食品科学
食品科學
식품과학
FOOD SCIENCE
2009年
15期
59-62
,共4页
何青云%陈从贵%王武%方红美%史勇立
何青雲%陳從貴%王武%方紅美%史勇立
하청운%진종귀%왕무%방홍미%사용립
鲜牛乳%瞬变高压%中温%乳过氧化物酶%活性
鮮牛乳%瞬變高壓%中溫%乳過氧化物酶%活性
선우유%순변고압%중온%유과양화물매%활성
raw milk%instantaneous high-pressure%medium temperature%laetoperoxidase%activity
本研究基于连续高压射流形成的脉冲加压方式,通过单因素和二次回归正交组合试验考察瞬变高压对鲜牛乳中乳过氧化物酶(LP)的影响.结果表明:进料温度35℃、处理4min条件下,40~80MPa的瞬变高压能够显著激活LP酶;相同进料温度下,60MPa处理2~8min,LP酶活性随处理时间的延续显著降低(P<0.05);20MPa瞬变压力下,进料温度为45℃时LP酶活性达到最高;影响LP酶活性的主次顺序为:进料温度>处理压力>处理时间,而且该三个因素对LP酶活性的影响存在交互作用,并可用二次多项式模型Y=62.70-9.43A2-7.96B2+3.44C2加以描述.
本研究基于連續高壓射流形成的脈遲加壓方式,通過單因素和二次迴歸正交組閤試驗攷察瞬變高壓對鮮牛乳中乳過氧化物酶(LP)的影響.結果錶明:進料溫度35℃、處理4min條件下,40~80MPa的瞬變高壓能夠顯著激活LP酶;相同進料溫度下,60MPa處理2~8min,LP酶活性隨處理時間的延續顯著降低(P<0.05);20MPa瞬變壓力下,進料溫度為45℃時LP酶活性達到最高;影響LP酶活性的主次順序為:進料溫度>處理壓力>處理時間,而且該三箇因素對LP酶活性的影響存在交互作用,併可用二次多項式模型Y=62.70-9.43A2-7.96B2+3.44C2加以描述.
본연구기우련속고압사류형성적맥충가압방식,통과단인소화이차회귀정교조합시험고찰순변고압대선우유중유과양화물매(LP)적영향.결과표명:진료온도35℃、처리4min조건하,40~80MPa적순변고압능구현저격활LP매;상동진료온도하,60MPa처리2~8min,LP매활성수처리시간적연속현저강저(P<0.05);20MPa순변압력하,진료온도위45℃시LP매활성체도최고;영향LP매활성적주차순서위:진료온도>처리압력>처리시간,이차해삼개인소대LP매활성적영향존재교호작용,병가용이차다항식모형Y=62.70-9.43A2-7.96B2+3.44C2가이묘술.
Pulsed pressure caused by the continuous high-pressure jet of reciprocating pump was applied to treat raw milk for sterilization. The effects of feed temperature, pressure and treatment time on the activity of lactoperoxidase in raw milk were investigated by single-factor and quadratic orthogonal rotation combination design methods. When raw milk was pressurized at 40-- 80 MPa for 4 min at 35 ℃, the activity of laetoperoxidase elevated significantly. While at the same temperature, pressure treatment at 60 MPa for 2-8 min led to sustained marked decline of tbe activity of lactoperoxidase(P < 0.05). The highest activity of lactoperoxidase was attained by instantaneous 20 MPa pressure treament at 45 ℃. The significant sequence of the three factors affecting the activity of lactoperoxidase (Y) was as follows: feed temperature (A) > pressure (B) > treatment time (C) and all these factors had a significant interaction effect, which could be described by a regression equation: Y = 62.70 - 9.43A2-7.96B2+3.44C2.