贮藏期鸡蛋新鲜度指标与S-卵白蛋白含量的相关关系

Correlation Analysis between Egg Freshness Indexes and S-Ovalbumin Content during Storage

为了系统地研究鸡蛋新鲜度变化与S-卵白蛋白含量之间的关系,明确贮藏期间各鸡蛋品质参数对S-卵白蛋白形成的影响程度,本实验选取当日产新鲜海兰褐壳鸡蛋为研究对象,考察了鸡蛋哈夫值、蛋黄指数、pH值等指标与S-卵白蛋白含量的相关性,分析了各鸡蛋品质参数与S-卵白蛋白含量的灰色关联度,并以S-卵白蛋白含量为自变量建立了等价蛋龄预测模型。结果表明:鸡蛋哈夫值与S-卵白蛋白含量之间存在极显著负相关关系(R=-0.913,P<0.01),其中S-卵白蛋白含量与蛋质量之间存在极显著负相关关系(R=-0.367,P<0.01),与浓蛋白高度存在极显著负相关关系(R=-0.905,P<0.01);蛋黄指数与S-卵白蛋白含量之间存在极显著负相关关系(R=-0.900,P<0.01);pH值与S-卵白蛋白含量间存在极显著正相关关系(R=0.648,P<0.01);此外,各品质因素与S-卵白蛋白含量的综合灰色关联度均大于0.6,且pH值是影响S-卵白蛋白含量变化的主导因素(灰色关联度为0.742)。建立的多项式回归等价蛋龄预测模型的决定系数为R^2=0.986 81(P<0.01),模型可靠性高。

In order to systematically investigate the relationship between changes in egg freshness and S-ovalbumin content and to clarify the effect of various egg quality parameters on the increase in S-ovalbumin content during storage, fresh eggs from Hyline Brown laying hens were tested for Haugh unit （HU）, egg yolk index and pH and their correlation with S-ovalbumin content, and the gray correlation degree of egg quality parameters and S-ovalbumin content was analyzed. In addition, the prediction model of equivalent egg age was established with S-ovalbumin content as independent variable. The results showed that there was a strong negative correlation between HU and S-ovalbumin content （R = ？0.913, P 〈 0.01）, and that S-ovalbumin content had a strong negative correlation with egg mas （R = ？0.367, P 〈 0.01） and a strong negative correlation with concentrated protein height （R = ？0.905, P 〈 0.01）. A strong negative correlation existed between egg yolk index and S-ovalbumin content （R = ？0.900, P 〈 0.01）, and the correlation between pH and S-ovalbumin content was positive （R = 0.648, P 〈 0.01）. In addition, the comprehensive gray correlation degree between each quality factor and S-ovalbumin content was more than 0.6, and pH was the dominant factor affecting the change of S-ovalbumin content （gray correlation degree was 0.742）. The decision coefficient （R2） of the established polynomial regression model for equivalent age prediction was 0.986 81 （P 〈 0.01）.