摘要
采集了储藏0-5年的60个籼稻样品的电导率、脂肪酸值、丙二醛（MDA）含量、过氧化氢酶（CAT）活性、过氧化物酶（POD）、多酚氧化酶（PPO）活性等品质指标的测定数据,然后采用多元逐步回归分析法,对上述指标进行了新鲜度敏感指标的筛选,建立了敏感指标与稻谷新鲜度的预测模型,并加以验证.结果表明：电导率、MDA含量对籼稻新鲜度有显著影响,其中电导率对新鲜度敏感度最大,MDA含量次之;电导率、MDA含量与籼稻新鲜度间的多元回归模型公式为Y=0.0624X电导率＋1.156XMDA含量.验证结果表明：多元回归模型是切合实际的,电导率、MDA含量作为籼稻新鲜度敏感指标是正确的.
The measured data of quality indexes such as electrical conductance（EC）, fatty acid value, MDA content （MDAC） , enzyme （ CAT, POD, PPO） activity were collected for the 60 long - grain riee samples with storage time range from 0 to 5 year in this paper. The sensitive indexes of long-grain riee freshness were selected from above-mentioned indexes by multiple stepwise regression of SPSS10.0, and the mathematical forecasting model of the rice freshness was established and verified. Those results show that two indexes have significantly influence on rice freshness, electrical conductivity is highly sensitive to long-grain rice freshness, and MDA content takes second place. Multiple regression model between electrical conductivity, MDA content and long-grain riee freshness is Y = 0. 062 4XEC ＋ 1. 156XMDAC --3. 750. The verified results show that the multiple stepwise regression model could practically reflect the freshness of long -grain rice, and the selected resuits are reliable.
出处
《河南工业大学学报（自然科学版）》
CAS
北大核心
2007年第4期12-15,共4页
Journal of Henan University of Technology：Natural Science Edition
关键词
籼稻
新鲜度
敏感指标
筛选
验证
long - grain rice
freshness
sensitive index
selecting
verifying
