玉米青贮瘤胃降解特性与蛋白质分子结构的关系 |
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引用本文: | 王晓帆,张幸怡,郝小燕,高红,丁雪,张永根,辛杭书. 玉米青贮瘤胃降解特性与蛋白质分子结构的关系[J]. 动物营养学报, 2016, 0(6): 1924-1934. DOI: 10.3969/j.issn.1006-267x.2016.06.036 |
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作者姓名: | 王晓帆 张幸怡 郝小燕 高红 丁雪 张永根 辛杭书 |
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作者单位: | 东北农业大学动物科学技术学院,哈尔滨,150030 |
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基金项目: | 国家奶牛产业技术体系项目(CARS-37),寒区规模化奶牛场奶牛精细饲养与粗饲料高效利用关键技术集成与示范(2012BAD12B05-1),东北农业大学青年才俊项目(14QC14) |
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摘 要: | 本试验旨在探索玉米青贮瘤胃降解特性与其蛋白质分子结构的相关性,并建立拟合方程。试验采用尼龙袋法测定11种玉米青贮的干物质、蛋白质以及中性洗涤纤维的瘤胃降解率,并对其降解特性进行计算,利用傅里叶变换红外光谱(Fourier transform infrared spectroscopy,FTIR)技术对玉米青贮样品的蛋白质分子结构(酰胺Ⅰ带、酰胺Ⅱ带、α-螺旋、β-折叠)进行分析。结果表明,酰胺Ⅱ带的峰高分别与干物质有效降解率(DM_(ED))极显著相关(r=-0.71,P0.01),与中性洗涤纤维慢速降解部分的降解速率(NDF_c)(r=-0.52,P0.05)、不可降解部分(NDF__u)(r=-0.46,P0.05)显著相关;酰胺Ⅰ带、Ⅱ带的峰高比分别与干物质快速降解部分(DM_a)(r=0.57,P0.01)、慢速降解部分(DM_b)(r=-0.55,P0.01)极显著相关,与蛋白质不可降解部分(CP_u)显著相关(r=-0.50,P0.05),与蛋白质有效降解率(CP_(ED))趋于相关(r=0.38,P0.10);α-螺旋的峰高分别与干物质不可降解部分(DM_u)极显著相关(r=0.59,P0.01),与蛋白质快速降解部分(CP_a)显著相关(r=0.45,P0.05);α-螺旋和β-折叠的峰高比与干物质慢速降解部分的降解速率(DM_c)极显著相关(r=0.59,P0.01),与蛋白质慢速降解部分的降解速率(CP_c)显著相关(r=0.57,P0.05),与CP_ED显著相关(r=0.43,P0.05);蛋白质分子结构与蛋白质慢速降解部分(CP_b)、中性洗涤纤维快速降解部分(NDF_a)、慢速降解部分(NDF_b)并无相关(P0.10)。玉米青贮蛋白质分子结构对DM_(ED)(R~2=0.50)、CP_(ED)(R~2=0.48)拟合最好。初步证明,可以利用FTIR技术分析玉米青贮瘤胃降解特性与其蛋白质分子结构的相关性,并建立回归方程,同时利用二者的数量关系对玉米青贮的营养价值进行快速、非破坏分析,从而减少传统化学分析耗时、费力、环境污染等缺点。
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关 键 词: | 瘤胃降解特性 傅里叶红外光谱技术 蛋白质分子结构 相关性 多元回归 |
Relationship between Rumen Degradation Characteristics of Corn Silages with Protein Molecular Structures |
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Abstract: | The objective of this present research was to investigate the correlation between rumen degradation characteristics of corn silages with protein molecular structures,and the fitting equation was established.Rumen degradation rates of dry matter,crude protein and neutral detergent fiber of 11 kinds of corn silages were determined by nylon bag technique in order to calculated their degradation characteristics,and protein molecular structures (amide Ⅰ,amide Ⅱ,α-helix and β-sheet) were analyzed by Fourier transform infrared spectroscopy (FTIR).The results showed that:the peak height of amide Ⅱ had a very significant correlation with effective degradable rate of dry matter (r=-0.71,P<0.01),had a extremely significant correlation with degradation rate of slowly degraded part (r=-0.52,P<0.01) and none degraded part (r=-0.46,P<0.01) of neutral detergent fiber;the ratio of amide Ⅰ peak height to amide Ⅱ had a very significant correlation with rapidly degraded part (r=0.57,P<0.01) and slowly degraded part (r=-0.55,P<0.01) of dry matter,had a significant correlation with none degraded part of crude protein (r=-0.55,P<0.05) and tended to have a significant correlation with effective degradable rate of crude protein (r=0.38,P<0.10);the peak height of α-helix had a very significant correlation with none degraded part of dry matter (r=0.59,P<0.01),and a significant correlation with rapidly degraded part of crude protein (r=0.45,P<0.05);the ratio of cα-helix peak height to β-sheet had a very significant correlation with degradation rate of slowly degraded part of dry matter (r=0.59,P<0.01) and a significant correlation with degradation rate of slowly degraded part of crude protein (r=0.57,P<0.05),had a significant correlation with effective degradable rate of crude protein (r=0.43,P<0.05),but no correlation had been found between protein molecular structures with slowly degraded part of crude protein,rapidly degraded part and slowly degraded part of neutral detergent fiber (P>0.10).The equations between protein molecular structures with effective degradable rate of dry matter (R2 =0.50) and crude protein (R2 =0.48) were the best.These results preliminary indicate that,FTIR can be used to analysis the relationship between rumen degradation characteristics of corn silages with protein molecular structures and establish regression equations.With the quantitative relations,analyzing nutritional values of corn silages will be rapidly and nondestructively,thus reducing the disadvantages of environmental pollution,time-consuming and laborious in traditional chemical analysis methods. |
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Keywords: | rumen degradation characteristics FTIR protein molecular structures correlation multi-regression |
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