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提高饲料效率的策略

来源：硕腾猪业 2022-09-14 14:07:26| 查看：次

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　　我的钢铁网数据显示，9月13日，长春、西安、昆明等地豆粕价格已冲上5000元/吨，大北农、新希望、海大、安佑等一大批饲料企业已经开启了新一轮的涨价潮，最高涨幅达150元/吨！如何提升饲料效率？降低成本？

　　标题：提高饲料效率的策略

　　Feed efficiency improvement strategies

　　对于商品猪生产，生产成本中饲料成本居首，占总成本的55-65%。

　　In commercial pig production,feed is the largest production cost component accounting for 55-65%of the total cost.

　　提高饲料效率一直是生猪选育项目的重中之重。饲料转化率（FCR）是平均日采食量（ADFI）与平均日增重（ADG）的简单比率，以往被用于选育具有饲料效率优势的猪。然而，猪的生长效率远复杂于简单的FCR，并由生长猪的生物学所驱动（https://genesus.com/feed-intake-growth-and-health/）。仅仅基于FCR进行选育，无法获得采食量和长势的优化，而这两者确是颇为重要的经济性状。

　　Improvement of feed efficiency has always been a priority in pig breeding and selection programs.The feed conversion ratio(FCR),which is a simple ratio of the average daily feed intake(ADFI)to the average daily gain(ADG),was historically used to select for feed efficiency.However,efficiency of the growing pig is more complex than simply FCR and driven by the biology of the growing pig(https://genesus.com/feed-intake-growth-and-health/).Selection placed solely on FCR will not result in optimal change in both feed intake and growth,two economically important traits.

　　采食量是生长的主要驱动因素，ADFI和ADG之间的遗传相关性相对较高（0.32–0.84）（Hoque等，2009年；Jiao等，2014年）。因此，人们普遍认为猪吃得越多，长得越快。然而采食量与长势之间的相关性并不完美（即小于1），因此找到并选育吃得少、长得快的动物是有机可乘的。长势和采食量都会显著影响盈利，但它们的经济价值不同，影响相反。与直接基于FCR的选育相比，另一种选育策略是使用选育指数，加快生长，同时限制采食量的变化。

　　Feed intake is a primary driver of growth and the genetic correlation between ADFI and ADG is relatively high(0.32–0.84)(Hoque et al.,2009;Jiao et al.,2014).Therefore,people generally thought that the pigs have to eat more to grow faster.However,the correlation between feed intake and growth is not perfect(i.e.less than 1),and thus there is an opportunity to identify and select animals having faster growth with lower feed intake.Growth rate and feed intake both significantly impact profitability,but their economic values are not the same and are weighted in opposite directions.Compared to direct selection on FCR,an alternative selection strategy is to use a selection index that improves growth rate while limiting the change of feed intake.

　　此外，饲料效率还受到瘦肉率、脂肪沉积率以及饲料能量利用率的影响（https://genesus.com/feed-intake-growth-and-health/）。ADFI和脂肪以及ADFI和腰部厚度之间存在中到高的遗传相关性（0.22-0.57）（Jiao等，2014；麦克尼尔和肯普，2015）。参考这些遗传相关性状可提高生长和采食量方面估计育种值（EBV）的准确性，从而提高饲料效率的遗传改良率。

　　In addition,feed efficiency is also affected by the rate of lean and fat deposition and energy utilization from the diet(https://genesus.com/feed-intake-growth-and-health/).Moderate to high genetic correlations between ADFI and fat and ADFI and loin depth(0.22-0.57)(Jiao et al.,2014;MacNeil&Kemp,2015)demonstrate these effects.Inclusion of these genetically correlated traits improves the accuracy of the estimated breeding values(EBV)for both growth and feed intake,and consequently increase the genetic improvement rate for feed efficiency.

　　另外，基因组信息有助于利用遗传相关性不强的性状（如ADFI和ADG）来改良上述性状。一般认为正性相关的性状有更多相同的遗传标记，但标记对性状影响不一。基因组评估和选育利用不同的标记，找到背离预期相关性的动物，从而加快定向选育。此外，收集个体动物采食数据成本非常高，限制了具有实际采食数据的动物数。利用基因组信息，即使没有采食数据，动物的EBV也会更准确，更准确的EBV能够带来更高的遗传改良率。

　　Furthermore,utilizing genomic information provides advantages for improving these traits with unfavorable genetic correlations(e.g ADFI and ADG).Positively correlated traits are expected to have more genetic markers in common however not all markers affecting the traits are the same.Genomic evaluation and selection can utilise the markers not in common to effectively identify animals that go against the expected correlation thereby driving selection more quickly in the desired direction.Further,collecting individual animal feed intake data is very costly,limiting the number of animals with actual feed intake data.Utilizing genomic information,even for animals without feed intake data will result in more accurate EBV for all animals including the ones without feed intake data.More accurate EBV results in a higher rate of genetic improvement.

　　作为一家全球猪育种公司，Genesus在基因改良项目中考虑了所有这些策略。自2004年以来，Genesus一直在收集个体采食量及多个饲料效率相关性状，包括生长率（120日龄，120kg/265lb）、超声、胴体测量获得的脂肪和腰部厚度。Genesus在基因组评估和选育研究方面大量投入，使用定制SNP（单核苷酸多态性，一种遗传标记）芯片，包含6万个以上SNP，囊括许多与饲料效率相关性状的SNP。

　　As a global pig breeding company,Genesus considers all these strategies within our genetic improvement program.Since 2004,we have been collecting individual feed intake along with multiple feed efficiency component traits,including growth rate(Day120,measured as age at 120kg/265lb),ultrasound and carcass fat and loin depths.Genesus has invested heavily in genomic evaluation and selection research and utilises a custom SNP(single nucleotide polymorphism,a kind of genetic marker)chip with>60K SNPs including many SNPs associated with feed efficiency component traits.

　　通过基因组评估多个性状模型，我们能获得ADFI和120日龄生长率准确的基因组EBV，然后在选育指数中对ADFI和120日龄生长率重点优化选择。如此，我们可选育采食量变化最小，长得更快的猪，从而提高FCR。我们杜洛克群体中ADFI和120日龄生长率的遗传趋势以及计算所得的FCR EBV如下图所示。从2017年起ADFI保持稳定，生长率持续改善（达到120kg/265lb所需天数减少），这是将两个性状都包含在选育指数中并适当强调的结果。结果也显示在生长率提高，采食量基本不变的情况下，FCR也在稳步改善。

　　Through a genomic evaluation multiple trait model,we are able to obtain accurate genomic EBV for both ADFI and Day120,then give optimal selection emphasis on ADFI and Day120 in the selection index.In this way,we can select pigs having the genetic ability for faster growth with minimal change in feed intake and thereby resulting in improved FCR.The genetic trends for ADFI and Day120 together with the calculated FCR EBV in our Duroc population are shown in the figure below.From year 2017 onward,it shows continual improvement in growth rate(fewer days to reach 120kg/265lb)while limiting the change in ADFI when both traits were included in the selection index and appropriately emphasised.The result shows that FCR has been steadily improving through increased growth and essentially unchanged feed intake.

　　原文链接：https://www.thepigsite.com/articles/feed-efficiency-improvement-strategies

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