不同饲养水平对瑶山鸡生产性能和胴体品质的影响

文章旨在研究不同饲养水平对瑶山鸡生产性能和胴体特征的影响。试验将400只平均体重一致的1日龄瑶山鸡随机分为2组,每组4个重复,每个重复50只。2组分别饲喂代谢能水平为3155 Kcal/kg、粗蛋白质水平为225 g/kg的高能高蛋白日粮和代谢能水平为2965 Kcal/kg、粗蛋白质水平为195 g/kg的低能低蛋白日粮。试验共开展10 w。同时将240只产蛋高峰期瑶山鸡随机分为2组,每组4个重复,每个重复30只,饲喂上述日粮4 w,试验结束后收集受精蛋进行孵化。结果:高能高蛋白组种鸡在8和10 w的体重和采食量均显著高于低能低蛋白组(P<0.05),而料重比显著降低(P<0.05)。高能高蛋白组种鸡受精率和孵化率显著高于低能低蛋白组(P<0.05),而残次率、胚胎死亡率和出壳前死亡率显著降低(P<0.05)。1~10 w时高能高蛋白组种鸡体重均显著高于低能低蛋白组(P<0.05),与低能低蛋白组相比,高能高蛋白组屠体重、可食用部分显著升高(P<0.05),腿肌占比显著降低(P<0.05)。结论:中等生长速度的瑶山肉种鸡可以更有效地利用高能量高蛋白(代谢能:3155 Kcal/kg,粗蛋白质:225 g/kg)饲料。     

浅析我国南方冬闲田种植一年生黑麦草的应用研究

针对我国南方地区冬闲田数量多、利用率低的现象,充分利用冬闲田种草养畜,不仅可以解决牲畜季节性青绿粗饲料缺乏问题,还能促进农民增收和农业可持续发展。一年生黑麦草由于适生范围广,鲜草产量高,营养丰富且柔嫩多汁,适口性好,家畜家禽喜欢采食,深受农户青睐,成为一种极具发展前途的越年生优质牧草,近年来在畜牧业生产中得到广泛应用。本文从一年生黑麦草生物性状、营养特性、冬闲田的丰产栽培技术、青贮技术以及在各类畜禽的饲喂研究角度进行综述,并指出今后的研究重点和方向。旨在为一年生黑麦草在畜牧业中的进一步推广应用提供参考。     

天然植物生长调节剂芸苔素的生物活性及应用浅析

天然芸苔素属于甾体类植物内源生物活性物质,其骨架为甾醇,其中芸苔素内酯生物活性最强,被称为第六类植物激素,是高效、广谱、无毒的植物生长调节剂(PGR)。为更好地将芸苔素推广应用于农业生产,本文概括了芸苔素内酯的生物活性及在粮食、果蔬等作物上的应用。探讨了芸苔素内酯在提高种子活力,促进作物生长,大幅度促进产量提升以及品质改善,提升作物抗逆性,缓解农药对作物影响的研究概况及取得的进展,指出了芸苔素内酯的应用是作物增产增收的关键途径,同时,能够减少化肥、农药的施用量,减少作物种植成本与减轻环境污染,将带来显著的经济效益。     

威宁县白萝卜优质生产技术

从播前准备、品种选择、播种方式和方法、田间管理、病虫害防治、适时收获等方面系统阐述了威宁白萝卜的优质生产技术措施，以期为广大农民朋友提供科学的技术指导和参考。     

人参皂苷和多糖对肺肠功能影响研究进展

消化和呼吸功能是畜牧养殖过程中面临的两大问题,其会严重影响畜牧业经济效益。作为人参主要功能性成分,人参总皂苷和人参多糖在肺肠功能调节方面具有较好效果。本文总结了近年来人参总皂苷和人参多糖对肺肠功能调节的研究情况,以期为其在畜牧生产应用方面提供参考。     

智慧物流在饲料企业管理中的应用研究

饲料行业的竞争日益激烈,其需要学会使用现代科技提升竞争力,智慧物流就是这些技术之一。智慧物流可以提升饲料企业对原材料和产品在物流过程中的管控。本文试图探索智慧物流如何提升饲料企业的管理。通过智慧物流,饲料企业可以改进生产管理的流程和模式,加强采购管理中的风险管理,追踪产品售后的流向和信息,提升企业的产品质量,保证企业财务数据的真实性和可靠性。     

花生壳黄酮的提取纯化工艺

本文采用酶法预处理结合超声波辅助提取的方式，最大程度地提高了花生壳总黄酮的得率，并优化大孔树脂纯化工艺，提高了有效成分的纯度。花生壳黄酮的最佳提取工艺为：花生壳粉与水混合，半纤维素酶与木聚糖酶按1:1（m/m）复配，用量0.25‰，50℃酶解30 min后，按料液比1:20（m/V）加入乙醇至终浓度60%，于功率1000 W，55℃超声波辅助提取60 min，花生壳总黄酮的得率约为2.5%。选用D101型大孔树脂，上样缓冲液为pH 5.0的60%乙醇溶液，洗脱液为pH 10.0的70% 乙醇溶液，上样与洗脱流速为0.75 BV/h和1.5 BV/h。纯化后的花生壳总黄酮和木犀草素的纯度分别为10.54%和5.85%，提高了90%和120%。     

酒糟和醋糟营养成分差异及其瘤胃降解特性分析

本试验旨在评价酒糟、醋糟等非常规饲料资源的饲用价值，为酒糟醋糟资源应用于肉牛养殖提供数据参考。试验选用山西不同地区酒糟、醋糟试样5个，试样编号分别为白酒糟、啤酒糟、醋糟1、醋糟2、醋糟3，发酵原料分别为白酒糟（高粱）、啤酒糟（大麦+大米）、醋糟1（高粱+大麦）、醋糟2（大麦+玉米）、醋糟3（高粱+玉米）。通过实验室常规方法测定样品常规营养成分以及利用体外产气法和尼龙袋法评价其饲用价值，同时建立体外法与尼龙袋法测定干物质降解率的回归方程。结果表明：5个样品的干物质（DM）含量为23.25% ~ 42.96%，粗蛋白质（CP）含量分别为啤酒糟（31.84%）>白酒糟（14.58%）>醋糟3（14.40%）>醋糟1（12.21%）>醋糟2（8.46%）。醋糟1的中性洗涤纤维（NDF）、酸性洗涤纤维（ADF）含量均为最高，其次为醋糟2、醋糟3，白酒糟NDF含量最低。啤酒糟的72 h产气量（GP72）显著高于白酒糟（P < 0.05）。体外产气法和尼龙袋法测定的酒糟72 h干物质降解率（IVDMD72、DMD72）显著高于醋糟（P < 0.05）。5个试样的IVDMD72与DMD成正相关，随着降解时间增加其相关性逐渐增加。综上，酒糟的CP含量较高（14.58% ~ 31.84%），醋糟NDF、ADF含量相对较高（59.59% ~ 64.91%，38.78% ~ 54.78%）。结合GP、IVDMD及DMD结果，酒糟消化性能优于醋糟。以IVDMD建立估算DMD的回归公式为DMD72=-19.215+1.645IVDMD72（R2=0.912，P < 0.05）|以IVDMD建立估算DM有效降解率（ED）的回归公式为ED=-12.448+1.045IVDMD72（R2=0.929，P < 0.01）。 [关键词] 醋糟|酒糟|体外产气法|尼龙袋法     

Soil quality assessments in integrated crop–livestock–forest systems: A review

Integrated crop–livestock–forest is a promising strategy to improve soil quality. It comprises four different integrated farming systems: crop–livestock, crop–forest, forest–livestock and crop–livestock–forest. This work systematically reviewed studies about integrated crop–livestock–forest systems and soil quality. A total of 92 papers were retrieved from the Web of Science—Clarivate Analytics platform, and the following information was analysed: publication year, institution, region of the studied site, type of integrated system, soil type, tillage system, maximum soil depth and the soil quality indicators assessed. Most studies were published in the second half of the 2010s. Brazil is a prominent focus of research about soil quality and integrated crop–livestock–forest systems, with significant contribution from its central and southern regions. The Embrapa was the main publishing institution, present in over one‐third of the studies. Crop–livestock was the most common integrated system, Ferralsols was the most common soil group, and most of the studied soils were clayey. No tillage was the main tillage system. Most studies focused on the topsoil, assessing physical and/or chemical soil quality indicators. More emphasis on biological indicators of soil quality is required, as well as assessments integrating biological, physical and chemical indicators of soil quality. Future works should compare different integrated systems, including assessments deeper in the soil profile, especially in systems with the forest component, and also in sandy and silty soils. Soil quality indicators that have been rarely used should be further tested. Novel indicators should be added to better understand the promotion of soil quality by integrated crop–livestock–forest systems.     

Improvement,identification, and target prediction for miRNAs in the porcine genome by using massive,public high-throughput sequencing data

Despite the broad variety of available microRNA (miRNA) research tools and methods, their application to the identification, annotation, and target prediction of miRNAs in nonmodel organisms is still limited. In this study, we collected nearly all public sRNA-seq data to improve the annotation for known miRNAs and identify novel miRNAs that have not been annotated in pigs (Sus scrofa). We newly annotated 210 mature sequences in known miRNAs and found that 43 of the known miRNA precursors were problematic due to redundant/missing annotations or incorrect sequences. We also predicted 811 novel miRNAs with high confidence, which was twice the current number of known miRNAs for pigs in miRBase. In addition, we proposed a correlation-based strategy to predict target genes for miRNAs by using a large amount of sRNA-seq and RNA-seq data. We found that the correlation-based strategy provided additional evidence of expression compared with traditional target prediction methods. The correlation-based strategy also identified the regulatory pairs that were controlled by nonbinding sites with a particular pattern, which provided abundant complementarity for studying the mechanism of miRNAs that regulate gene expression. In summary, our study improved the annotation of known miRNAs, identified a large number of novel miRNAs, and predicted target genes for all pig miRNAs by using massive public data. This large data-based strategy is also applicable for other nonmodel organisms with incomplete annotation information.