首页> 美国卫生研究院文献>Journal of Animal Science >ASAS-NANP SYMPOSIUM: RUMINANT/NONRUMINANT FEED COMPOSITION: Challenges and opportunities associated with creating large feed composition tables
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ASAS-NANP SYMPOSIUM: RUMINANT/NONRUMINANT FEED COMPOSITION: Challenges and opportunities associated with creating large feed composition tables

机译:ASAS-NANP研讨会:反刍动物/非变化饲料组成:与创建大型饲料组成表相关的挑战和机会

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摘要

Traditional feed composition tables have been a useful tool in the field of animal nutrition throughout the last 70 yr. The objective of this paper is to discuss the challenges and opportunities associated with creating large feed ingredient composition tables. This manuscript will focus on three topics discussed during the National Animal Nutrition Program (NANP) Symposium in ruminant and nonruminant nutrition carried out at the American Society of Animal Science Annual Meeting in Austin, TX, on July 11, 2019, namely: 1) Using large datasets in feed composition tables and the importance of standard deviation in nutrient composition as well as different methods to obtain accurate standard deviation values, 2) Discussing the importance of fiber in animal nutrition and the evaluation of different methods to estimate fiber content of feeds, and 3) Description of novel feed sources, such as insects, algae, and single-cell protein, and challenges associated with the inclusion of such feeds in feed composition tables. Development of feed composition tables presents important challenges. For instance, large datasets provided by different sources tend to have errors and misclassifications. In addition, data are in different file formats, data structures, and feed classifications. Managing such large databases requires computers with high processing power and software that are also able to run automated procedures to consolidate files, to screen out outlying observations, and to detect misclassified records. Complex algorithms are necessary to identify misclassified samples and outliers aimed to obtain accurate nutrient composition values. Fiber is an important nutrient for both monogastrics and ruminants. Currently, there are several methods available to estimate the fiber content of feeds. However, many of them do not estimate fiber accurately. Total dietary fiber should be used as the standard method to estimate fiber concentrations in feeds. Finally, novel feed sources are a viable option to replace traditional feed sources from a nutritional perspective, but the large variation in nutrient composition among batches makes it difficult to provide reliable nutrient information to be tabulated. Further communication and cooperation among different stakeholders in the animal industry are required to produce reliable data on the nutrient composition to be published in feed composition tables.
机译:传统的饲料组成表是在过去70年的最近70年的动物营养领域的有用工具。本文的目的是讨论与创建大型饲料成分组成表相关的挑战和机会。本手稿将重点关注在美国动物科学年会,德克萨斯州奥斯汀的美国动物科学年度会议上进行的反刍动物和非变化营养中讨论的三个主题,即2019年7月11日,即:1)使用饲料组成表中的大型数据集和标准偏差在营养成分中的标准偏差以及获得准确标准偏差值的不同方法,2)讨论纤维在动物营养中的重要性以及对饲料纤维含量的不同方法的评价, 3)新型饲料源的描述,例如昆虫,藻类和单细胞蛋白,以及与饲料组成表中包含这种进料相关的挑战。饲料组成表的发展具有重要挑战。例如,不同来源提供的大型数据集往往具有错误和错误分类。此外,数据具有不同的文件格式,数据结构和馈送分类。管理此类大型数据库需要具有高处理电源和软件的计算机,该计算机也能够运行自动化程序来整合文件,以筛选偏远的观察,并检测错误分类的记录。需要复杂的算法以识别错误分类的样本和旨在获得准确的营养成分值的异常值。纤维是单线治和反刍动物的重要营养素。目前,有几种方法可用于估计饲料的纤维含量。然而,其中许多没有准确估计光纤。总膳食纤维应用作估计饲料中纤维浓度的标准方法。最后,新的饲料来源是从营养角度取代传统饲料来源的可行选择,但批量之间的营养成分的大变化使得难以提供可靠的营养信息。在动物行业中的不同利益攸关方之间的进一步沟通与合作需要在饲料组成表中发表的营养成分中产生可靠的数据。

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