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Article(id=1153433637279227965, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153433633999282214, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20241028004, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1730044800000, receivedDateStr=2024-10-28, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1752929608888, onlineDateStr=2025-07-19, pubDate=1742832000000, pubDateStr=2025-03-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752929608888, onlineIssueDateStr=2025-07-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752929608888, creator=13701087609, updateTime=1752929608888, updator=13701087609, issue=Issue{id=1153433633999282214, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='6', pageStart='1', pageEnd='322', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752929608105, creator=13701087609, updateTime=1758086445549, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1175062977960096080, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153433633999282214, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1175062977960096081, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153433633999282214, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=177, endPage=182, ext={EN=ArticleExt(id=1153433637765767232, articleId=1153433637279227965, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Main quality analysis and comprehensive evaluation of rice resources in Liaoning, columnId=1153433635433730748, journalTitle=Journal of Food Safety & Quality, columnName=Special Topic: Comprehensive Utilization and Quality Safety of Agricultural Products, runingTitle=null, highlight=null, articleAbstract=

Objective To systematically evaluate the differences in overall quality of rice from different regions in Liaoning Province. Methods Using 125 different rice varieties as research objects, the quality of rice from different regions in Liaoning Province was analyzed and comprehensively evaluated through physical and chemical testing methods, using correlation analysis (CA), principal component analysis (PCA), and hierarchical cluster analysis (HCA). Results The order of influence of different varieties and origins of rice on quality indicators was: Retention rate of germ grains>chalky grains rate>chalkiness>milled rice rate>brown rice rate>moisture> ash>protein>brown rice quality>fat>length-width ratio>fiber. Using stepwise regression analysis, the regression equation was obtained as follows: Brown rice rate=4.672×brown rice quality-0.104×chalky grains rate+0.141×chalkiness-0.860×length-width ratio-13.205. PCA extracted 4 principal components with a cumulative variance contribution rate of 80.046%, effectively elucidating all quality information characteristics. The results from HCA were consistent with those obtained from PCA, categorizing the 125 rice varieties into 3 major groups; through comprehensive assessment, the top 3 ranked varieties were identified as Yudao No.17 from Xiqing Village, Shiyuan Town, Dashiqiao City in Yingkou; Ichigo-hime from Zhangjia Village at Xinli Farm in Dawa County, Panjin; and Yanfeng No.47 from Gongxing Village in Tianshui Township, Panshan County, Panjin. Conclusion This study effectively highlights the differences in quality among various regional rices within Liaoning and provides a theoretical basis for breeding programs and product development related to rice germplasm.

, correspAuthors=Yi-Cen CHEN, 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=Yi-Cen CHEN, Xu ZHAO, Lin LIN, Feng LU, Si-Min XING, Li-Na QIAO, Hong-Mei JING), CN=ArticleExt(id=1153433653028839969, articleId=1153433637279227965, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=辽宁稻米资源主要品质分析及综合评价, columnId=1153433635601502912, journalTitle=食品安全质量检测学报, columnName=本期专题：农产品综合利用及质量安全, runingTitle=null, highlight=null, articleAbstract=

目的 系统评估不同产地辽宁稻米总体品质的差异性。方法 以125个不同稻谷品种为研究对象, 通过理化测试方法, 运用相关性分析法(correlation analysis, CA)、主成分分析法(principal component analysis, PCA)、聚类分析法(hierarchical cluster analysis, HCA)对不同产地辽宁稻谷品质进行质量分析和综合评价。结果 不同品种不同产地稻谷对品质指标的影响顺序为: 留胚粒率>垩白粒率>垩白度>精米率>出糙率>水分>灰分>蛋白>糙米质量>脂肪>长宽比>纤维; 利用逐步回归分析法得到回归方程: 出糙率=4.672×糙米质量-0.104×垩白粒率+0.141×垩白度-0.860×长宽比-13.205, 运用PCA共提取4个主成分, 累计方差贡献率为80.046%, 能有效解析所有品质信息特征。HCA结果与PCA结果一致, 125个稻谷品种被划分成3大类; 通过综合评估得出排名前3的品种分别为营口市大石桥市水源镇西青村的域稻17、盘锦市大洼县新立农场张家村的一目惚、盘锦市盘山县甜水乡公兴村的盐丰(47)。结论 本研究可以有效体现出不同产地辽宁稻谷品质质量间的差异性, 为稻谷种质选育、产品研发提供一定的理论依据。

, correspAuthors=陈怡岑, authorNote=null, correspAuthorsNote=
* 陈怡岑(1987—), 女, 硕士, 高级工程师, 主要研究方向为粮食储藏与加工。E-mail:
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Chinese Journal of Rice Science, 2004, 18(2): 44-48., articleTitle=Correlation and cluster analysis of hybrid rice grain quality traits, refAbstract=null), Reference(id=1175086850030060196, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, doi=null, pmid=null, pmcid=null, year=2016, volume=44, issue=5, pageStart=1, pageEnd=6, url=null, language=null, rfNumber=[30], rfOrder=55, authorNames=张梅霞, 陈荣江, journalName=河南科技学院学报(自然科学版), refType=null, unstructuredReference=张梅霞, 陈荣江. 基于主成分分析的粳稻品质评价及聚类分析[J]. 河南科技学院学报(自然科学版), 2016, 44(5): 1-6., articleTitle=基于主成分分析的粳稻品质评价及聚类分析, refAbstract=null), Reference(id=1175086850122334887, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, doi=null, pmid=null, pmcid=null, year=2016, volume=44, issue=5, pageStart=1, pageEnd=6, url=null, language=null, rfNumber=[30], rfOrder=56, authorNames=ZHANG MX, CHEN RJ, journalName=Journal of Henan University of Science and Technology (Natural Science Edition), refType=null, unstructuredReference=ZHANG MX, CHEN RJ. Quality evaluation and cluster analysis based on principal component analysis for japonica rice[J]. Journal of Henan University of Science and Technology (Natural Science Edition), 2016, 44(5): 1-6., articleTitle=Quality evaluation and cluster analysis based on principal component analysis for japonica rice, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1175086841255575980, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, xref=null, ext=[AuthorCompanyExt(id=1175086841263964589, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, companyId=1175086841255575980, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. 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Tieling Project Service Centre, Tieling 112000, China), AuthorCompanyExt(id=1175086841477874104, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, companyId=1175086841465291190, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.铁岭市项目服务中心, 铁岭 112000)])], figs=[ArticleFig(id=1175086844099314187, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, language=EN, label=Fig.1, caption=Correlation analysis of various indicators, figureFileSmall=Qv+7Ws9MY1nFbq0YKrHuHg==, figureFileBig=uOgw1Mb3lvVE1BwBLXWcuQ==, tableContent=null), ArticleFig(id=1175086844187394573, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, language=CN, label=图1, caption=各指标相关性分析

注: *P<0.05; **P<0.01; ***P<0.001。

, figureFileSmall=Qv+7Ws9MY1nFbq0YKrHuHg==, figureFileBig=uOgw1Mb3lvVE1BwBLXWcuQ==, tableContent=null), ArticleFig(id=1175086844254503439, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, language=EN, label=Fig.2, caption=BIPOLT diagram, figureFileSmall=Nw1M0DW4ZauN/fsWLWc4WA==, figureFileBig=AcdtsIKheP1TKaOYK5Byng==, tableContent=null), ArticleFig(id=1175086844342583825, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, language=CN, label=图2, caption=BIPOLT图, figureFileSmall=Nw1M0DW4ZauN/fsWLWc4WA==, figureFileBig=AcdtsIKheP1TKaOYK5Byng==, tableContent=null), ArticleFig(id=1175086844434858515, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, language=EN, label=Table 1, caption=

Basic quality indicators of rice

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品质指标 平均值
/%		 标准差
/%		 变异
系数/%		 范围/%
糙米质量 20.55 0.02 0.41 18.84~21.21
出糙率 80.70 0.03 2.11 72.77~84.05
精米率 76.74 0.04 2.91 63.84~80.64
留胚粒率 85.25 0.20 16.67 24.78~99.70
垩白粒率 9.34 0.77 7.18 0.05~41.00
垩白度 3.18 1.11 3.53 0.00~33.05
长宽比 1.84 0.12 0.23 1.40~2.80
水分 12.83 0.07 0.88 11.40~15.00
灰分 1.60 0.40 0.64 0.40~3.60
纤维 1.44 0.15 0.22 0.08~1.80
脂肪 2.58 0.12 0.31 1.90~3.50
蛋白 8.02 0.05 0.44 6.90~9.30
), ArticleFig(id=1175086844531327509, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, language=CN, label=表1, caption=

稻谷基本品质指标

, figureFileSmall=null, figureFileBig=null, tableContent=
品质指标 平均值
/%		 标准差
/%		 变异
系数/%		 范围/%
糙米质量 20.55 0.02 0.41 18.84~21.21
出糙率 80.70 0.03 2.11 72.77~84.05
精米率 76.74 0.04 2.91 63.84~80.64
留胚粒率 85.25 0.20 16.67 24.78~99.70
垩白粒率 9.34 0.77 7.18 0.05~41.00
垩白度 3.18 1.11 3.53 0.00~33.05
长宽比 1.84 0.12 0.23 1.40~2.80
水分 12.83 0.07 0.88 11.40~15.00
灰分 1.60 0.40 0.64 0.40~3.60
纤维 1.44 0.15 0.22 0.08~1.80
脂肪 2.58 0.12 0.31 1.90~3.50
蛋白 8.02 0.05 0.44 6.90~9.30
), ArticleFig(id=1175086844661350934, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, language=EN, label=Table 2, caption=

Total variance of the interpretation

, figureFileSmall=null, figureFileBig=null, tableContent=
成份 初始特征值 提取平方和载入
合计 方差/% 累积/% 合计 方差/% 累积/%
1 3.994 33.284 33.284 3.994 33.284 33.284
2 2.372 19.769 53.052 2.372 19.769 53.052
3 1.990 16.584 69.636 1.990 16.584 69.636
4 1.249 10.410 80.046 1.249 10.410 80.046
), ArticleFig(id=1175086844732654104, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, language=CN, label=表2, caption=

解释的总方差

, figureFileSmall=null, figureFileBig=null, tableContent=
成份 初始特征值 提取平方和载入
合计 方差/% 累积/% 合计 方差/% 累积/%
1 3.994 33.284 33.284 3.994 33.284 33.284
2 2.372 19.769 53.052 2.372 19.769 53.052
3 1.990 16.584 69.636 1.990 16.584 69.636
4 1.249 10.410 80.046 1.249 10.410 80.046
), ArticleFig(id=1175086844812345881, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, language=EN, label=Table 3, caption=

Comprehensive scores of the top 3 rice varieties

, figureFileSmall=null, figureFileBig=null, tableContent=
新序号 稻种 扦样地点 综合
得分
1 域稻17 营口市大石桥市水源镇西青村 1.74
2 一目惚 盘锦市大洼县新立农场张家村 1.43
3 盐丰(47) 盘锦市盘山县甜水乡公兴村 1.36
), ArticleFig(id=1175086844883649050, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, language=CN, label=表3, caption=

排名前3的稻种综合得分

, figureFileSmall=null, figureFileBig=null, tableContent=
新序号 稻种 扦样地点 综合
得分
1 域稻17 营口市大石桥市水源镇西青村 1.74
2 一目惚 盘锦市大洼县新立农场张家村 1.43
3 盐丰(47) 盘锦市盘山县甜水乡公兴村 1.36
), ArticleFig(id=1175086844996895259, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, language=EN, label=Table 4, caption=

Final clustering centers

, figureFileSmall=null, figureFileBig=null, tableContent=
类别 聚类
1 2 3
标准化糙米质量/g -0.54367 0.45153 -0.62066
标准化出糙率/% -1.01271 0.40543 -0.50266
标准化精米率/% -1.19729 0.28795 -0.30720
标准化留胚粒率/% -0.17175 0.09009 -0.11724
标准化垩白粒率/% 3.52651 -0.11651 -0.19257
标准化垩白度/% 3.50627 -0.14429 -0.14881
标准化长宽比/% -0.69150 -0.11150 0.23928
标准化水分/% -0.47154 0.68217 -0.97413
标准化灰分/% -0.47251 0.65436 -0.93232
标准化纤维/% 0.47169 -0.63572 0.90445
标准化脂肪/% -0.43997 0.41014 -0.56938
标准化蛋白/% -0.77350 0.37654 -0.48424
), ArticleFig(id=1175086845076587036, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433637279227965, language=CN, label=表4, caption=

最终聚类中心

, figureFileSmall=null, figureFileBig=null, tableContent=
类别 聚类
1 2 3
标准化糙米质量/g -0.54367 0.45153 -0.62066
标准化出糙率/% -1.01271 0.40543 -0.50266
标准化精米率/% -1.19729 0.28795 -0.30720
标准化留胚粒率/% -0.17175 0.09009 -0.11724
标准化垩白粒率/% 3.52651 -0.11651 -0.19257
标准化垩白度/% 3.50627 -0.14429 -0.14881
标准化长宽比/% -0.69150 -0.11150 0.23928
标准化水分/% -0.47154 0.68217 -0.97413
标准化灰分/% -0.47251 0.65436 -0.93232
标准化纤维/% 0.47169 -0.63572 0.90445
标准化脂肪/% -0.43997 0.41014 -0.56938
标准化蛋白/% -0.77350 0.37654 -0.48424
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辽宁稻米资源主要品质分析及综合评价
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陈怡岑 1, * , 赵旭 1 , 林琳 1 , 路峰 2 , 邢思敏 1 , 乔丽娜 2 , 井红梅 3
食品安全质量检测学报 | 本期专题：农产品综合利用及质量安全 2025,16(6): 177-182
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食品安全质量检测学报 | 本期专题：农产品综合利用及质量安全 2025, 16(6): 177-182
辽宁稻米资源主要品质分析及综合评价
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陈怡岑1, * , 赵旭1, 林琳1, 路峰2, 邢思敏1, 乔丽娜2, 井红梅3
作者信息
  • 1.辽宁省粮食科学研究所, 沈阳 110000
  • 2.辽宁省粮食和物资储备事务服务中心, 沈阳 110000
  • 3.铁岭市项目服务中心, 铁岭 112000

通讯作者:

* 陈怡岑(1987—), 女, 硕士, 高级工程师, 主要研究方向为粮食储藏与加工。E-mail:
Main quality analysis and comprehensive evaluation of rice resources in Liaoning
Yi-Cen CHEN1, * , Xu ZHAO1, Lin LIN1, Feng LU2, Si-Min XING1, Li-Na QIAO2, Hong-Mei JING3
Affiliations
  • 1. Liaoning Grain Science Research Institute, Shenyang 110000, China
  • 2. Liaoning Province Food and Materials Reserve Affairs Service Center, Shenyang 110000, China
  • 3. Tieling Project Service Centre, Tieling 112000, China
出版时间: 2025-03-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20241028004
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摘要
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目的 系统评估不同产地辽宁稻米总体品质的差异性。方法 以125个不同稻谷品种为研究对象, 通过理化测试方法, 运用相关性分析法(correlation analysis, CA)、主成分分析法(principal component analysis, PCA)、聚类分析法(hierarchical cluster analysis, HCA)对不同产地辽宁稻谷品质进行质量分析和综合评价。结果 不同品种不同产地稻谷对品质指标的影响顺序为: 留胚粒率>垩白粒率>垩白度>精米率>出糙率>水分>灰分>蛋白>糙米质量>脂肪>长宽比>纤维; 利用逐步回归分析法得到回归方程: 出糙率=4.672×糙米质量-0.104×垩白粒率+0.141×垩白度-0.860×长宽比-13.205, 运用PCA共提取4个主成分, 累计方差贡献率为80.046%, 能有效解析所有品质信息特征。HCA结果与PCA结果一致, 125个稻谷品种被划分成3大类; 通过综合评估得出排名前3的品种分别为营口市大石桥市水源镇西青村的域稻17、盘锦市大洼县新立农场张家村的一目惚、盘锦市盘山县甜水乡公兴村的盐丰(47)。结论 本研究可以有效体现出不同产地辽宁稻谷品质质量间的差异性, 为稻谷种质选育、产品研发提供一定的理论依据。

辽宁省  /  稻米  /  品质调查  /  质量分析  /  评价

Objective To systematically evaluate the differences in overall quality of rice from different regions in Liaoning Province. Methods Using 125 different rice varieties as research objects, the quality of rice from different regions in Liaoning Province was analyzed and comprehensively evaluated through physical and chemical testing methods, using correlation analysis (CA), principal component analysis (PCA), and hierarchical cluster analysis (HCA). Results The order of influence of different varieties and origins of rice on quality indicators was: Retention rate of germ grains>chalky grains rate>chalkiness>milled rice rate>brown rice rate>moisture> ash>protein>brown rice quality>fat>length-width ratio>fiber. Using stepwise regression analysis, the regression equation was obtained as follows: Brown rice rate=4.672×brown rice quality-0.104×chalky grains rate+0.141×chalkiness-0.860×length-width ratio-13.205. PCA extracted 4 principal components with a cumulative variance contribution rate of 80.046%, effectively elucidating all quality information characteristics. The results from HCA were consistent with those obtained from PCA, categorizing the 125 rice varieties into 3 major groups; through comprehensive assessment, the top 3 ranked varieties were identified as Yudao No.17 from Xiqing Village, Shiyuan Town, Dashiqiao City in Yingkou; Ichigo-hime from Zhangjia Village at Xinli Farm in Dawa County, Panjin; and Yanfeng No.47 from Gongxing Village in Tianshui Township, Panshan County, Panjin. Conclusion This study effectively highlights the differences in quality among various regional rices within Liaoning and provides a theoretical basis for breeding programs and product development related to rice germplasm.

Liaoning Province  /  rice  /  quality investigation  /  quality analysis  /  evaluation
陈怡岑, 赵旭, 林琳, 路峰, 邢思敏, 乔丽娜, 井红梅. 辽宁稻米资源主要品质分析及综合评价. 食品安全质量检测学报, 2025 , 16 (6) : 177 -182 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20241028004
Yi-Cen CHEN, Xu ZHAO, Lin LIN, Feng LU, Si-Min XING, Li-Na QIAO, Hong-Mei JING. Main quality analysis and comprehensive evaluation of rice resources in Liaoning[J]. Journal of Food Safety & Quality, 2025 , 16 (6) : 177 -182 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20241028004
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0 引言
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随着人口的增加和社会经济的发展, 国家对粮食的质与量的要求正在逐步提高[1]。口粮安全日益受到人们的重视, 由于各种原因, 不同品种、不同地区种植的稻米品质情况不尽相同。稻米品质的形成具有综合性和复杂性[2-4], 广义的稻米品质包括加工品质、外观品质、蒸煮品质、营养品质以及感官品质等多个方面[5]。目前生产上对稻米品质评价一般采用的指标, 如加工精度、碎米量、不完善粒含量、出米率和垩白度等, 这些指标虽说可以对稻米进行初步定等, 但仍存在表达结果不准确、不能全面反映稻米品质的弊端。张丽娜等[6]对辽宁省不同地域稻米品质比较分析, 发现在外观品质上, 辽宁沿海平原稻区垩白粒率和垩白度明显高于其他稻区; 在营养品质上, 沿海平原稻区水稻蛋白质含量明显高于其他稻区, 而直链淀粉含量明显低于其他稻区, 中部平原亚区米饭外观和口感明显低于东北部山地丘陵亚区; 于秋竹等[7]对黑龙江省不同积温条件下水稻品种产量及品质现状进行综合评价, 发现高产优质的水稻品质性状, 具体表现为脂肪酸含量、垩白大小和粒长的差异; 冯莹莹等[8]对46个东北南部地区优质粳稻的13个稻米品质指标进行检测分析和综合性评价, 给出供试粳稻品种对直链淀粉含量影响最小、垩白粒率影响最大的结论; 张子军等[9]认为决定寒地早粳稻米品质的主要因素包括粒型以及稻种的加工品质和外观品质, 如垩白等; LI等[10]研究也表明在水稻优质育种方面应注重垩白和粒型等选择, 才能有效提高水稻品质育种的效率。可见, 稻米外观品质、加工品质是目前育种者和种植者更为关注的研究热点。
本研究通过探究辽宁地区不同品种稻谷质量(糙米质量、出糙率、精米率等指标)情况, 对稻谷品质指标构建品质模型, 并通过相关性分析、主成分分析、聚类分析等分析手段, 预测辽宁地区稻米品质, 确定优良稻谷品种, 指导农户科学种植, 为粮食企业针对性收购、合理加工成品粮提供帮助。
1 材料与方法
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1.1 材料
随机采集2022年10月收获的辽宁省稻谷主产区125个品种(样品), 地产当季纯种粳稻谷, 生育期为145~165 d, 每块稻田采集样品数量1000 g, 样品在自然条件下干燥并储藏14 d, 理化性状稳定后进行品质指标测定。
1.2 仪器与设备
JSWL大米食味计、JMCT12大米外观品质测定检测仪(北京东孚久恒仪器技术有限公司); JGMJ8090稻谷精米检测机(上海嘉定粮油仪器有限公司); FOSS 1241近红外光谱谷物分析仪(丹麦福斯分析仪器公司)。
1.3 方法
出糙率测定参照GB/T 5495—2008《粮油检验稻谷出糙率检验》; 整精米率测定参照GB/T 21719《稻谷整精米率经验法》; 垩白度、垩白粒率测定参照GB/T 17891—2017《优质稻谷》附录A《稻米整精米率、粒型、垩白粒率、垩白度及透明度的测定 图形法》。
1.4 数据处理
利用Microsoft Excel 2007软件对试验数据进行初步整理, 利用SPSS 27.0软件对各指标进行相关性分析和多元线性回归分析, 最后建立回归方程, P<0.01表示极显著相关, P<0.05表示显著相关, P>0.05表示相关性不显著, 利用Origin 2021进行热图及主成分分析图绘制。
2 结果与分析
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2.1 不同品种不同产地稻谷品质指标之间的比较
出糙率和整精米率可以表征稻谷的加工品质[11-12], 在现行的国家标准中出糙率是稻谷的定等指标[13-14], 与加工厂的经济效益密切相关[15]; 水分是稻谷的重要组成部分[16-17], 是影响稻谷品质的重要指标; 粒型和垩白可以科学反映稻谷的外观品质[16], 指导企业加工生产; 此外, 稻谷还具备一定的营养特性[18-20], 比如蛋白、纤维、脂肪等。对稻谷基本品质指标进行测定, 从表1可知, 样本中纤维含量的变异系数0.22%, 变异系数最小, 范围0.08%~1.80%, 平均值含量1.44%; 其次是长宽比的变异系数0.23%, 范围1.40%~2.80%, 平均值含量1.84%; 留胚粒率的变异系数最大为16.67%, 范围24.78%~99.70%, 平均值含量85.25%, 说明不同品种不同产地稻谷对纤维影响最小, 留胚粒率影响最大; 由变异系数大小可知不同品种不同产地稻谷对品质指标的影响顺序为: 留胚粒率>垩白粒率>垩白度>精米率>出糙率>水分>灰分>蛋白>糙米质量>脂肪>长宽比>纤维。
2.2 辽宁地产稻谷品质特征的回归及相关性分析
以出糙率为因变量, 糙米质量、精米率、留胚粒率、长宽比、垩白度、垩白粒率、水分、纤维、脂肪、灰分、蛋白为自变量, 利用逐步回归分析法, 得到回归方程: 出糙率=4.672×糙米质量-0.104×垩白粒率+0.141×垩白度-0.860×长宽比-13.205, 调整后R2=0.851, 模型整体P为0.000, 模型中的常数项和自变量系数的显著性都小于0.05, 说明该回归方程显著。经过多重线性回归分析, 可以发现样本的出糙率受到糙米质量、垩白粒率、垩白度、长宽比的影响, 可以用糙米质量、垩白粒率、垩白度、长宽比4个指标表达出糙率。在相关性热力图中, 颜色的深浅代表两个变量之间的相关系数大小[21], 见图1, 数值范围一般介于-1到+1之间, 其中+1表示完全正相关, -1表示完全负相关, 而接近0的值则表明变量间几乎没有线性关系。从图1可以看出, 灰分和脂肪相关系数为0.78, 两者呈极显著正相关; 出糙率和糙米质量相关系数为0.90, 两者呈极显著正相关; 纤维与蛋白的相关系数为-0.71, 两者呈极显著负相关; 垩白粒率和垩白度相关系数为0.87, 两者呈极显著正相关; 长宽比与出糙率的相关系数为-0.30, 两者呈极显著负相关; 精米率与出糙率相关系数为0.63, 两者呈极显著正相关, 精米率分别与垩白粒率、垩白度和长宽比呈负相关, 并且精米率与长宽比存在极显著性, 这与王莹等[22]关于精米率与长宽比的研究成果有一些出入, 还有待进一步验证并探讨其原因。
2.3 不同品种不同产地稻谷品质特征的主成分分析
对12个品质与营养指标进行主成分分析, 以特征值>1.0为标准, 得到BIPOLT图, 如图2所示, 在PC1主成分中出糙率指标的贡献率大于垩白度、垩白粒率指标的贡献率; PC2主成分中纤维指标的贡献率大于长宽比指标的贡献率; 从表2可知, 共得到4个特征值大于1的主成分因子, 其中第一主成分特征值为3.994, 方差贡献率达到33.284%; 第二主成分的特征值为2.372, 贡献率为19.769%; 第三主成分特征值为1.990, 贡献率为16.584%; 第四主成分特征值为1.249, 贡献率为10.410%。4个主成分累积方差贡献率达到80.046%, 说明这4个主成分能够代表大部分品质的信息。如图2所示, PC1、PC2主成分的贡献率分别为33.3%、19.8%, 且所有样本均在置信区间内, 具有统计学意义。
Y1=0.31Z糙米质量+0.29Z出糙率+0.19Z精米率+0.03Z留胚粒率-0.06Z垩白粒率-0.08Z垩白度-0.11Z长宽比+0.46Z水分+0.46Z灰分-0.43Z纤维+0.32Z脂肪+0.24Z蛋白
Y2=0.39Z糙米质量+0.45Z出糙率+0.48Z精米率+0.27Z留胚粒率-0.10Z垩白粒率-0.11Z垩白度-0.29Z长宽比-0.14Z水分-0.22Z灰分+0.24Z纤维-0.22Z脂肪-0.25Z蛋白
Y3=-0.12Z糙米质量+0.06Z出糙率-0.03Z精米率-0.06Z留胚粒率+0.67Z垩白粒率+0.65Z垩白度-0.31Z长宽比+0.04Z水分+0.02Z灰分-0.04Z纤维-0.06Z脂肪-0.05Z蛋白
Y4=-0.25Z糙米质量-0.25Z出糙率-0.06Z精米率+0.57Z留胚粒率-0.02Z垩白粒率-0.003Z垩白度-0.31Z长宽比+0.17Z水分+0.14Z灰分+0.14Z纤维+0.43Z脂肪-0.55Z蛋白
以4个主成分所对应的方差贡献率为权重(公式中的Zx1-12是x1-12标准化后的数值), 计算各品种稻米品质的综合得分(Y):
Y=0.33284Y1+0.19769Y2+0.16584Y3+0.10410Y4
排名前3的稻种综合得分, 见表3。
2.4 不同品种不同产地稻谷品质特征的聚类分析
聚类分析的目标是在形似的基础上收集数据来分类, 将实验样本分为3个聚类, 聚类1包括5个样本, 占样本总数的4%; 聚类2包括72个样本, 占样本总数的57.6%, 聚类3包括48个样本, 占样本总数的38.4%。通过表4可知, 聚类1样本组合除垩白粒率、垩白度、纤维数值为正值, 其他指标均为负值, 说明聚类1样本的垩白程度大, 属于短粒型米, 纤维含量高; 聚类2样本属于短粒型米, 且垩白少, 样本整体质量好、营养品质优良; 聚类3样本属于高纤维稻米, 通过对比发现主成分分析法结果与聚类分析法结果一致。
3 讨论与结论
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3.1 讨论
影响稻谷品质的因素有很多方面, 比如遗传[23]、生长环境[24-25]、施肥量与施肥方式[26-27]等, 不同品种、不同产地种植的稻谷表现出不同的品质状态, 本研究中发现留胚粒率属于受稻种和种植地影响最为明显的指标, 稻谷加工企业在收购稻谷时, 应针对留胚粒率的大小以及粒型, 设置稻谷碾制工艺系数[28], 生产留胚米; 此外垩白度和垩白粒率也对稻种和种植地较为敏感, 且垩白度、垩白粒率与精米率成负相关, 这与王荣升等[5]、任鄄胜等[29]和张海霞等[30]研究结果一致, 农户需要在满足稻谷质量和数量要求的基础上, 进一步结合市场需求, 种植出更高品质的优质稻谷; 还有一点值得关注, 目前稻米生产企业和种植农户较为关注出米率这个指标, 不少企业已经把出米率作为收购稻谷的定等指标, 取代了标准中的出糙率。
3.2 结论
本研究确定了辽宁地区125个常见稻种加工生产稻米的质量情况, 发现以变异系数作为标准, 不同品种不同产地稻谷对品质指标影响的大小顺序为: 留胚粒率>垩白粒率>垩白度>精米率>出糙率>水分>灰分>蛋白>糙米质量>脂肪>长宽比>纤维; 利用逐步回归分析法得到: 出糙率=4.672×糙米质量-0.104×垩白粒率+0.141×垩白度-0.860×长宽比-13.205, 因此可以用糙米质量、垩白粒率和垩白度较为简单的指标预测出糙率, 为稻谷初步定等; 采用主成分分析法建立辽宁省稻米品质特性综合评价模型, 确定4个主成分, 累计贡献率80.046%, 通过综合评估得出排名前3的品种分别为: 营口市大石桥市水源镇西青村的域稻17、盘锦市大洼县新立农场张家村的一目惚、盘锦市盘山县甜水乡公兴村的盐丰(47); 通过聚类分析方法确定了3个聚类, 聚类1样本的垩白程度大, 属于短粒型米, 纤维含量高; 聚类2样本属于短粒型米, 且垩白少, 样本整体质量好、营养品质优良; 聚类3样本属于高纤维稻米, 以上结论可为筛选出辽宁地区优质稻谷、稻米提供参考, 为更好地发展辽宁稻谷生产以及提升稻米品质综合潜力提供理论依据。
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2025年第16卷第6期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20241028004
  • 接收时间：2024-10-28
  • 首发时间：2025-07-19
  • 出版时间：2025-03-25
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  • 收稿日期：2024-10-28
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    1.辽宁省粮食科学研究所, 沈阳 110000
    2.辽宁省粮食和物资储备事务服务中心, 沈阳 110000
    3.铁岭市项目服务中心, 铁岭 112000

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* 陈怡岑(1987—), 女, 硕士, 高级工程师, 主要研究方向为粮食储藏与加工。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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