提高猪饲料效率的测定与选择

为提高猪饲料效率的选择,本试验测定一些与猪饲料效率相关的生产性状并进行遗传评估。方法：测定60头军牧1号白猪后备公猪的采食量、体增重、背膘厚等生产性状,用猪剩余采食量（RFI）和饲料转化率（FCR）作为评价饲料效率的两个指标,并对其遗传参数进行评估。结果：测定期内军牧1号公猪群体FCR均值为2．61,RFI的标准差为77．52。RFI与FCR的遗传力分别是0．35、0．33,RFI与ADFI（日采食量）、ADG（日增重）、BF（背膘厚）的遗传相关分别是0．89、0．12、-0．05,FCR与ADFI、ADG、BF的遗传相关分别是0．55、-0．65、-0．11。结论：军牧1号白猪品种内饲料效率存在较大的遗传差异,由于RFI与ADG遗传相关很低,因此用RFI作为选择性状可有效提高猪的饲料效率。     

5种模型估算杜洛克猪的剩余采食量及与饲料效率等指标的相关分析

使用SPSS软件统计分析2017—2019年在农业农村部种猪质量监督检验测试中心(广州)集中测定的359头杜洛克种猪生长性能测定成绩,通过5种模型估算杜洛克猪剩余采食量(RFI)与饲料效率、背膘厚、眼肌面积、日增重等生长指标的相关性,根据RFI高低分组进行了相关分析。发现5种模型估算的RFI均与饲料效率有极显著相关(P<0.01),都可用来估测杜洛克种猪饲料效率;5种模型的RFI与背膘厚、眼肌面积的关系表现出两种相反的趋势:a、b、d、e模型中,低RFI组背膘更厚;c模型中,低RFI组背膘更薄,所以可能低RFI组瘦肉率更低。同时c、d、e模型低RFI组表现出与生长速度更慢(P<0.05)、c、d模型低RFI组表现出日增重更低的趋势(P<0.05)。其呈现的规律提示可能低RFI杜洛克猪虽然饲料效率较好,但生长会更慢、瘦肉率会更低。所以选择RFI模型估算杜洛克种猪瘦肉率、生长速度相关指标时,需要考虑更多生产实际需求。     

Effects of feeding level on efficiency of high- and low-residual feed intake beef steers

Comparing heat production after ad libitum (ADLIB) and restricted (RESTRICT) feeding periods may offer insight into how residual feed intake (RFI) groups change their energy requirements based on previous feeding levels. In this study, the authors sought to explain the efficiency changes of high- and low-RFI steers after feed restriction. To determine RFI classification, 56 Angus-cross steers with initial body weight (BW) of 350 ± 28.7 kg were individually housed, offered ad libitum access to a total mixed ration, and daily intakes were recorded for 56 d. RFI was defined as the residual of the regression of dry matter intake on mid-test BW^0.75 and average daily gain. High- and low-RFI groups were defined as >0.5 SD above or below the mean of zero, respectively. Fourteen steers from each high and low groups (n = 28) were selected for the subsequent 56-d RESTRICT period. During the RESTRICT period, intake was restricted to 75% of previous ad libitum intake on a BW^0.75 basis, and all other conditions remained constant. After the RESTRICT period, both RFI groups had decreased maintenance energy requirements. However, the low-RFI group decreased maintenance energy requirements by 32% on a BW^0.75 basis, more (P < 0.05) than the high-RFI group decreased maintenance requirements (18%). Thus, the low-RFI steers remained more efficient after a period of feed restriction. We conclude that feed restriction decreases maintenance energy requirement in both high- and low-RFI groups that are restricted to the same degree.     

Genetic variability in the feeding behavior of crossbred growing cattle and associations with performance and feed efficiency

The objectives of the present study were to estimate genetic parameters for several feeding behavior traits in growing cattle, as well as the genetic associations among and between feeding behavior and both performance and feed efficiency traits. An additional objective was to investigate the use of feeding behavior traits as predictors of genetic merit for feed intake. Feed intake and live-weight data on 6,088 growing cattle were used of which 4,672 had ultrasound data and 1,548 had feeding behavior data. Feeding behavior traits were defined based on individual feed events or meal events (where individual feed events were grouped into meals). Univariate and bivariate animal linear mixed models were used to estimate (co)variance components. Heritability estimates (± SE) for the feeding behavior traits ranged from 0.19 ± 0.08 for meals per day to 0.61 ± 0.10 for feeding time per day. The coefficient of genetic variation per trait varied from 5% for meals per day to 22% for the duration of each feed event. Genetically heavier cattle, those with a higher daily energy intake (MEI), or those that grew faster had a faster feeding rate, as well as a greater energy intake per feed event and per meal. Better daily feed efficiency (i.e., lower residual energy intake) was genetically associated with both a shorter feeding time per day and shorter meal time per day. In a validation population of 321 steers and heifers, the ability of estimated breeding values (EBV) for MEI to predict (adjusted) phenotypic MEI was demonstrated; EBVs for MEI were estimated using multi-trait models with different sets of predictor traits such as liveweight and/or feeding behaviors. The correlation (± SE) between phenotypic MEI and EBV for MEI marginally improved (P < 0.001) from 0.64 ± 0.03 to 0.68 ± 0.03 when feeding behavior phenotypes from the validation population were included in a genetic evaluation that already included phenotypic mid-test metabolic live-weight from the validation population. This is one of the largest studies demonstrating that significant exploitable genetic variation exists in the feeding behavior of young crossbred growing cattle; such feeding behavior traits are also genetically correlated with several performance and feed efficiency metrics. Nonetheless, there was only a marginal benefit to the inclusion of time-related feeding behavior phenotypes in a genetic evaluation for MEI to improve the precision of the EBVs for this trait.     

肉牛剩余采食量的概念和实践应用

剩余采食量(RFI)是实际采食量与预测采食量的差值,是衡量肉牛饲料效率的新指标。文章简要介绍了RFI的概念、测定方法、应用RFI的益处,以及影响肉牛RFI的一些生理因素,包括采食量、消化率、体组织代谢、活动量、体温调节等。最后,文章讨论了RFI在肉牛生产实践中的应用。     

Genetic parameters for production traits and measures of residual feed intake in Duroc and Landrace pigs

Data on 380 Duroc boars from seven generations, and 1026 Landrace pigs (341 boars and 685 gilts) from six generations were used to estimate genetic parameters for daily gain (DG), backfat thickness (BF), metabolic weight (MWT), daily feed intake (FI), feed conversion ratio (FCR) and residual feed intake (RFI). Two measures of RFI were estimated as the difference between actual feed intake and that predicted from models that included initial test age and weight and DG (RFI1); and initial test age and weight, DG and BF (RFI2). Heritability estimates for DG, MWT and FI were moderate for both breeds. BF estimates were high for both the breeds. The measures of feed efficiency (FCR and RFI) were moderately heritable. Genetic correlations of BF with measures of RFI were stronger when BF was not included in the estimation of RFI (0.40 and 0.46 for Duroc and Landrace, respectively (for RFI1), compared with 0.05 and 0.06 for Duroc and Landrace, respectively (for RFI2)). Genetic correlations of MWT with measures of RFI were all negative and low. Genetic and phenotypic correlations between DG and measures of RFI were close to zero, which indicated that selection for reduced RFI could be made without adversely affecting DG. BF should also decrease, and MWT should increase under selection for reduced RFI. The reduction in BF would depend on the measure of RFI used.     

Improving production efficiency in the presence of genotype by environment interactions in pig genomic selection breeding programmes

We simulated a genomic selection pig breeding schemes containing nucleus and production herds to improve feed efficiency of production pigs that were cross‐breed. Elite nucleus herds had access to high‐quality feed, and production herds were fed low‐quality feed. Feed efficiency in the nucleus herds had a heritability of 0.3 and 0.25 in the production herds. It was assumed the genetic relationships between feed efficiency in the nucleus and production were low (r_g = 0.2), medium (r_g = 0.5) and high (r_g = 0.8). In our alternative breeding schemes, different proportion of production animals were recorded for feed efficiency and genotyped with high‐density panel of genetic markers. Genomic breeding value of the selection candidates for feed efficiency was estimated based on three different approaches. In one approach, genomic breeding value was estimated including nucleus animals in the reference population. In the second approach, the reference population was containing a mixture of nucleus and production animals. In the third approach, the reference population was only consisting of production herds. Using a mixture reference population, we generated 40–115% more genetic gain in the production environment as compared to only using nucleus reference population that were fed high‐quality feed sources when the production animals were offspring of the nucleus animals. When the production animals were grand offspring of the nucleus animals, 43–104% more genetic gain was generated. Similarly, a higher genetic gain generated in the production environment when mixed reference population was used as compared to only using production animals. This was up to 19 and 14% when the production animals were offspring and grand offspring of nucleus animals, respectively. Therefore, in genomic selection pig breeding programmes, feed efficiency traits could be improved by properly designing the reference population.     

Improvement in feed efficiency and reduction in nutrient loading from rainbow trout farms: the role of selective breeding

Resource efficiency, the ratio of inputs to outputs, is essential for both the economic and environmental performance of any sector of food production. This study quantified the advancement in the feed conversion ratio (FCR) and reduction in nutrient loading from rainbow trout farming in Finland and the degree to which genetic improvements made by a national breeding program have contributed to this advancement. The study combined two datasets. One included annual records on farm-level performance of commercial rainbow trout farms from 1980 onwards, and the other included individuals across eight generations of the national breeding program. The data from the commercial farms showed that from 1980 onwards, the farm-level feed conversion ratio improved by 53.4%, and the specific nitrogen and phosphorus loading from the farms decreased by over 70%. Hence, to produce 1 kg of fish today, only half of the feed is needed compared to the 1980s. The first generation of the breeding program was established in 1992. The FCR was not directly selected for, and hence, the genetic improvement in the FCR is a correlated genetic change in response to the selection for growth and body composition. Since 1992, the estimated genetic improvement in the FCR has been 1.74% per generation, resulting in a cumulative genetic improvement of 11.6% in eight generations. Genetic improvement in the FCR is estimated to be 32.6% of the total improvement in the FCR observed at farms, implying that genetic improvement is a significant contributor to resource efficiency. The use of genetically improved rainbow trout, instead of the base population of fish, reduces feed costs by 18.3% and total production costs by 7.8% at commercial farms (by −0.266€ per kg of ungutted fish). For phosphorus and nitrogen, it can be assumed that the use of fish material with an improved FCR also leads to 18.3% less nitrogen and phosphorus flowing into an aquatic environment. Such improvements in resource efficiency are win–wins for both industry and the environment—the same amount of seafood can be produced with significantly reduced amounts of raw materials and reduced environmental impact.     

Selection for feed efficiency does not change the selection for growth and carcass traits in Nellore cattle

The objectives were to conduct a genetic evaluation of residual feed intake (RFI) and residual feed intake adjusted for fat (RFIFat) and to analyse the effect of selection for these traits on growth, carcass and reproductive traits. Data from 945 Nellore bulls in seven feed efficiency tests in a feedlot were analysed. Genetic evaluation was performed using an animal model in which the feed efficiency test and age of the animal at the beginning of the test were considered as a systematic effect. Direct additive genetic and residual effects were considered as random effects. Correlations and genetic gains were estimated by two‐trait analysis between feed efficiency measures (RFI and RFIFat) and other traits. Feed conversion showed low heritability (0.06), but dry matter intake (DMI), average daily gain, RFI, RFIFat, metabolic body weight and scrotal circumference measured at 450 days of age (SC450) showed moderate to high heritability (0.49, 0.28, 0.33, 0.36, 0.38 and 0.80, respectively). Similarly, ribeye area, backfat thickness, rump cap fat thickness, marbling score and subcutaneous fat thickness also had high heritability values (0.46, 0.37, 0.57, 0.51 and 0.47, respectively). Genetic correlations between RFI and SC450 were null, and between RFIFat and SC450 were strongly positive. Genetic and phenotypic correlations of RFI and RFIFat with carcass traits were not different from zero, as correlated responses for carcass traits were also not different from zero. The Nellore selection for feed efficiency by RFI or RFIFat allows the recognition of feed efficient animals, with DMI reduction and without significant changes in growth and carcass traits. However, because of the observed results between RFIFat and SC450, selection of animals should be analysed with caution and a preselection for reproductive traits is necessary to avoid reproductive impairments in the herd.     

Longitudinal analysis of body weight and average daily feed intake during the feedlot test period in Angus cattle

The objectives of this study were to compare different models for analysing body weight (BW) and average daily feed intake (ADFI) data collected during a 70-day feedlot test period and to explore whether genetic parameters change over time to evaluate the implications of selection response. (Co)variance components were estimated using repeatability and random regression models in 2,071 Angus steers. Models included fixed effects of contemporary group, defined as herd–year–observation_date–age, with additive genetic and permanent environmental components as random effects. Models were assessed based on the log likelihood, Akaike's information criterion and the Bayesian information criterion. For both traits, random regression models (RRMs) presented a better fit, indicating that genetic parameters change over the test period. Using a two-trait RRM, the heritability from day 1 up to day 70 for BW increased from 0.40 to 0.50, while for ADFI, it decreased from 0.44 to 0.33. The genetic correlation increased from 0.53 at day 1 up to 0.79 at day 70. Selection based on an index assuming no change in genetic parameters would yield a 2.78%–3.13% lower selection response compared to an index using parameters estimated with RRMs and assuming these genetic parameters are correct. Results imply that it may be beneficial to implement RRMs to account for the change of parameters across the feedlot period in feed efficiency traits.     

数字经济背景下饲料企业人力资源管理提质增效的策略探析

随着经济和技术发展水平不断攀升,世界进入数字化转型的新阶段,在此背景下,数字经济发展成为未来经济发展的主要趋势.数字经济背景下,大数据、云计算等技术发挥着关键的作用,这些技术不仅在企业管理、生产经营活动方面有重要促进作用,人力资源管理也深受影响.因此,人力资源管理进行数字化转型十分必要.我国饲料企业人力资源管理是提升企...     

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.     

基于生命周期评价的相同食物当量玉米与紫花苜蓿生产环境影响比较研究

为了探讨种植业结构调整对于我国环境的影响,本研究运用生命周期评价方法,计算了甘肃省民勤县农户水平2014与2015年从农资生产到农户入仓范围生产1 kg玉米籽粒及1 kg紫花苜蓿鲜草的环境影响,并使用基于蛋白质和热量的计量单位—食物当量(FEU),比较分析了1个FEU玉米籽粒和紫花苜蓿生产的全生命周期环境影响差异。结果表明,生产1 kg玉米籽粒和1 kg紫花苜蓿鲜草全生命周期的一次性能源消耗(PED)分别为9.35和1.22 MJ,水资源消耗(WU)分别为889.33和144.37 kg,矿物和化石资源消耗(DAR)分别为0.13和0.02 kg antimony-eq,气候变化潜值(GWP)分别为1.21和0.10 kg CO₂-eq,可吸入无机物(RI)分别为4.23×10^-3和1.88×10^-4 kg PM_2.5-eq,光化学臭氧合成(POFP)分别为2.41×10^-3和1.71×10^-4 kg NMVOC-eq,环境酸化潜值(AP)分别为8.55×10^-3和8.03×10^-4 kg SO₂-eq,淡水富营养化(FEP)分别为1.20和0.09 kg P-eq,生态毒性(ecotoxicity)分别为1.26×10^-2和1.49×10^-3 CTU。1个FEU紫花苜蓿生产的PED、WU、DAR、GWP、RI、POFP、AP、FEP和ecotoxicity则分别为玉米籽粒的20.50%、25.43%、21.08%、12.99%、6.98%、11.15%、14.76%、12.31%和18.58%。因而考虑到苜蓿的食物-经济比较优势,目前应给予其不少于粮食作物的种植补贴。并且如果将我国的部分玉米种植改为苜蓿种植,则是最便捷、经济的既能满足我国食物结构需求,又能减少农业生产的资源消耗与环境污染的措施。本研究同时也为在我国深入开展粮改饲提供了一定的立论基础。     

Structural equation models to disentangle the biological relationship between microbiota and complex traits: Methane production in dairy cattle as a case of study

The advent of metagenomics in animal breeding poses the challenge of statistically modelling the relationship between the microbiome, the host genetics and relevant complex traits. A set of structural equation models (SEMs) of a recursive type within a Markov chain Monte Carlo (MCMC) framework was proposed here to jointly analyse the host–metagenome–phenotype relationship. A non-recursive bivariate model was set as benchmark to compare the recursive model. The relative abundance of rumen microbes (RA), methane concentration (CH₄) and the host genetics was used as a case of study. Data were from 337 Holstein cows from 12 herds in the north and north-west of Spain. Microbial composition from each cow was obtained from whole metagenome sequencing of ruminal content samples using a MinION device from Oxford Nanopore Technologies. Methane concentration was measured with Guardian^® NG infrared gas monitor from Edinburgh Sensors during cow's visits to the milking automated system. A quarterly average from the methane eructation peaks for each cow was computed and used as phenotype for CH₄. Heritability of CH₄ was estimated at 0.12 ± 0.01 in both the recursive and bivariate models. Likewise, heritability estimates for the relative abundance of the taxa overlapped between models and ranged between 0.08 and 0.48. Genetic correlations between the microbial composition and CH₄ ranged from −0.76 to 0.65 in the non-recursive bivariate model and from −0.68 to 0.69 in the recursive model. Regardless of the statistical model used, positive genetic correlations with methane were estimated consistently for the seven genera pertaining to the Ciliophora phylum, as well as for those genera belonging to the Euryarchaeota (Methanobrevibacter sp.), Chytridiomycota (Neocallimastix sp.) and Fibrobacteres (Fibrobacter sp.) phyla. These results suggest that rumen's whole metagenome recursively regulates methane emissions in dairy cows and that both CH₄ and the microbiota compositions are partially controlled by the host genotype.     

基于改进的CASA模型模拟草原综合顺序分类体系各类的最大光能利用率

植被最大光能利用率是净初级生产力(NPP)估算的一个重要参数,对它的大小一直存在争议。利用遥感数据、气象数据和中国区域NPP实测资料,依据基于草原综合顺序分类(CSCS)改进的CASA模型,采用改进的最小二乘法对中国41类草地的最大光能利用率(εmax)进行了模拟,并通过与他人估算的光能利用率(ε)进行比较来验证εmax的可靠性和准确性。结果表明:此次研究的ε值略高于其他的研究结果。其主要原因有:ε最大值和最小值之间的跨度较大,从而使得平均值较高;由于缺乏实测数据,个别草地类型的ε估算值较高,导致了本研究ε值偏高;各研究采用的分类体系不同,模型和数据来源不同,从而导致结果存在差异。本研究中的εmax根据实测数据模拟得到,今后需进一步收集实测数据,对参数εmax的合理取值进行调整。