摘要
为寻找草莓品质的快速无损预测方法,利用LCR测试仪测试分析了草莓介电谱变化规律;以遗传算法(Genetic Algorithm,GA)筛选出各品质指标(呼吸强度、可溶性固形物含量和失重率)的特征频率点;以特征频率下的介电参数建立了草莓品质的偏最小二乘(Partial Least Squares,PLS)预测模型。研究结果表明:以GA法筛选频率后的介电参数所建立的呼吸强度、可溶性固形物和失重率的GA-PLS模型RPD值和R^2值分别为5.21、3.14、4.89和0.941、0.852、0.906,各品质指标预测值与实测值无显著差异(p>0.05)。介电谱技术结合遗传算法可用于预测贮藏期草莓的品质。
In order to find rapid non-destructive prediction methods for strawberry quality, dielectric spectrum was tested and its change rule was analyzed with Inductance, Capacitance, Resistance tester（ LCR）.The characteristic frequency points of quality indicators （respiration intensity, soluble solids content and weightlessness rate）were selected out by genetic algorithm（GA）.Partial Least Squares（PLS） quality prediction models were established based on the dielectric parameters at the characteristic frequency points. The results showed that the Relative Percent Deviation（RPD） and R~ values of the GA-PLS model for respiration intensity, soluble solid content（TSS） and weight loss rate established based on dielectric parameters selected out by GA were 5.21,3.14,4.89 and 0.941 ,0.852,0.906, respectively.There was no significant difference between the predicted value and the measured value（ p 〉0.05）for each quality indicator.Dielectric spectrum technology combining with GA can be used to predict the quality of the storage period of strawberries
出处
《食品工业科技》
CAS
CSCD
北大核心
2016年第23期272-276,共5页
Science and Technology of Food Industry
基金
国家自然科学基金资助项目(31160346)
关键词
介电谱
草莓
遗传算法
品质预测
dielectric spectrum
strawberry
genetic algorithm
quality prediction
