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Near infrared spectroscopy (NIRS) calibration equations to predict nutritional quality parameters of tropical forages

机译:近红外光谱(NIRS)校准方程可预测热带牧草的营养品质参数

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The objective of this study was to develop NIRS calibration curves to predict nutritional quality parameters of tropical forage species. For this a total of 1,991 samples of tropical forages (grasses and legumes) were employed. These samples showed a high heterogeneity in regrowth age, vegetative state and parts of the plants collected, sampling period and sample origin. Chemical analysis was performed to determine crude protein, neutral detergent fiber, acid detergent fiber (ADF), in vitro digestibility of dry matter and digestibility of neutral detergent fiber. A group of samples was used for each chemical parameter to develop the calibration curves. The curves were chosen taking into account the standard errors of: calibration; cross validation (SECV); and prediction. To evaluate the accuracy of each equation the coefficient of determination (R 2 ) and the RPD (ratio performance deviation) index (relation between standard deviation and SECV), which assesses the predictive power of the equations, were calculated. Validation was performed with external samples and results showed correlation coefficients (r) of 0.90 for all parameters except for ADF (r=0.72), demonstrating the precision of the predictive equations. However, the determination of ADF by this analytical method requires further work to increase its reliability. Keywords: Analytical methods, animal nutrition, forage quality, grasses, legumes. DOI: 10.17138/TGFT(4)139-145
机译:这项研究的目的是开发NIRS校准曲线,以预测热带饲草物种的营养质量参数。为此,总共使用了1,991个热带草料(草和豆类)样本。这些样品在再生年龄,植物的营养状态和部分植物,采样时间和样品来源方面显示出高度的异质性。进行化学分析以确定粗蛋白,中性洗涤剂纤维,酸性洗涤剂纤维(ADF),干物质的体外消化率和中性洗涤剂纤维的消化率。一组样品用于每个化学参数以绘制校准曲线。选择曲线时要考虑以下标准误差:校准;交叉验证(SECV);和预测。为了评估每个方程的准确性,计算了确定系数(R 2)和RPD(比率性能偏差)指数(标准偏差与SECV之间的关系),该指数评估了方程的预测能力。使用外部样本进行了验证,结果表明,除ADF外,所有参数的相关系数(r)> 0.90(r = 0.72),证明了预测方程的精度。但是,通过这种分析方法测定ADF需要进一步的工作以提高其可靠性。关键词:分析方法,动物营养,饲料质量,草,豆类。 DOI:10.17138 / TGFT(4)139-145

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