基于相关性和时序分析的鲜食黄桃安全贮藏期的确定及品质预测
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周慧娟,女,上海市农业科学院副研究员,博士

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上海市农委项目(编号:沪农科推字〔2020〕第2-14号);农业农村部科技教育司—国家桃产业技术体系项目(编号:CARS-31);上海市农委重点攻关项目(编号:沪农科推字〔2018〕第1-7号)


Prediction of safe storage period and quality of fresh yellow peach based on correlation and time series analysis
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    摘要:

    目的:建立鲜食黄桃安全贮藏期预测模型,实现贮藏品质的预警预测。方法:以锦绣黄桃为试材,对3个采摘期入库果实的带皮硬度、果肉组织硬度、果实色差、可溶性固形物含量等指标进行测定,并对果实质地、色泽、风味和香气4个感官模块进行评分,利用相关性和时序分析技术进行安全贮藏期的确定及品质预测。结果:利用轮廓曲线图确定了最佳聚类数为4,主要表现为果实硬度、可溶性固形物含量及果实红绿色差的差异,与消费者关注的质地、风味和色泽感官模块一致;果实质地、色泽和风味3个感官评分模块间有较强共线性,贮藏时间与果实硬度和果肉组织硬度呈负相关,与果实红绿色差呈正相关;果实红绿色差与果实带皮硬度和果肉组织硬度呈负相关,可作为硬度无损检测的表征因子之一。结论:温度(10.0±0.5) ℃、相对湿度80%~85%条件下,建立了非线性果实带皮硬度和果肉组织硬度预测数学模型f[T.(a,k,b)]=a×exp(k×T)+b和线性果实红绿色差预测数学模型f(x)=kx+b,两个预测模型的预测误差较低(R2>0.9,平均误差<0.2)。

    Abstract:

    Objective: In order to study the correlation between fruit firmness, total soluble solids, red and green color, sensory scores of fresh yellow peaches, a prediction model of safe storage period of yellow peach was established to realize early warning and prediction of fruits quality. Methods: Solute Jinxiu peach was used as test material,firmness with skin, firmness without skin, fruit color difference,soluble solid contentand other indexes of the fruits in storage in three picking periods were measured, and sensory scores were made in four modules: fruit texture, color, flavor and aroma. The correlation analysis and time series analysis techniques were used to evaluate and establish a mathematical prediction model. Results: The best cluster number determined by contour curve is 4, which mainly showed the differences of fruit firmness, red-green color and soluble solids content, itwas consistent with the three module features of texture, color and flavor that consumers paid attention to.There is strong collinearity among sensory scores of the three modules of fruit firmness, color and flavor. Storage time is negatively correlated with fruit with skin and firmness without skin, and positively correlated with fruit red-green color difference.The red-green color of fruit is negatively correlated with fruit with skin and firmness without skin, which can be used as one of the characterization factors for nondestructive testing of firmness. Conclusion: At a temperature of (10.0±0.5) ℃ and a relative humidity of 80%~85%,a nonlinear prediction model of fruit with skin and firmness without skin was established: f[T.(a,k,b)]=a×exp(k×T)+b; The linear prediction model of red-green color of fruit was established: f(x)=kx+b. The verification results show that the prediction error of the above two prediction models is low (R2>0.9, average error<0.2).

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周慧娟,高晓沨,叶正文,等.基于相关性和时序分析的鲜食黄桃安全贮藏期的确定及品质预测[J].食品与机械,2022,(8):144-151,226.
ZHOU Hui-juan, GAO Xiao-feng, YE Zheng-wen, et al. Prediction of safe storage period and quality of fresh yellow peach based on correlation and time series analysis[J]. Food & Machinery,2022,(8):144-151,226.

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  • 在线发布日期: 2022-10-16
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