高钙日粮对蛋鸡生产性能及出壳雏体内锌含量的影响

生长期日粮钙>3.11%,可使蛋鸡性成熟期明显延缓,开产日龄推迟;其蛋锌及子代出壳雏血锌和多数组织锌含量明显降低,但胚胎及出壳雏鸡未见畸变.出壳雏血锌含量能反映体内锌状态,可作为其评价指标.产蛋期高钙(6.11%)或低钙(0.83%)日粮均可使产蛋性能及孵化率降低.     

冰鲜鸡生产链中沙门氏菌的分离鉴定及PFGE分型研究

为揭示冰鲜鸡生产链中沙门氏菌的分布及传播机制,本研究于2013年7月～2013年12月采集广东某大型一体化养鸡企业下属2个种鸡场、2个孵化场、2个肉鸡场、1个屠宰场和5个销售点样品,用常规法和PCR进行沙门氏菌的分离鉴定,并对分离出的沙门氏菌进行血清学鉴定和PFGE分子分型.种鸡场、肉鸡场、屠宰场和销售点的沙门氏菌的检出率分别为1.46%(7/480)、7.00%(21/300)、62.86%(22/35)和54.67%(41/75),孵化场雏鸡胎粪检出率为1.11%(2/180),死胚检出率为12.00%(9/75).屠宰和销售环节是沙门氏菌污染的重要环节,食品安全风险较高.102株沙门氏菌共产生24种不同的PFGE谱型,从不同环节分离到多组相似度为100%的沙门氏菌,表明冰鲜鸡生产链中存在沙门氏菌沿生产链传播的现象.     

控光增绒技术在辽宁绒山羊中应用效果观察

2010～2012年,辽宁省畜牧科学研究院先后在本院科技示范场、凤城市绒山羊养殖户,开展了辽宁绒山羊控光增绒试验,设置了不同控光时间的试验组以及相应的对照组,以期验证该项技术在辽宁地区和辽宁绒山羊生产中的应用效果。试验结果表明,该项技术对辽宁绒山羊增绒效果不明显,达不到一年两次剪绒、提高产绒量的目的,建议谨慎将该项技术应用于辽宁地区辽宁绒山羊生产中。     

青海肉羊业生产现状及发展对策

针对国内外及青海省肉羊业生产现状和发展趋势,分析了青海省发展肉羊业的有利条件和存在的问题,并从加强对发展肉羊业的组织领导、建立肉羊良种繁育体系、大力开展经济杂交,实现商品肉羊杂交化、组织肥羔生产、加快畜群周转、加大草原建设和饲草料基地建设、培育“龙头企业”、注重肉羊生产加工环节的无公害化、落实疫病虫防治检疫制度等方面,对发展青海肉羊业生产提出了对策。     

已形成产业化格局的苍溪毛兔业

苍溪县近年来抓住毛兔产业西移的契机 ,采取增投入、普科技、抓饲料、建市场、扶龙头、强领导等措施大力发展长毛兔。一个市场牵龙头 ,龙头连基地 ,基地带农户的大产业 ,大规模 ,大流通 ,大市场 ,大效益的毛兔产业化发展格局已基本形成。 1 999年底 ,全县存栏毛兔 2 0 1 5万只 ,产毛 95 8吨 ,兔业产值达 1 6亿元 ,占牧业总产值的 2 9 4 % ,兔业创税 1 0 0 0余万元。通过养兔 ,全县已有 8 5万余农户摆脱贫困 ,走上了富裕之路     

绿色富硒牧草饲料作物生产技术规程

本规程规定了绿色富硒牧草饲料作物的生产基地环境、种植区域分布、生产管理、刈割利用、票证管理等内容,并制定了牧草饲料作物硒含量达到0.01～0.1mg/kg的产品标准.     

蜂王浆生产新技术的研究--产浆王台中卵孵化率的研究

本文就蜂王产在特种巢脾台基中卵的孵化率和提高卵的孵化率等问题进行了研究,结果表明,(1)蜂王在特种巢脾在台基中产下的卵,无论是滞留在特种巢脾中还是分装到产浆框中,其孵化率都一样;(2)在奖励饲喂的情况下,无论是特种巢脾上台基中的卵还是产浆框上的,其孵化率均分别极显著高于无奖励饲喂的;(3)采用本探讨技术生产蜂王浆时应将具卵产浆王台滞留在特种巢脾内孵化,并应通过奖励饲喂提高卵的孵化率.     

蛋壳资源综合开发利用

文中从禽蛋生产和蛋壳资源现状出发,论述了蛋壳资源利用的意义以及蛋壳资源的可利用方式,为蛋壳资源的综合开发利用提供指导。     

Genetic analyses of piglet survival and individual birth weight on first generation data of a selection experiment for piglet survival under outdoor conditions

Genetic parameters of piglet survival traits and birth weight were estimated on the first generation data of a selection experiment aimed at improving piglet survival using a multiple trait linear and threshold model. Data on 5293 piglets for survival at birth, at day one after birth and during the entire nursing period, as well as individual birth weight and litter size, were recorded in an outdoor production system. Genetic effects of piglet survival traits and birth weight were estimated based on threshold and Gaussian models, respectively, using a Bayesian approach. The statistical model included as fixed effects selection group, parity, gender, fostering, gestation length and month of farrowing and, alternatively, an adjustment for litter size. Direct genetic effects (i.e. the piglet's genetic potential) for piglet survival and birth weight were estimated separately, whereas maternal genetic and environmental effects could only be estimated for the given data structure in a combined litter effect. Posterior means of heritabilities for direct genetic effects of survival at birth, at first day after birth and the entire nursing period, as well as birth weight, were 0.08, 0.07, 0.08 and 0.20, respectively. Genetic correlations among survival traits were in the range of 0.29 to 0.40 and indicate that these traits were mainly attributable to different genetic effects. Genetic correlations between direct effects of survival traits and birth weight ranged between 0.18 and 0.23 and were reduced when weights of stillborn piglets were omitted in the analysis or the traits were adjusted for litter size. The magnitudes of direct genetic effects of survival traits are substantially higher than estimates in the literature, which may indicate that these traits have a higher genetic influence under outdoor conditions. The use of birth weight in the multiple trait estimation provided important information for the estimation of survival traits due to its favourable genetic correlations with survival, its high heritability and its high information content as a continuously measured trait.     

Control charts applied to simulated sow herd datasets

Statistical control charts were used to detect process change in pig production. Two charts were tested to detect small deviations in production processes: the cumulative sum (CUSUM) control chart and the exponentially weighted moving average (EWMA) control chart. A Monte-Carlo simulation was used for developing an optimal design of the EWMA and the CUSUM charts. The traits piglets born in total and the return to oestrus rate were considered. Over a given time period, small shifts were purposely implemented to test the performance of the charts. The average time to signal (ATS) and false positive rate (FPR) were taken as classification parameters to evaluate the performance of the charts. All shifts in the number of piglets born in total were detected with CUSUM and EWMA control charts. The trait piglets born in total showed an ATS ranging from 1.3 (FPR = 33.5%) to 6.8 weeks (FPR = 1.2%) using the CUSUM chart. The EWMA chart presented an ATS which ranged between 2.0 (FPR = 14.9%) and 6.3 (FPR = 1.9%) weeks. The application of the CUSUM to the return to oestrus rate resulted in an ATS of 2.6 (FPR =  38.3%) to 15.6 weeks (FPR = 3.0%) and the EWMA chart produced a signal between 4.1 (FPR = 14.5%) and 16.4 weeks (FPR = 1.4%). Both charts appear to be useful tools for tracking commercial swine farm processes and detecting emerging change in process performance.