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Application of NIRS fecal profiling and geostatistics to predict diet quality of African livestock.

机译:应用NIRS粪便分析和地统计学来预测非洲牲畜的饮食质量。

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摘要

Near infrared reflectance spectroscopy (NIRS) and geostatistical techniques were used to predict diet quality of sub-Saharan African (SSA) livestock, and to create cokriged estimated diet quality maps for cattle across a landscape. Rations of native vegetation were stall-fed to cattle (Bos indicus ), sheep (Ovis aries), and goats (Capra hircus) to generate diet-fecal pair data. Trials were conducted in Ethiopia, Kenya, Uganda, Tanzania, and Ghana. Historical data from Ethiopia, Nigeria, and Niger were included. Diet samples were analyzed for crude protein (CP%), and digestible organic matter (DOM%), while feces were scanned for NIR spectra. NIRS equations were developed from data using modified partial least square (MPLS) regression. Coefficients of determination (R2) of CP for cattle, sheep, and goats were 0.92, 0.95, and 0.97, with corresponding standard errors of calibration (SEC) being 0.90, 0.79, and 0.80, respectively. Standard errors of cross validation (SECV) for CP were 1.12%, 1.08%, and 1.03% for cattle, sheep, and goats, respectively. R2 and SEC values for DOM were 0.88, 0.94, 0.94 and 2.82%, 1.68%, and 2.65%, for cattle, sheep, and goats, respectively. Corresponding SECV values for DOM were 3.26%, 2.07%, and 3.30%, respectively. The statistics reported were within the acceptable limits for NIRS calibrations. The results indicate that dietary CP and DOM of free-ranging SSA livestock can be predicted with the same precision as that of conventional wet chemistry methods.;The cattle equation was used to predict cattle fecal samples collected, from February to August 2000, from selected households located within the northern Ghana savanna. The predicted CP% and DOM% were used with Normalized Differential Vegetation Index (NDVI) data, and cokriging technique to create diet quality maps for March and July 2000 for the northern Ghana savanna. Cross validation results indicated a moderate capability of cokriging to estimate predicted CP% for March (r2 = 0.687, SEp = 1.736) and July (r2 = 0.513, SEp = 1.558). Cokriged-estimated DOM value for July was above average (r2 = 0.584, SEp = 3.611), while March DOM% estimation was rather poor (r2 = 0.132, SEp = 3.891). The techniques of cokriging and creation of diet quality maps were moderately successful in this study.
机译:近红外反射光谱法(NIRS)和地统计学技术用于预测撒哈拉以南非洲(SSA)牲畜的饮食质量,并为整个景观的牛创建经联合估计的饮食质量图。将原始植被的定食饲喂给牛(Bos indicus),绵羊(Ovis aries)和山羊(Capra hircus)以生成饮食-粪便对数据。在埃塞俄比亚,肯尼亚,乌干达,坦桑尼亚和加纳进行了试验。包括埃塞俄比亚,尼日利亚和尼日尔的历史数据。分析饮食样品中的粗蛋白(CP%)和可消化的有机物(DOM%),同时对粪便进行NIR光谱扫描。使用修正的偏最小二乘(MPLS)回归从数据中开发出NIRS方程。牛,羊和山羊的CP的测定系数(R2)为0.92、0.95和0.97,相应的标准校正误差(SEC)分别为0.90、0.79和0.80。 CP的交叉验证标准误差(SECV)对于牛,绵羊和山羊分别为1.12%,1.08%和1.03%。牛,绵羊和山羊的DOM的R2和SEC值分别为0.88、0.94、0.94和2.82%,1.68%和2.65%。 DOM的相应SECV值分别为3.26%,2.07%和3.30%。报告的统计数据在NIRS校准的可接受范围内。结果表明,与常规湿化学方法相比,可以对自由放养的SSA牲畜的日粮CP和DOM进行预测。位于加纳北部大草原内的家庭。预测的CP%和DOM%与标准化差分植被指数(NDVI)数据和协同克里金法一起用于创建加纳北部大草原2000年3月和2000年7月的饮食质量图。交叉验证结果表明,协同估计的能力中等,可以估算3月(r2 = 0.687,SEp = 1.736)和7月(r2 = 0.513,SEp = 1.558)的预测CP%。 7月的Cokriged估算DOM值高于平均值(r2 = 0.584,SEp = 3.611),而3月DOM%估算则很差(r2 = 0.132,SEp = 3.891)。 cokriging和饮食质量图的创建技术在这项研究中取得了一定的成功。

著录项

  • 作者

    Awuma, Kosi Semebia.;

  • 作者单位

    Texas A&M University.;

  • 授予单位 Texas A&M University.;
  • 学科 Range management.;Animal sciences.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 176 p.
  • 总页数 176
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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