构树发酵饲料在猪禽养殖中的应用研究进展

构树(Broussonetia Papyrifera)资源丰富,在我国各地已被广泛种植,构树叶中粗蛋白质、粗纤维和糖类含量较高,还富含黄酮、生物碱等多种功能性活性物质,具有耐贫瘠、适应性强和生长迅速等优点,是一种开发利用价值极高的畜禽饲用原料资源。但鲜构树叶饲喂难以被猪禽直接消化,因此采用微生物降解的方式产生构树发酵饲料,以提高饲料消化率。构树发酵饲料替代部分常规饲料,饲喂猪禽,不仅绿色环保,适口性较好,而且改善了猪肉及鸡蛋的质量及风味,降低了饲养成本,提高了经济效益。本文着重介绍了构树作为一种新型蛋白饲料原料资源的饲用价值及构树发酵饲料替代部分其他饲料原料饲用于猪、禽养殖中的应用研究进展,探讨了构树发酵饲料在发展中存在的问题,并对其应用前景进行了评估与展望。     

茶多酚作为饲料添加剂在猪生产中的应用

茶叶中主要的活性物质茶多酚具有优异的抗氧化、抑菌、抗癌等生物学功能,作为饲料添加剂具有无毒、无害、无残留等优点,在养殖生产中有良好的应用效果。本文主要综述了茶多酚作为饲料添加剂在猪生产中的应用现状。     

测定饲料中维生素A和维生素E含量方法的研究

本文旨在建立一种能同时准确测定饲料中维生素A和维生素E含量的方法,试验将样品在碱性条件下65℃水浴超声皂化提取,冰乙酸调pH至中性,乙醇稀释后直接用高效液相色谱法(HPLC)进行测定。结果表明:维生素A在0.036~108IU/mL线性关系良好,相关系数为1.00000,检出限1000IU/kg,方法回收率为95.8%~98.8%,RSD为0.8%~4.4%(n=5);维生素E在0.6~125μg/mL线性关系良好,相关系数为0.99998,检出限15mg/kg,方法回收率为95.3%~102.2%,RSD为0.8%~4.2%(n=5)。本方法快速简便,适用于配合料、浓缩料、维生素预混料和复合预混料中同时准确测定维生素A和维生素E的含量,相对于国标法节省了大量的时间和试剂,可应用于日常大批量饲料检测中。     

电子商务环境下大型饲料企业商业模式的创新发展

我国饲料产业是一个涉及农业、畜牧业以及服务业的传统产业,长久发展中具有比较完善的产业链,同时也具有相对固定的商业模式。饲料生产企业一般在产业经济中起重要作用。但由于近几年电子商务发展迅速,饲料企业传统商业模式发生较大变化,而且由于价值链单向流动,产业发展稳定性受到威胁,导致饲料企业在发展中遇到诸多挑战。为了更好的发展,饲料企业在电子商务环境下必须要积极实施商业模式改革创新,积极拓展新的盈利途径,选择适合自身发展的商业模式。本文主要分析电子商务环境下大型饲料企业商业模式的创新措施。     

燕麦与苜蓿不同比例组合对驴盲肠体外发酵的影响

研究燕麦干草与苜蓿不同比例组合对驴盲肠液体外发酵的影响,旨在为肉驴养殖中粗饲料的科学利用提供理论依据。将燕麦干草和苜蓿按干物质比为80∶20、60∶40、40∶60和20∶80分为Ⅰ、Ⅱ、Ⅲ、Ⅳ组,通过体外产气法与人工瘤胃持续发酵法培养2、4、8、12和24 h,各时间点3个重复,发酵终止后测定发酵参数和饲草养分降解率,通过24 h时发酵参数的加权估算值计算饲草组合效应值。结果表明:1)燕麦与苜蓿不同比例组合影响了其养分降解率,随着苜蓿比例的增加,干物质(DM)和酸性洗涤纤维(ADF)降解率增大,Ⅳ组显著高于Ⅰ组(P<0.05),各组中性洗涤纤维(NDF)降解率差异不显著(P>0.05)。2)随着苜蓿含量的增加,pH逐渐升高,Ⅳ组显著高于Ⅰ组(P<0.05);各时间点产气量(GP)均为Ⅱ组显著高于其余3组(P<0.05),且24 h时Ⅳ组显著高于Ⅰ和Ⅲ组(P<0.05);从发酵12 h开始Ⅲ、Ⅳ组氨态氮(NH_3-N)浓度显著高于Ⅰ、Ⅱ组(P<0.05);24 h时Ⅱ组微生物蛋白(MCP)浓度显著高于Ⅲ组(P<0.05),与Ⅰ、Ⅳ组无显著差异(P>0.05);燕麦与苜蓿不同比例组合对挥发性脂肪酸(VFA)有显著影响,24 h时Ⅰ和Ⅳ组丙酸浓度显著高于Ⅱ和Ⅲ组(P<0.05),而Ⅰ、Ⅱ组总VFA(TVFA)含量显著高于Ⅲ、Ⅳ组(P<0.05)。3)发酵24 h后Ⅰ、Ⅱ和Ⅳ组均产生正组合效应,且Ⅳ组效应值最大,而Ⅲ组产生负组合效应。综上所述:燕麦与苜蓿按20∶80组合时能提高DM、NDF和ADF降解率,且多项组合效应值更高;燕麦与苜蓿饲喂驴以20∶80组合效果较好。     

植物性添加剂对肠道调控作用的研究进展

畜禽养殖业特别是反刍动物对新型饲料添加剂的需求越来越高,植物次生代谢产物和提取物逐渐引起人们的关注,但关于其对反刍动物瘤胃发酵、甲烷产生及生产性能影响的研究较少。本综述的目的是提供有关植物提取物和次生代谢产物的现有研究数据,探讨其作为添加剂对胃肠道功能的调节作用。     

Prevotella copri,a potential indicator for high feed efficiency in western steers

There has been a great interest to identify a microbial marker that can be used to predict feed efficiency of beef cattle. Such a marker, specifically one that would allow an early identification of animals with high feed efficiency for future breeding efforts, would facilitate increasing the profitability of cattle operations and simultaneously render them more sustainable by reducing their methane footprint. The work presented here suggests that Prevotella copri might be an ideal microbial marker for identifying beef cattle with high feed efficiency early in their life span and in the production cycle. Developing more refined quantification techniques that allow correlation of P. copri to feed efficiency of beef cattle that can be applied by lay people in the field holds great promise to improve the economy of cattle operations while simultaneously reducing their environmental impact by mitigating methane production from enteric fermentation.     

Theoretical turnover rate of the rumen liquid fraction in dairy cows and its relationship to feed intake,rumen fermentation,and milk production

Ruminant animals are able to convert plant materials (grain and the human‐indigestible portion of carbohydrates) to milk and meat. In this conversion, most of the plant materials are digested by rumen fermentation and are changed to short‐chain fatty acids, microbial cells, and methane, which is released into the atmosphere. The relationships among feed, rumen fermentation, and milk production are poorly understood. Here we report a novel indicator of characteristics of rumen fermentation, theoretical turnover rate (TTOR) of the rumen liquid fraction. The TTOR was calculated from the presumed rumen volume (PRV) which is estimated by dividing the methane yield by the methane concentration of rumen fluid. The formula for the TTOR is: TTOR = PRV/body weight^0.75. Our present analyses confirm that the TTOR as an indicator is capable of connecting feed, rumen fermentation, and milk production, because dry matter intake/TTOR showed a strong correlation with milk yield/TTOR. In addition, the TTOR may be related to ruminal pH, as we observed that the ruminal pH decreased as the TTOR increased. We propose that the TTOR is a factor characterizing rumen fermentation and a good indicator of the productivity of ruminants and dysbiosis of the rumen microbiome.     

Diagnostic Feed Values of Natural Grasslands Based on Multispectral Images Acquired by Small Unmanned Aerial Vehicle

Grasslands are the largest renewable source of terrestrial chlorophytes. Furthermore, grasslands can be both fiber sources and the primary metabolizable energy source for ruminants. Therefore, rapid, accurate, and large-scale monitoring of grassland ecosystems is important to provide spatial information on forage quality control and rangeland management. In this experiment, 100 grassland sites were randomly selected in two study areas. A multiaxis unmanned aerial vehicle (UAV) made 26 flights over those areas to capture spectral images during August 2016, which enabled the acquisition of vegetation index values of the grassland sites. Next, grassland plots were harvested and the nutritional composition of the grass was determined. After selecting the most sensitive spectral information for each nutritional value, retrieval models for grassland nutrition were constructed. Predictor variables of the models were then tested on the samples. The results demonstrate that there are correlations between nutritional values and vegetation indices. The predicted values of the coefficient of determination (R²-P) and root mean square error (RMSE) for dry matter (DM) were 0.676% and 4.719%. The same values for crude protein (CP) were 0.653% and 1.361%. The R²-P and RMSE values for in vitro DM digestibility (IVDMD) prediction models were weak, but they could be improved by more sensitive wavelengths and improved mathematical models to fit the data. The results show that UAV remote sensing can be used to estimate the feed values of natural grassland and that this sensing approach provides a rapid, flexible, and efficient method of estimating feed values. Although the prediction models for nutritional values need to be improved, they still opened perspectives for the use of UAV-based remote sensing in rangeland management and grassland husbandry.