低, 为综合评估较高组。
3 讨论
收起
本研究基于质地品质和营养成分通过TPA法得到6种不同产地的香菇质地指标参数, 多重比较和差异分析获得了其质地特性, 相关性分析和主成分分析进一步计算出香菇种类之间的评价指标, 然后通过对香菇的营养成分进行比较和差异分析得到其营养成分特性, 主成分分析后得出营养成分的主要评价指标, 最后结合质地参数和营养成分分析对香菇品质进行综合评价。结果表明这16类香菇中, 承德地区香菇普遍硬度偏高, 有较好的弹性和咀嚼性, 其中, 产地为承德平泉的香菇具有更高的硬度和咀嚼性。与此同时, 平泉香菇也具有较高的蛋白质和总糖含量。这可能是由于硬度与纤维含量存在联系, 在一定范围内, 纤维和蛋白含量与硬度和咀嚼性呈现正相关[29]。相关性分析表明, 香菇质地与硬度具有最大范围相关性, 除与内聚性具有负相关性, 与其他指标均呈现正相关性。这与食品相关的研究结果一致[22,30-31], 香菇越硬实, 香菇弹性越大, 越耐咀嚼, 因此能够用硬度指标来反映这16种香菇的质地特性。香菇质地和营养成分主成分分析结果分别筛选出3个香菇质地影响因子, 质地品质中占比最高的影响因子PC1的重要指标包括了咀嚼性、胶黏性和硬度, 营养成分中包括蛋白质、Ca、精氨酸。6个指标的聚类分析结果显示第Ⅲ类样品具有最好的综合品质, 均为承德香菇品种Y5和Y6。综上所述, 香菇中营养成分蛋白质、多糖、Ca和精氨酸含量能够影响香菇的咀嚼性、胶黏性和硬度等质地参数, 并呈正相关。在16种香菇中, 承德地区的香菇品质各有不同, 相较于其他地区的样本较优, 平泉香菇整体表现相对较优于其他品种, 平泉香菇中Y5的品质相对较好, 其硬度和咀嚼性相对较高, 且蛋白质等多种营养成分含量也较高, 是作为功能性食品原料开发利用和定向育种亲本材料的优秀种类。
4 结论
收起
本研究通过对市场流通中香菇品质口碑较好并且呈规模种植的6个产地16类香菇的质地特性和营养成分进行综合分析, 发现承德平泉地区的香菇品质较优, 其中平泉香菇Y5表现最佳, 具有较高的硬度、咀嚼性和总糖含量。主成分分析表明, 质地品质主要由咀嚼性、胶黏性和硬度决定, 而营养成分以蛋白质、Ca和精氨酸为关键指标。相关性分析显示硬度与弹性、咀嚼性呈正相关, 与内聚性呈负相关。综合来看, 承德平泉昼夜温差大的季风性气候对香菇中蛋白质等营养成分的累积有重要作用, 而蛋白质、钙和精氨酸的含量能够影响口感, 所以承德平泉香菇Y5具有优异的质地和营养特性, 适合作为功能性食品原料或育种亲本材料。
基金
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  • 承德市基础研究项目(202305B075)
文献
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2025年第16卷第14期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20250402001
  • 接收时间：2025-04-02
  • 首发时间：2026-01-07
  • 出版时间：2025-07-25
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  • 收稿日期：2025-04-02
基金
承德市基础研究项目(202305B075)
作者信息
    承德市食品药品检验检测中心, 承德 067000

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*刘畅(1997—), 女, 硕士, 初级工程师, 主要研究方向为食品检验检测。E-mail:
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
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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