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对卡罗来纳柳(Salix caroliniana)的营养成分和缩合单宁浓度进行近红外反射光谱(NIRS)分析。

Near infrared reflectance spectroscopy (NIRS) analyses of nutrient composition and condensed tannin concentrations in carolina willow (Salix caroliniana).

作者信息

Lavin Shana R, Sullivan Kathleen E, Wooley Stuart C, Stone Koni, Russell Scott, Valdes Eduardo V

机构信息

Disney's Animal Kingdom, Lake Buena Vista, Florida.

University of Florida, Gainesville, Florida.

出版信息

Zoo Biol. 2015 Nov;34(6):576-82. doi: 10.1002/zoo.21240. Epub 2015 Aug 28.

Abstract

Iron overload disorder has been described in a number of zoo-managed species, and it has been recommended to increase the tannin composition of the diet as a safe way to minimize iron absorption in these iron-sensitive species. The goal of this study was to examine the potential of near infrared reflectance spectroscopy (NIRS) as a rapid and simple screening tool to assess willow (Salix caroliniana) nutrient composition (crude protein: CP; acid detergent fiber: ADF; neutral detergent fiber: NDF; lignin, gross energy: GE) and condensed tannin (CT) concentrations. Calibration equations were developed by regression of the lab values from 2 years using partial least squares on n = 144 NIRS spectra to predict n = 20 independent validation samples. Using the full 2-year dataset, good prediction statistics were obtained for CP, ADF, NDF, and GE in plant leaves and stems (r(2 ) > 0.75). NIRS did not predict lignin concentrations reliably (leaves r(2)  = 0.52, stems r(2)  = 0.33); however, CTs were predicted moderately well (leaves r(2)  = 0.72, stems r(2)  = 0.67). These data indicate that NIRS can be used to quantify several key nutrients in willow leaves and stems including concentrations of plant secondary compounds which, depending on the bioactivity of the compound, may be targeted to feed iron-sensitive browsing animals.

摘要

铁过载疾病已在多种动物园管理的物种中有所描述,有人建议增加日粮中的单宁成分,作为一种安全的方法,以尽量减少这些对铁敏感的物种对铁的吸收。本研究的目的是检验近红外反射光谱法(NIRS)作为一种快速简便的筛选工具,用于评估柳树(卡罗来纳柳)营养成分(粗蛋白:CP;酸性洗涤纤维:ADF;中性洗涤纤维:NDF;木质素、总能:GE)和缩合单宁(CT)浓度的潜力。通过对2年的实验室值进行回归分析,使用偏最小二乘法对n = 144个NIRS光谱进行分析,以预测n = 20个独立验证样本,从而建立校准方程。使用完整的2年数据集,对植物叶片和茎中的CP、ADF、NDF和GE获得了良好的预测统计结果(r(2) > 0.75)。NIRS不能可靠地预测木质素浓度(叶片r(2) = 0.52,茎r(2) = 0.33);然而,CT的预测效果中等(叶片r(2) = 0.72,茎r(2) = 0.67)。这些数据表明,NIRS可用于量化柳叶和柳茎中的几种关键营养素,包括植物次生化合物的浓度,根据化合物的生物活性,这些化合物可能被用作对铁敏感的食草动物的饲料。

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