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出 处:《华中农业大学学报》2006年第1期76-80,共5页Journal of Huazhong Agricultural University
基 金:国家自然科学基金项目(39870597)资助
摘 要:2002年每季度自道观河水库采样1次,每次采细鳞鲴(Xenocypris microlepisBleeker)鲜鱼10尾,测量体长、体重,取鳞片鉴定年龄。测定背部肌肉水分、粗蛋白、粗脂肪、粗灰分、碳水化合物等的含量,按Brett andGrove法计算能值。结果表明细鳞鲴肌肉中水分含量为76.38%,干物质粗蛋白含量为17.80%,粗脂肪含量为3.54%,粗灰分含量为1.79%,碳水化合物含量为0.49%;能值为5.91 J/mg(湿重)。各项生化指标和能值无明显季节变化;含水量随鱼年龄的增长而下降,能值、蛋白质、脂肪含量均随年龄增长而增加;能值的增长趋势在3龄前明显,3龄后趋于平缓,可以定性地认为其能量增长的“拐点”年龄为3龄左右。粗蛋白、粗脂肪含量以及能值与鱼体体长、体重都有显著相关关系,且各对相关关系均以二次方程Y=a+bx-cx2的相关性最好。能值Q(%)与水分(Wat)含量的回归方程为Q=70.854 3?1.422 0(Wat)+0.007 5(Wat)2(r=-0.965 9)。通过回归方程以水分含量来估计粗蛋白质、粗脂肪含量和能值是完全可行的。Seasonal sampling of fresh small-scare yellowtail, Xenocypris microlepis was made in Daoguanhe Reservoir in 2002. Body weight, body length were measured and ages were identified on scales. Biochemical composition indices including water content, crude protein, crude fat, crude ash and carbohydrate were determinated. Energy content of dorsal muscle was calculated using Brett and Grove method. The result showed that water content, crude protein, crude fat, crude ash and carbohydrate of dorsal mussel of small -scare yellowtail were 76.38%, 17. 80%, 3. 54%, 1.79% and 0. 49%, respectively. Energy content of dorsal mussel was 5. 91 J/mg(wet weight). There were no significant seasonal variations of all biochemical composition. Water content decreased with the increase in age; while contents of crude protein, crude fat and energy content increased with the increase in age. There was an obvious increasing tendency of energy content before 3 years old and became constant later on. Qualitatively "inflection polnt" of increment of energy was about 3 years old. There were close correlations between crude protein, crude fat, and energy content and body weight, body length; and each pair of correlation could be expressed using quadratic equation Y = a + bx - cx^2. Regressive equation of energy content water content was Q% = 70.854 3 -1. 422 0(Water%) +0. 007 5(Water%)2 (r=-0. 965 9). It is usable to evaluate content of protein, fat and energy using regressive relative equations.
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