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首页> 外文学位 >Prediction of dry matter, crude protein degradability, and amino acid composition of corn silage and grass silage by near infrared reflectance spectroscopy (NIRS).
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Prediction of dry matter, crude protein degradability, and amino acid composition of corn silage and grass silage by near infrared reflectance spectroscopy (NIRS).

机译：通过近红外反射光谱法（NIRS）预测玉米青贮饲料和草料青贮饲料的干物质，粗蛋白降解性和氨基酸组成。

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摘要

This research program was designed to meet three objectives. The first was to ascertain the feasibility of using near infrared reflectance spectroscopy (NIRS) to predict ruminal degradability of dry matter (DM) and crude protein (CP) in corn silage (CS) and CP degradability in grass silage (GS) as determined by the in situ technique. The second objective was to develop calibration models to predict intestinal disappearance of DM and CP in CS and intestinal digestibility of CP in GS as determined by the mobile bag technique. The last objective was to investigate the feasibility of using LAIRS to predict the essential amino acid (AA) composition of CS and GS.; In situ data showed substantial variation in soluble and degradable DM and CP fractions as well as AA composition of CS. Based on the RPD statistic used to evaluate calibration equations, LAIRS provides a viable option for the prediction of soluble DM and CP for CS, effectively degraded CS CP and CS CP disappearance from the intestinal and total digestive tract. It was not possible to produce robust calibration equations to predict rates of CS DM or CP degradability. Further study is required to ascertain the usefulness of LAIRS in predicting AA composition of CS.; Interpretation of spectral data showed that DM solubility and degradability of CS is linked to N-H bonding. There was a strong relationship between soluble DM, potentially degradable DM and effective degradability of CS CP. A review of the major wavelengths used in each calibration model indicated that fiber did not play a major role in CS DM digestibility.; For the GS study, samples were classified according to increasing content of neutral detergent fiber (NDF) as this constituent is related to plant maturity. The content of soluble CP in GS significantly (P 0.01) decreased with increasing maturity but there was no significant difference (P > 0.05) in potentially degradable CP. Likewise the rate of degradation of the potentially degradable CP fraction did not change according to NDF content. The amount of ruminally undegradable CP from GS significantly (P 0.01) increased with advancing maturity but there was no difference in intestinal digestibility of ruminally undegradable CP according to NDF content. Likewise, there was no difference in essential AA content, expressed on a CP basis, due to stage of maturity.; Ruminally undegraded CP was inversely related to CP ruminal disappearance after 12 h and/or 24 h incubation. Pearson correlation coefficients were -0.83 and 0.86, respectively.; NIRS was not successful in predicting CP solubility or degradability fractions for GS as determined by the in situ technique. Prediction of essential AA content of GS was promising as RPD statistics for each equation, except Met and Lys, approached 2.3.; This thesis presents data for the development of several NIRS calibration models, which have not been previously explored in the scientific literature. These include models to predict intestinal digestibility as well as AA composition of forage. The concluding chapter presents recommendations for experimental methodology as well as for future research in the area of NIRS model development.
机译：该研究计划旨在满足三个目标。首先是确定使用近红外反射光谱法（NIRS）预测玉米青贮饲料（CS）中干物质（DM）和粗蛋白（CP）的瘤胃降解能力以及草青贮饲料（GS）的瘤胃降解能力的可行性，原位技术。第二个目标是开发校准模型，以预测通过手提袋技术确定的CS中DM和CP的肠道消失以及GS中CP的肠道消化率。最后一个目的是研究使用LAIRS预测CS和GS必需氨基酸（AA）组成的可行性。原位数据显示可溶性和可降解的DM和CP馏分以及CS的AA组成存在很大差异。基于用于评估校准方程式的RPD统计量，LAIRS为预测CS的可溶性DM和CP，有效降解CS CP和CS CP从肠道和总消化道的消失提供了可行的选择。不可能产生鲁棒的校准方程来预测CS DM或CP降解率。需要进一步研究以确定LAIRS在预测CS的AA组成中的有用性。光谱数据的解释表明，DM的溶解度和CS的可降解性与N-H键有关。可溶性DM，可能降解的DM和CS CP的有效降解性之间存在很强的关系。对每个校准模型中使用的主要波长的回顾表明，光纤在CS DM消化率中没有发挥主要作用。对于GS研究，根据中性洗涤剂纤维（NDF）含量的增加对样品进行分类，因为该成分与植物成熟度有关。 GS中可溶性CP的含量随着成熟度的增加而显着降低（P <0.01），但潜在可降解CP则没有显着差异（P> 0.05）。同样，可能降解的CP馏分的降解速率也不会根据NDF含量而变化。 GS的瘤胃不可降解CP的量随成熟度的增加而显着增加（P <0.01），但根据NDF含量，瘤胃不可降解CP的肠消化率没有差异。同样，由于成熟阶段的不同，以CP为基准表示的基本AA含量也没有差异。孵育12 h和/或24 h后，瘤胃未降解的CP与CP瘤胃消失呈负相关。皮尔逊相关系数分别为-0.83和0.86。 NIRS无法成功预测通过原位技术确定的GS的CP溶解度或降解率。 GS的基本AA含量的预测是有希望的，因为除Met和Lys外，每个方程的RPD统计数据均接近2.3。本文提出了用于开发多种NIRS校准模型的数据，而科学文献中以前并未对此进行探索。这些模型包括预测肠道消化率以及饲料的AA组成的模型。最后一章提出了有关实验方法学以及NIRS模型开发领域的未来研究的建议。

著录项

  • 作者

    Swift, Mary Lou.;

  • 作者单位

    The University of British Columbia (Canada).;

  • 授予单位 The University of British Columbia (Canada).;
  • 学科 Agriculture Agronomy.; Agriculture Animal Culture and Nutrition.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 127 p.
  • 总页数 127
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 农学（农艺学）;饲料;
  • 关键词

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