Mogodiniyai Kasmaei K, Rustas B-O, Spörndly R, Udén P
Department of Animal Nutrition and Management, Swedish University of Agricultural Sciences, Kungsängen Research Center, SE-753 23 Uppsala, Sweden.
J Dairy Sci. 2013 Oct;96(10):6644-9. doi: 10.3168/jds.2013-6858. Epub 2013 Aug 16.
A meta-analysis was conducted to establish linkages between crop and fermentation variables. Data from well-controlled mini silage studies were used in which no additives had been used and no ingress of air had occurred. The silage set consisted of data on crop chemical composition and epiphytic lactic acid bacteria count, and fermentation products (organic acids, alcohols, and ammonia-N) from 118 silages made from 30 grass, 7 legume, 15 grass and legume mixtures, and 66 whole-crop maize samples. The prediction models for fermentation products on crop variables were obtained by stepwise multiple regression analysis. Perennial forage and maize silages were analyzed separately. The best models were obtained for acetic acid in perennial forage silages, with a coefficient of determination of 0.63, and for lactic acid and ethanol in whole-crop maize silages, with coefficients of determination of 0.84 and 0.61, respectively. Fermentation products of perennial forage and maize silages were best related to dry matter and crude protein contents, respectively. Overall, the prediction equations were weak.
进行了一项荟萃分析,以建立作物与发酵变量之间的联系。使用了来自精心控制的小型青贮研究的数据,这些研究未使用添加剂且未发生空气进入的情况。青贮数据集包括118个青贮饲料的作物化学成分、附生乳酸菌计数以及发酵产物(有机酸、醇类和氨态氮)的数据,这些青贮饲料由30个禾本科牧草、7个豆科牧草、15个禾本科与豆科混合牧草以及66个全株玉米样本制成。通过逐步多元回归分析获得了发酵产物关于作物变量的预测模型。多年生牧草青贮饲料和玉米青贮饲料分别进行了分析。多年生牧草青贮饲料中乙酸的最佳模型决定系数为0.63,全株玉米青贮饲料中乳酸和乙醇的最佳模型决定系数分别为0.84和0.61。多年生牧草青贮饲料和玉米青贮饲料的发酵产物分别与干物质和粗蛋白含量最为相关。总体而言,预测方程的效果较弱。