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一种利用粪便近红外反射光谱法辅助测定地中海灌木林地山羊饮食组成的方法。

A fecal near-infrared reflectance spectroscopy-aided methodology to determine goat dietary composition in a Mediterranean shrubland.

作者信息

Glasser T, Landau S, Ungar E D, Perevolotsky A, Dvash L, Muklada H, Kababya D, Walker J W

机构信息

Department of Natural Resources and Agronomy, Institute of Plant Sciences, Agricultural Research Organization-The Volcani Center, PO Box 6, Bet Dagan 50250, Israel.

出版信息

J Anim Sci. 2008 Jun;86(6):1345-56. doi: 10.2527/jas.2006-817. Epub 2008 Feb 29.

Abstract

An ecologically sound approach to the problem of brush encroachment onto Israeli rangeland might be their utilization by goats, but better knowledge of the feeding selectivity and ability of goats to thrive in encroached areas is required to devise viable production systems. Direct observation of bites could provide precise and accurate estimates of diet selection, but construction of a sufficiently large database would require too much time. The present study describes the first attempt to construct fecal near-infrared reflectance spectroscopy (NIRS) calibrations of the botanical and nutritional composition of the diet, and of the total intake of free-ranging goats, based on reference values determined with bite-count procedures. Calibration of fecal NIRS was based on 43 observations encompassing 3 goat breeds and 4 periods (spring, summer, and fall of 2004, and spring of 2005). Each observation comprised 242 min of continuous recording of the species and bite-type category selected by a single animal, on each of 2 consecutive days. The mass and chemical quality of each species and bite-type category-a total of more than 200,000 bites-were determined by using the simulated bite technique. Associated feces were scanned in the 1,100- to 2,500-nm range with a reflectance monochromator. Fecal NIRS calibrations had reasonable precision for dietary percentages of the 3 main botanical components: herbaceous vegetation (as one category; R(2) = 0.85), Phillyrea latifolia (R(2) = 0.89), and tannin-rich Pistacia lentiscus (R(2) = 0.77), with SE of cross-validation (SECV) of 7.8, 6.3, and 5.6% of DM, respectively. The R(2) values for dietary percentages of CP, NDF, IVDMD, and polyethylene glycol-binding tannins were 0.93, 0.88, 0.91, and 0.74, respectively, with SECV values of 0.9, 2.1, 4.3, and 0.9% of DM, respectively. The R(2) values for intakes of herbaceous vegetation, P. latifolia, and P. lentiscus were 0.80, 0.75, and 0.65, with SECV values of 71, 64, and 46 g of DM/d, respectively. The R(2) values for the daily nutrient intakes were below 0.60. Fecal NIRS data can be used to expand the databases of botanical and nutritional dietary composition when observed and resident animals graze simultaneously, but intakes should be calculated from fecal NIRS-predicted dietary DM composition and an independent evaluation of DMI.

摘要

利用山羊来解决以色列牧场灌木丛侵占问题可能是一种生态合理的方法,但为了设计可行的生产系统,需要更深入了解山羊在侵占地区的采食选择性和生长能力。直接观察啃咬情况可以提供饮食选择的精确估计,但构建一个足够大的数据库需要太多时间。本研究描述了首次尝试基于用啃咬计数程序确定的参考值,构建粪便近红外反射光谱(NIRS)校准模型,以分析自由放养山羊的日粮植物和营养成分以及总摄入量。粪便NIRS校准基于43次观测,涵盖3个山羊品种和4个时期(2004年春、夏、秋以及2005年春)。每次观测包括连续两天对单只动物选择的物种和啃咬类型进行242分钟的连续记录。通过模拟啃咬技术确定每个物种和啃咬类型的质量和化学品质——总共超过200,000次啃咬。相关粪便在1100至2500纳米范围内用反射单色仪进行扫描。粪便NIRS校准对于三种主要植物成分的日粮百分比具有合理的精度:草本植物(作为一个类别;R² = 0.85)、阔叶薰衣树(R² = 0.89)和富含单宁的乳香黄连木(R² = 0.77),交叉验证标准误(SECV)分别为干物质的7.8%、6.3%和5.6%。粗蛋白、中性洗涤纤维、体外干物质消化率和聚乙二醇结合单宁的日粮百分比的R²值分别为0.93、0.88、0.91和0.74,SECV值分别为干物质的0.9%、2.1%、4.3%和0.9%。草本植物、阔叶薰衣树和乳香黄连木摄入量的R²值分别为0.80、0.75和0.65,SECV值分别为71、64和46克干物质/天。每日营养摄入量的R²值低于0.60。当观察到的动物和常驻动物同时放牧时,粪便NIRS数据可用于扩展植物和营养日粮组成的数据库,但摄入量应根据粪便NIRS预测的日粮干物质组成和干物质采食量的独立评估来计算。

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