【作者】 王丽；

【导师】 王强；

【作者基本信息】 中国农业科学院 ， 农产品质量与食物安全， 2012， 博士

【摘要】 本文分析了111个花生品种的蛋白质亚基组成、氨基酸组成等特征成分指纹图谱，建立了氨基酸近红外快速无损检测技术，分析了花生感官品质、理化营养品质及加工品质与蛋白质凝胶性、溶解性之间的关系，构建了适宜加工凝胶型和溶解型蛋白质的花生品质评价方法、评价标准，确定了花生的加工适宜性，并在此基础上建立了花生加工专用品种品质基础数据库。本研究明确了花生加工特性，建立了花生加工品质评价方法和标准，实现花生品种品质的科学评价和分类，促进花生加工业的健康发展。本试验选取我国12个花生主要种植省份的111个花生品种作为试验材料。SDS-PAGE指纹图谱分析表明，花生蛋白质由花生球蛋白（Arachin）和伴花生球蛋白（Conarachin）组成，各品种花生球蛋白亚基组成有差异，双纪2号、粤油14号等26个品种缺失35.5kDa蛋白质亚基；不同花生品种Arachin/Conarachin比值变化范围较大，介于0.87～1.68。氨基酸指纹图谱分析表明，天门冬氨酸（3.07±0.60g/100g花生）、精氨酸（3.14±0.53g/100g花生）含量显著高于其他作物，因此被称为花生中的特征性氨基酸。采用PCA和PLS建立花生氨基酸的近红外预测模型，Asp、Thr、Ser、Glu、Gly、Leu、Arg、Cys等预测模型的R2为0.83～0.96，表明近红外预测结果的准确性和精确性接近化学方法。在此基础上，系统全面分析了花生的感官品质、理化营养品质及加工品质之间关系。结果表明，百果重与百仁重（r=0.923），粗脂肪与粗蛋白（r=-0.399），Arachin与Conarachin（r=-0.996），粗脂肪与果形（r=0.661）等在0.05水平上呈显著的关系。花生蛋白质溶解性与凝胶性的硬度、弹性、内聚力相关性分析表明，蛋白质的溶解性与凝胶性的硬度（r=-0.687）和内聚力（r=-0.588）分别呈显著的负相关，初步说明蛋白质溶解性好的品种凝胶性较差，反之亦然。采用Minkowski方法建立了花生蛋白质凝胶性的评价方程：凝胶性0.02680.1618硬度0.3781弹性1.1573内聚力，该方程计算结果与硬度、弹性和内聚力的相关系数分别为0.87、0.41和0.47，该方程预测凝胶性综合值与原始值接近。利用有监督主成分回归分析建立适宜加工凝胶型和溶解型蛋白质花生品质评价模型，通过外部验证确定模型的准确性和可靠性。得到适宜加工凝胶型蛋白质的花生品质评价模型（理论分析）为：该模型预测值和实际值的相关系数为0.937，表明预测值与实际值基本吻合。适宜加工溶解型蛋白质的花生品质评价模型（理论分析）为：溶解性=0.770362粗脂肪-0.60393粗蛋白-0.91626总糖-8.32449胱氨酸+3.214817精氨酸-0.21846伴花生球蛋白-1.1688537.5k Da+1.8193423.5k Da+1.01813915.5kDa-0.44476蛋白质提取率+0.207081出仁率+47.67507该模型预测值和实际值的相关系数为0.820，可以预测未知品种蛋白质溶解性的好坏。为了进一步确定花生的加工适宜性，建立了适宜加工凝胶型蛋白质和溶解型蛋白质的花生品质评价标准。通过K-means聚类分析，将花生蛋白质凝胶性综合值划分为三个等级，即大于1.08的为Ⅰ级（适宜），0.85～1.08为Ⅱ级（基本适宜），小于0.85为Ⅲ级（不适宜）。依据聚类中心值及实际情况，将适宜加工凝胶型蛋白质花生品质评价指标分为三类，适宜、基本适宜和不适宜。适宜的评价标准（理论分析）为：果形为曲棍形、驼峰形、串珠形；粗蛋白大于27.70%、胱氨酸大于0.89%、精氨酸大于3.98%、伴花生球蛋白Ⅰ大于29.35%、粗纤维小于2.53%、甘氨酸小于1.34%、亮氨酸小于1.60%、花生球蛋白/伴花生球蛋白小于1.08%、23.5kDa蛋白质亚基小于20.83%。通过K-means聚类分析，将蛋白质的溶解性划分为三个等级，即大于86的为Ⅰ级（适宜），68～86为Ⅱ级（基本适宜），小于68为Ⅲ级（不适宜）。依据聚类中心值及实际情况，将适宜加工溶解型蛋白质花生品质评价指标分为三类，适宜、基本适宜和不适宜。适宜评价标准为（理论分析）：精氨酸大于4.40%、23.5kDa蛋白质亚基大于24.00%、出仁率大于74.32%、蛋白质提取率大于85.38%、粗蛋白大于27.58%、15.5kDa蛋白质亚基小于5.78%、粗脂肪小于46.95%、伴花生球蛋白Ⅰ小于23.49%、总糖小于5.14%、37.5kDa小于12.65%、胱氨酸小于0.48%。以上两个评价模型中指标数较多，为了加工企业方便、快捷的利用模型选取适宜加工的花生品种，优化以上建立的花生品质评价模型，采用尽量少的指标反映多的问题。得到适宜加工凝胶型蛋白质花生品质评价模型为（实际应用）：凝胶性=e1.5710.02474*果形0.007009*粗蛋白0.04351*精氨酸-0.005*伴花生球蛋白Ⅰ0.06057*23.5kDa该模型预测值和实际值的相关系数为0.718。适宜加工溶解型蛋白质花生品质模型为（实际应用）：4溶解性=1.49017*粗蛋白3.3775*胱氨酸0.39096*伴花生球蛋白Ⅰ56.016274*15.5kDa266.7366该模型预测值和实际值的相关系数为0.699。依据凝胶性符合正态分布的模型（实际应用），采用回归方程的回归系数，确定各指标权重。依据聚类中心值及实际情况，将适合加工凝胶型蛋白质花生品质评价指标分为三类，适宜、基本适宜和不适宜。适宜的评价标准为：果形为曲棍形、驼峰形、串珠形，粗蛋白大于27.42%、精氨酸大于3.70%、伴花生球蛋白Ⅰ大于29.37%、23.5kDa蛋白质亚基小于20.80%。采用本标准确定适宜加工凝胶型蛋白质的花生品种为鲁花11、双纪2号、汴花3号、丰花1号等44个。依据溶解性符合正态分布的模型（实际应用），采用回归方程的回归系数，确定各指标权重。依据聚类中心值及实际情况，将适宜加工溶解型蛋白质花生品质评价指标分为三类，适宜、基本适宜和不适宜。适宜加工溶解型蛋白质的花生品质评价标准为：粗蛋白大于27.58%、胱氨酸小于0.48%，伴球蛋白Ⅰ小于23.49%、15.5kDa蛋白质亚基小于5.78%。采用本标准确定适宜加工溶解型蛋白质的花生品种为豫花9326、白沙1016、豫花15、五彩花生等75个。基于花生品质特性、指纹图谱、花生品质评价模型及评价标准，采用动态网页技术（ASP）构建基于B/S（Browser/Server，浏览器/服务器）建立蛋白用花生加工专用品种数据库。该数据库包括系统管理模块、数据库管理模块及数据操作模块；系统管理模块设置用户组及用户，数据库管理模块设定数据字段及数据字典，数据操作模块将花生及其制品的感官品质、理化营养品质、加工品质、特征成分指纹图谱及品种适宜性评价模型等相关信息输入数据库；用户通过Internet访问服务器端的数据可以实现一个功能完善的花生加工专用品种品质基础数据库。更多还原

【Abstract】 This research analyzed the fingerprint characteristic of protein subunits, amino acids and NearInfrared Reflectance Spectroscopy (NIRS). The relationship of peanut quality with gel property andsolubility were analysis. Process suitability of gel property and solubility were established. Processdatabase were established. Therefore, it‘s necessary to establish a rapid nondestructive testingtechnology, and construct the evaluation methodology and criterion of peanuts quality, for estimatingthe processing suitability scientifically.There were111peanut varieties used in this research. The fingerprint of SDS-PAGE showed that26varieties lack the subunit of35.5kDa. The ranges of arachin/conarachin was0.87～1.68. Thecharacteristic amino acids of peanut were Asp (3.07±0.60g/100g peanut) and Arg (3.14±0.53g/100g peanut). The PCA and PLS was used to establish the models of amino acids (Asp, Thr, Ser,Glu, Gly, Leu, Arg, Cys), the R2of these models ranged from0.83to0.96.The process characteristics of peanuts were analysis in this article. The results showed thathundred seed weight and hundred kernel weight (r=0.923), crude fat and crude protein (r=-0.399),arachin and conarachin (r=-0.996), crude fat and shape (r=0.661) had significant relationship in0.05level.The correlation of peanut protein showed that the relationship of solubility and hardness(r=-0.687), cohesiveness (r=-0.588) were inverse. The Minkowski was used to establish theevaluation equation:gel property0.02680.1618hardness0.3781springiness1.1573cohesiveness. The correlationcoefficients between the newly depicted index and the original ones were0.87,0.41and0.47corresponding to hardness, springiness and cohesiveness, respectively.The super principal component regression analysis was used to establish the gel property andsolubility evaluation models. The quality evaluation model of gel property as followed:TheCoefficient of correlation between predicted value and true value was0.937.The quality evaluation model of solubility as followed:So lub ility0.770362crude fat-0.60393crude protein-0.91626Total sugur-8.32449Cys3.214817Arg-0.21846Conarachin-1.1688537.5k Da1.8193423.5k Da1.01813915.5kDa-0.44476extraction rate0.207081kernelratio47.67507The Coefficient of correlation between predicted value and true value was0.820. The gel property of peanut was divided into three grades. The value of gel property higher than1.08was defined as Ⅰ grade (suitable),0.85～1.08was defined as Ⅱ grade (medium appropriate),lower than0.85was defined as Ⅲ grade (inappropriate). Clustering center value and practicalsituation was used to classify the indexes of peanut into three grades. The varieties which havequgunxing, tuofengxing, chuanzhuxing, crude protein higher than27.70%, crude fiber lower than2.53%, Glu lower than1.34%, Cys higher than0.89%, Leu lower than1.60%, Conarachin Ⅰ higherthan29.35%, arachin/conarachin lower than1.08%,23.5kDa lower than20.83%were suitable toprocess gel. The solubility of peanut was divided into three grades. The value of solubility higher than86was defined as Ⅰ grade (suitable),68～86was defined as Ⅱ grade (medium appropriate), lowerthan68was defined was Ⅲ grade (inappropriate). Clustering center value and practical situation wasused to classify the indexes of peanut into three grades. The varieties which have Arg higher than4.40%,23.5kDa higher than24.00%,15.5kDa lower than5.78%, crude fat lower than46.95%, kernelratio higher than74.32%, ConarachinⅠ lower than23.49%, protein extraction ratio higher than85.38%, crude protein higher than27.58%, total sugar lower than5.14%,37.5kDa lower than12.65%,Cys lower than0.48%were suitable to process solubility.Two of the above models included lots of indexes which could not use in the industry facility.The simplify models contained less indexes but can reflect more problem. The quality evaluationmodel of gel property as followed:gel property e1.5710.02474*s hape0.007009*c rude property0.04351*Arg-0.005*c onarachinⅠ0.06057*23.5kDa The Coefficient of correlation between predicted value and true value was0.718.The quality evaluation model of solubility as followed:The Coefficient of correlation between predicted value and true value was0.699.The varieties which have qugunxing, tuofengxing, chuanzhuxing, crude protein higher than27.42%, crude fibre lower than2.53%, Arg higher than3.70%, Conarachin Ⅰ higher than29.37%,23.5kDa lower than20.80%were suitable to process gel. There was44varieties suitability to processgel property, eg. Luhua11, Shuangji2, Bianhua3, Fenghua1. The varieties which have crude proteinhigher than27.58%, Cys lower than0.48%, ConarachinⅠ lower than23.49%,15.5kDa lower than5.78%were suitable to process solubility. There was75varieties suitability to process solubility, eg.Yuhua9326, Baisha1016, Yuhua15, Wucaihuasheng.ASP was used to establish the process special varieties basis database. The database was visitedby the internet. Sensory quality, chemical quality and processing quality of peanuts and their products,characteristics of fingerprint, and model of processing were input into the database.更多还原