不同笼养方式对鸡蛋蛋黄风味的影响

2023-08-15 00:24高丽冰陈刚王晶齐广海张海军邱凯武书庚
中国农业科学 2023年13期
关键词:叠层电子鼻质构

高丽冰,陈刚,王晶,齐广海,张海军,邱凯,武书庚

不同笼养方式对鸡蛋蛋黄风味的影响

1农业农村部动物产品质量安全饲料源性因子风险评估实验室/农业农村部饲料生物技术重点开放实验室/中国农业科学院饲料研究所,北京 100081;2中国农业大学农业农村部设施农业工程重点开放实验室,北京 100083

【目的】采用感官评价、电子鼻和电子舌检测、质构仪分析,确定传统叠层笼养和栖架福利笼养下鸡蛋蛋黄风味的差异,为鸡蛋蛋黄风味研究提供基础数据。【方法】以传统叠层笼养和栖架福利笼养的55周龄健康京粉蛋鸡所产鸡蛋为试验对象,通过感官评价、电子鼻和电子舌检测、质构仪检测蛋黄的气味、滋味和质感,运用线性判别分析(linear discriminant analysis, LDA)分析、支持向量机(support vector machine, SVM)分析、K-最近邻法(K-nearest neighbor method, KNN)分析和决策树(decision tree)分析对两种笼养方式的蛋黄风味进行判别,探究不同笼养模式对鸡蛋蛋黄风味的影响。【结果】与栖架福利笼养相比,传统叠层笼养的蛋黄颜色评分显著增加(<0.05)。感官评价中,栖架福利笼养组蛋黄的奶香味滋味评分显著高于传统叠层笼养组(<0.05),海苔味滋味和糊口性评分低于栖架福利笼养组(<0.05)。相关性分析结果表明,蛋黄整体喜好度评分与滋味喜好度和质感喜好度评分显著正相关(<0.05)。蛋香味滋味评分与滋味喜好度评分显著正相关(<0.05),蛋香滋味与鱼腥滋味和甜味滋味显著负相关(<0.05),鱼腥滋味与甜味滋味显著正相关(<0.05)。蛋黄颗粒感与蛋黄粘牙度呈显著正相关(<0.05)。仪器检测中,栖架福利笼养组蛋黄在电子鼻传感器W2W(芳香有机硫成分)、W2S(甲醇、乙醇)、W1W(对硫化物灵敏)和W1S(对甲基类灵敏)响应程度显著大于传统叠层笼养组(<0.05),在电子舌传感器SRS(酸味)、STS(咸味)和UMS(鲜味)响应程度显著小于传统叠层笼养组(<0.05),蛋黄质构特性的硬度和咀嚼性显著大于传统叠层笼养组(<0.05)。判别分析可知,K-最邻近法判别方法可依据电子鼻响应值判别两种笼养方式下的蛋黄气味差异,准确率为94.5%。支持向量机算法、K-最邻近法和决策树判别方法可依据电子舌响应值判别两种笼养方式下的蛋黄滋味差异,准确率为100.0%。【结论】栖架福利笼养下鸡蛋蛋黄奶香味滋味增强、海苔味滋味和糊口减弱,电子鼻硫化物传感器响应值增强,电子舌鲜味和咸味传感器响应值减弱。基于电子鼻和电子舌检测,采用K-最邻近法、支持向量机算法和决策树方法能够判别传统叠层笼养和栖架福利笼养下蛋黄风味差异。

蛋黄风味;福利笼养;电子鼻;电子舌;质构特性;产蛋鸡

0 引言

【研究意义】近年来人们对养殖动物福利的重视,正在推动蛋鸡养殖方式转变。2002年瑞典已停止使用传统笼养,2009年荷兰和德国开始逐步淘汰传统笼养,2022年法国市面出售鸡蛋必须来自非笼养养殖场。福利养殖将是蛋鸡养殖的发展趋势,对于保障蛋鸡健康和产品安全、促进蛋品国际贸易方面有重要的意义。目前,我国主要采用叠层笼养和立体散养系统方式,对福利笼养模式进行了有益的探索,如蛋鸡健康和行为、鸡蛋品质等,福利笼养包括装配型鸡笼、单层散养系统、多层散养系统和舍外自由散养系统。栖架笼养属于福利笼养的多层散养系统,平台和底网均设有清粪传送带,实现鸡只与粪便自动分离,保持鸡舍低粉尘浓度和良好的空气质量[1]。与传统笼养相比,福利笼养可降低产蛋后期蛋鸡的肝脏重量和腹脂重量,栖架笼养可增强蛋鸡肱骨强度,骨矿密度和骨矿重量[2-3]。【前人研究进展】不同养殖方式对鸡蛋品质和风味的影响是目前研究者们关注的热点。平层养殖蛋鸡可显著提高鸡蛋蛋壳厚度,不影响其他鸡蛋品质[4]。与笼养蛋鸡所产鸡蛋相比,舍外散养蛋鸡所产鸡蛋的挥发性风味物质浓度降低,感官评价的气味无显著差异[5]。鸡蛋品质及风味直接影响消费者对鸡蛋的选取及满意程度,与经济效益密切相关。风味的形成取决于风味前体物及相互作用,而风味的描述和评价受到人们习惯、喜好等主观因素影响。目前鸡蛋风味的评价,主要包括主观性的感官评价和客观的特征风味物质分析。关于鸡蛋风味的描述,主要是蛋黄风味的描述,报道的有蛋香味、鱼腥味和海洋味等,且主要集中在饲料因素方面[6]。蛋香味为特征风味,主要由磷脂结合的亚油酸和花生四烯酸自动氧化形成,还受油酸和γ-亚麻酸的影响[7-8]。鱼腥味为生鲜鱼的风味,与蛋黄中n-3不饱和脂肪酸呈线性增长关系[9]。食品感官的仪器检测节约成本,提高效率,但仪器响应方式与人类感官系统的响应方式不同[10-12]。电子鼻采用传感阵列监控挥发性化合物,根据传感器响应可得到鸡蛋气味的特性[13]。电子舌通过鸡蛋溶液中分子与生物膜反应可量化鸡蛋的滋味特征[14]。质构仪通过检测鸡蛋物性描述蛋黄质构属性[15-16]。【本研究切入点】笼养方式可能影响鸡蛋风味,但栖架笼养对鸡蛋风味的影响并不清楚。因此,应结合主观感官评价与电子感官仪器分析方法综合判断鸡蛋风味。【拟解决的关键问题】本研究旨在明确传统叠层笼养和栖架福利笼养方式对鸡蛋品质和蛋黄风味的影响,通过分析感官评价与仪器检测的差异以及感官属性间的相关性,确定电子感官仪器检测对两种养殖模式蛋黄风味的判别准确度,为栖架福利笼养的应用及鸡蛋风味研究提供基础数据。

1 材料与方法

1.1 试验时间和地点

蛋鸡养殖于2020年10月6日在中国农业大学上庄实验站进行,样品测定在中国农业科学院饲料研究所和中国标准化研究院实验中心进行。

1.2 试验材料

选取饲养于同一间鸡舍内传统叠层(传统笼养,Traditional caging regime)和栖架福利笼养(栖架笼养,Furnished caging regime)两个笼养方式下55周龄、健康京粉6号产蛋鸡各216只(产蛋率85.76±1.41%,符合峪口京粉饲养手册中正常生产性能指标),饲喂相同的玉米-豆粕型日粮。传统笼养采用传统商品鸡笼,尺寸为0.6 m×0.45 m×0.4 m(长×宽×高),养殖密度为18.5 只/m2。栖架福利笼养尺寸为4.5 m×0.75 m×2.9 m(长×宽×高),内设12根长为0.75 m栖杆、2层产蛋箱(总面积为0.675 m2)和1.05 m2沙浴区,栖杆与饲槽相平行,平均每只蛋鸡占用栖杆长度为0.164 m,同时设置2条集蛋线、3层采食槽以及2条采用乳头式饮水器的饮水线,各层平台与网面均采用金属网上铺设塑料网,饲养密度为16.3 只/m2,本试验笼已完成蛋品质等相关试验研究[17]。每个处理8个重复,每个重复27只鸡。试验鸡第380日龄,每个重复连续2天选取接近平均蛋重的鸡蛋共31枚鸡蛋,共采集496枚鸡蛋样品分析。

1.3 鸡蛋品质检测

电子天平测定蛋重、蛋壳重和蛋黄重用以计算蛋壳比例和蛋黄比例;蛋白高度、蛋黄颜色和哈氏单位使用SONOVA蛋品质自动分析仪(Orka技术有限公司,以色列)测定。

1.4 感官评价

每个重复取10枚鸡蛋样品进行感官评价。感官评价在中国标准化研究院实验中心进行。正式评价前筛选培训评价员,本次感官评价共招募8名感官评价小组成员(4名男性和4名女性,年龄在20岁到35岁之间)。鸡蛋样品经煮蛋器蒸煮15 min,冷却至室温后,分离蛋黄并密封,评价前置于60℃恒温箱中保温。参考Goldberg方法[18],样品进行编码后随机分发给评价员,评价员在未知样品处理的情况下评价样品。评价小组经讨论后确定了描述词汇的3个香气、5个滋味和6个质地描述词。确定描述词后讨论并定义描述词相对应的参考物(煮熟鸡蛋,酒鼻子,纯牛奶,蔗糖,盐溶液,海苔),使用上述参考物培训小组成员。按上述方法制备样品,对样品进行数字编码后,随机呈给评价员。以气味(煮熟鸡蛋蛋黄、氨味酒鼻子和新鲜鱼肉)、滋味(煮熟鸡蛋蛋黄、新鲜鱼肉、氨味酒鼻子、低脂牛奶、蔗糖和海苔)为参照,采用非结构化15 cm线量表,从0分(低)到15分(高)对样品气味、滋味、质感和喜好程度进行评价。每个样品评价前,评价员使用纯净水清除口腔残留样品。每个重复样品评价重复3次,每天1次。

1.5 蛋黄电子鼻和电子舌分析

每个重复分别取3枚和5枚鸡蛋的蛋黄进行电子鼻和电子舌分析。使用煮蛋器蒸煮鸡蛋15 min后冷却至室温,分离出蛋黄,研碎混匀后待测。取6 g蛋黄样品放入15 mL样品瓶后密封置于室温平衡30 min,每个样品做3个平行。电子鼻(PEN3,Airsense公司,德国)的设置参数为:清洗时间180 s,归零时间10 s,样品准备时间5 s,测定时间150 s,载气流速300 mL/min,进样流量300 mL/min。电子鼻传感器及对应的敏感物质见表1。

取30 g蛋黄样品,加蒸馏水120 mL,混匀超声20 min后,5 000 r/min-1离心10 min,取上清液进行测试。采用电化学传感器的电子舌(ARTREE Ⅱ 电子舌,Alpha MOS,法国)测定样品溶液的综合味觉信息,使用去离子水和0.01 mol·L-1的HCl溶液活化传感器后,进行样品测定,每个样品测定前使用去离子水清洗传感器,每个样品重复检测6次,取后4次结果进行分析。电子舌传感器及对应的滋味名称见表1。

1.6 蛋黄质构特性分析

每个重复取3枚蒸煮后的完整蛋黄进行质构分析,采用物性测试仪(TMS-PRO, Ensoul Technology Ltd., 美国)测定质构参数,使用型号为P/25N探头对样品进行连续两次40%的挤压。测定条件:起始力0.05 N;测定速度0.5 mm/s;测后速度0.5 mm/s;压缩程度40%;触发值0.05 N。

1.7 数据处理及统计分析

试验数据使用SPSS软件(Windows22.0版;SPSS Inc., Chicago, IL, USA)分析,独立样本t检验(双尾)用于分析处理间差异。数据表示为平均值±标准差,统计学差异显著水平定义设定为<0.05。使用Origin 2020b软件(Origin Pro, Version 2021. Originlab Corporation, Northampton, Ma, USA)对感官评价数据进行相关性分析。在基于Window 10系统的Matelab 2016软件(Matelab 2016b, The MathWorks, Inc., Natick, MA, USA)中通过分类学习器完成传统笼养和栖架笼养下蛋黄电子鼻和电子舌的判别分析,包括线性判别分析(linear discriminant analysis, LDA)、支持向量机(support vector machine, SVM)分析、K-最近邻法(K-nearest neighbor method, KNN)分析和决策树(decision tree)分析,形成基于分类算法的混淆矩阵,其中1为传统笼养鸡蛋蛋黄,2为栖架笼养鸡蛋蛋黄。

表1 电子鼻和电子舌传感器名称及性能描述

2 结果

2.1 鸡蛋品质分析

笼养方式对蛋重、蛋黄比例、蛋壳比例、蛋白高度和哈氏单位的影响未见显著差异(>0.05)(表2)。与栖架笼养相比,传统笼养的蛋黄颜色评分显著增加(<0.05)。

2.2 蛋黄风味的感官评价分析

栖架笼养和传统笼养下鸡蛋蛋黄感官评价评分表明(表3),笼养方式对蛋黄气味无显著性影响(>0.05),但显著影响蛋黄的滋味和质感评分(<0.05)。与传统笼养方式相比,栖架笼养方式下鸡蛋蛋黄奶香味滋味的评分更高(<0.05)、海苔味滋味和糊口性评分显著降低(<0.05)。两种笼养方式对蛋黄的喜好度评分无显著差异(<0.05)。

2.3 蛋黄风味感官评价的相关分析

对感官评价中属性间的相关分析可知(图1),整体喜好度与滋味喜好度和质感喜好度显著正相关(<0.05),气味喜好度与滋味喜好度显著正相关(<0.05),滋味喜好度与质感喜好度显著正相关(<0.05)。气味喜好度与蛋香味气味显著正相关(<0.05)。蛋黄滋味喜好度与蛋香味滋味显著正相关(<0.05),蛋香滋味与鱼腥滋味和甜味滋味显著负相关(<0.05),鱼腥滋味与甜味滋味显著正相关(<0.05)。蛋黄颗粒感与蛋黄粘牙度呈显著正相关(<0.05)。

表2 不同笼养方式对鸡蛋品质的影响(n=10)

同行数据后所标字母不同表示差异显著(<0.05),未标注或所标字母相同表示差异不显著(>0.05)。下同

The different letters indicate significant difference (<0.05), no letter or the same letter indicate no significant difference (>0.05). The same as below

表3 不同养殖模式对蛋黄感官评价和整体喜好度的影响

A:感官评价喜好度的相关性分析;B:感官评价气味喜好度和气味特征的相关性分析;C:感官评价滋味喜好度和滋味特征的相关性分析;D:感官评价质感喜好度和质感特征的相关性分析

2.4 蛋黄风味的电子鼻和电子舌分析

栖架笼养组蛋黄在电子鼻传感器W2W(芳香有机硫成分),W2S(甲醇、乙醇),W1W(对硫化物灵敏)和W1S(对甲基类灵敏)响应程度显著大于传统笼养(<0.05),说明栖架笼养组蛋黄气味丰富度增强(图2-A)。此外,栖架笼养组蛋黄在电子舌传感器SRS(酸味),STS(咸味)和UMS(鲜味)响应程度显著小于传统笼养(<0.05)(图2-B)。

2.5 蛋黄质构特性分析

与传统笼养相比,栖架笼养熟蛋黄的硬度和咀嚼性显著升高(<0.05)(表4),其他质构特性无显著差异(>0.05)。

2.6 电子仪器检测的判别分析

电子鼻数据判别分析如图3所示,KNN的分类准确率为94.5%,优于LDA和SVM的91.5%,更优于决策树的89.0%。电子舌数据判别分析如图4所示,SVM、KNN和决策树的分类准确率为100%,优于LDA的96.0%。根据混淆矩阵可知,KNN判别传统叠层笼养和栖架福利笼养蛋黄的气味和滋味准确率最高。

图2 不同养殖模式蛋黄电子鼻(A)和电子舌(B)的雷达图(n=8)

表4 不同笼养模式对蛋黄质构特性的影响(n=8)

不同笼养方式蛋黄电子鼻的判别分析:线性判别分析(A),支持向量机(B),K-最邻近法(C)和决策树(D)数字1,传统笼养;数字2,栖架笼养。下同

图4 蛋黄分类算法的电子舌混淆矩阵。

3 讨论

3.1 不同笼养方式对鸡蛋品质的影响

本试验采用同批次京粉产蛋鸡,育雏后分别转入传统叠层笼和栖架福利笼,饲喂相同饲粮并处于相同鸡舍环境下,饲养至55周龄,鸡蛋蛋重、蛋黄比例等指标无显著差别,但传统叠层笼组蛋黄颜色显著加深。有报道,在传统笼养和有机笼养下生蛋黄颜色不同,可能与饲料中添加蛋黄着色剂或色素有关[19]。本试验中,蛋黄颜色的改变可能与不同笼养方式下试鸡的状态有关。有研究表明,类胡萝卜素能够加深蛋黄颜色,还具有鸡体免疫调节作用,在舍外养殖中,色素可能被用于支持免疫系统[20-22]。

3.2 不同笼养方式对鸡蛋蛋黄风味的影响

与传统笼养相比,栖架笼养提高了奶香味滋味评分,降低了海苔味滋味和糊口性评分。有报道,奶香味主要来源于脂肪酸(硬脂酸、油酸和亚麻酸)加热分解,脯氨酸的增加可提高奶香味感官评分[23-24]。蛋黄香味是由极性脂溶性成分和非脂溶性成分共同作用产生[25]。蛋黄香味受养殖方式、饲粮、品种等因素影响。在饲粮中添加椰子油和大麻籽可增强蛋黄蛋香味滋味,可能与蛋黄中n-6不饱和脂肪酸的含量提高有关[9, 26]。品种和发酵饲料会改变蛋黄中半胱氨酸的含量,导致鸡蛋滋味变化[27]。本试验中,栖架笼养组提高蛋黄奶香味滋味,可能是通过改变所含脂肪酸和氨基酸前体物质的组成或含量。另一方面,栖架笼养组蛋黄海苔味滋味降低,说明其前体物质n-3不饱和脂肪酸含量有改变。在饲粮中添加亚麻籽提高了蛋黄中海苔味滋味评分,降低了蛋黄滋味接受度,这由于蛋黄中二十二碳六烯酸含量的增加[7]。与笼养模式相比,散养模式下鸡蛋中n-3不饱和脂肪酸含量增多,n-6不饱和脂肪酸含量减少,且蛋黄滋味感官评分降低[19]。

与传统笼养相比,栖架笼养降低了蛋黄糊口性。糊口性为蛋黄独特的质感特性,表现为蛋黄在口腔中黏附的状态。有机笼养下熟蛋黄质感降低[19]。蛋黄质感受脂蛋白组成和结构影响。蛋液中蛋黄比例增加,降低蛋白溶解度使凝胶特性弹性增强[28]。蛋黄加热后脂质迁移形成上层的高脂质结构和下层的低脂质结构,高脂结构中脂蛋白结晶度降低且形成有序、稳定的结构[29]。此外,在感官评价相关分析中,栖架笼养组奶香味滋味评分提高、海苔味滋味和糊口性评分降低,有助于提高蛋黄喜好度,但蛋黄喜好度评分无显著差异。这可能是由于蛋黄受整体喜好度受滋味喜好度(= 0.66,<0.05)和质感喜好度(= 0.98,<0.05)共同影响。

与传统笼养相比,栖架笼养组蛋黄电子鼻W1W、W2W传感器响应程度显著升高,电子舌鲜味、咸味传感器响应程度显著降低,蛋黄内聚性和硬度的质构特性显著增加。与电子鼻传感器反应的挥发性物质大多由脂肪酸的氧化分解形成[30]。有研究表明,蛋黄电子鼻传感器响应值随贮藏时间和温度呈线性增长,可能与蛋黄中脂肪酸含量变化有关[31]。本研究中,电子鼻感受器响应值存在差异可能由于栖架笼养下蛋黄中脂肪酸发生改变。研究表明,与传统笼养相比,散养蛋鸡所产鸡蛋的脂肪酸组成存在差异[32]。电子舌鲜味和咸味传感器响应值作为蛋黄滋味的主要指标,可用于判断鸡蛋的品种[33]。此外,蛋黄中呈味氨基酸含量的变化影响电子舌鲜味和咸味传感器响应值[31]。鲜味与5'-一磷酸肌苷呈正相关,咸味与氯化物呈正相关[34]。栖架笼养组电子舌传感器响应程度降低可能由于蛋黄中呈味氨基酸减少。本试验结果表明,感官评价的质感喜好度评分与质构特性数值呈负相关,但并未影响福利笼养蛋黄的质感喜好度的评分。在白康等研究中,饲粮添加棉籽油使蛋黄质构特性弹性的数值显著增加,蛋黄难以嚼碎,熟蛋黄口感品质降低[35]。栖架笼养下蛋黄内聚性和硬度的质构特性增加可能与蛋黄的脂质组成和脂蛋白结构有关。在蛋液中添加奶酪可降低炒蛋硬度和内聚性,可能由于奶酪脂质进入蛋液脂蛋白基质增加了蛋白间的可塑性,高温高压处理使脂质结构紧密,从而增强炒蛋硬度、内聚性和粘附性[36]。

3.3 不同笼养方式下蛋黄风味的判别分析

采用KNN、SVM和决策树方法,基于电子鼻和电子舌数据,能够判别传统叠层笼养和栖架笼养下蛋黄气味和滋味。以电子鼻传感器响应值为基础,KNN可有效判别不同笼养方式下蛋黄气味。KNN可快速建立模型,可判别海兰褐、五黑鸡和北农2号鸡蛋蛋清和蛋黄的气味[31, 37]。电子鼻响应值使用SVM、主成分分析和DFA分析,可判断蜂蜜的来源和质量[38]。基于电子舌数据,KNN、SVM和决策书可有效判别两种笼养方式下蛋黄的滋味。研究表明,以电子鼻传感器响应值为基础,结合SVM可有效预测牛肉存贮时间和微生物群的种群及数量[12]。王琼等研究表明,基于电子鼻和电子舌结果,主成分分析可判别不同烟熏工艺的培根,且与模糊数字感官评价法结果一致[39]。

4 结论

(1)传统叠层笼养和栖架福利笼养对鸡蛋蛋重、蛋黄比例等指标无影响,但传统叠层笼组蛋黄颜色显著加深。

(2)栖架笼养下鸡蛋蛋黄的奶香味滋味增强、海苔味滋味和糊口性减弱,并且电子鼻的硫化物传感器响应程度更强,电子舌的咸味和鲜味传感器响应值降低。

(3)采用KNN、SVM和决策树方法,基于电子鼻和电子舌检测,能够判别传统叠层笼养和栖架福利笼养下蛋黄气味和滋味的差异。

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Effects of Different Caging Regimes on Egg Yolk Flavor of Laying Hens

1Laboratory of Quality & Safety Risk Assessment for Products on Feed-origin Risk Factor, Ministry of Agriculture and Rural Affairs/Key Laboratory of Feed Biotechnology, Ministry of Agriculture and Rural Affairs/Institute of Feed Research, Chinese Academy of Agricultural Sciences, Beijing 100081;2Key Laboratory of Agricultural Engineering in Structure and Environment, Ministry of Agriculture and Rural Affairs/China Agricultural University, Beijing 100083

【Objective】In this study, sensory evaluation, electronic nose detection, electronic tongue detection and texture analyzer detection were used to determine the differences in egg yolk flavor between traditional caging regime and furnished caging regime, to provide basic data on the egg yolk flavor. 【Method】The eggs were produced by Jing Tint 6 laying hens that were 55 weeks old and healthy in traditional caging regime and furnished caging regime that was used as the test objects. The aroma, flavor and texture of egg yolk were detected by sensory evaluation, electronic nose detection and electronic tongue detection, and texture analyzer. Linear discriminant analysis (LDA) analysis, support vector machine (SVM) analysis, K-nearest neighbor method (KNN) analysis and decision tree analysis were used to distinguish the yolk flavor of the two caging regimes to explore the influence of different caging regimes on the flavor of egg yolk.【Result】The yolk color was significantly increased in traditional caging regime compared with furnished caging regime (<0.05). The milky flavor scores of egg yolk in furnished caging regime were significantly higher than that in traditional caging regime (<0.05), and the seaweed flavor scores and stickiness scores of egg yolk in traditional caging regime were higher than those in furnished caging regime (<0.05). The results of correlation analysis showed that the overall preference score of the yolk was significantly correlated with the acceptance of flavor scores and texture scores (<0.05). Egg flavor was significantly negatively correlated with fishy flavor and sweet flavor (<0.05), and the fishy flavor was significantly positively correlated with sweet flavor (<0.05). There was a significant positive correlation between egg yolk lumpy and egg yolk adhesive dentition (<0.05). The responses of W2W, W2S, W1W and W1S of electronic nose sensors in furnished caging regime were significantly higher than those in traditional caging regime (<0.05), and the responses of SRS, STS and UMS of egg yolk electronic tongue sensors in furnished caging regime were significantly lower than those in traditional caging regime (<0.05). The hardness and chewiness of egg yolk in furnished caging regime were significantly higher than that in traditional caging regime (<0.05). The KNN method could discriminate the differences in egg yolk aroma in the different caging regimes based on the responses of the electronic nose, and the accuracy was 94.5%. The SVM, KNN method and decision tree could distinguish the differences in egg yolk flavor in the different caging regime based on the responses of the electronic tongue, with 100% accuracy rate. 【Conclusion】In conclusion, the milky flavor of egg yolk was increased in furnished caging regime, and seaweed flavor and stickiness were reduced. The instrument detected the increased responses of the electronic nose sulfide sensor and the decreased responses of the electronic tongue umami and salty sensors in furnished caging regime. According to the responses of electronic nose and electronic tongue, the differences in egg yolk flavor in two different caging regimes could be effectively distinguished by KNN analysis, SVM analysis and decision tree analysis.

egg flavor; furnished caging regime; electronic nose; electronic tongue; texture characteristics; laying hen

10.3864/j.issn.0578-1752.2023.13.014

2022-04-26;

2023-02-28

现代农业产业技术体系专项资金资助(CARS-40-K12)、中国农业科学院农科英才特殊支持计划(NKYCQN-2021-016)

高丽冰,E-mail:18811618200@163.com。通信作者王晶,Tel/Fax:010-82106097;E-mail:wangjing@caas.cn

(责任编辑 林鉴非)

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