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Suitability of faecal near-infrared reflectance spectroscopy (NIRS) predictions for estimating gross calorific value

机译:粪便近红外反射光谱(NIRS)预测对估算总热值的适用性

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A total of 220 faecal pig and poultry samples, collected from different experimental trials were employed with the aim to demonstrate the suitability of Near Infrared Reflectance Spectroscopy (NIRS) technology for estimation of gross calorific value on faeces as output products in energy balances studies. NIR spectra from dried and grounded faeces samples were analyzed using a Foss NIRSystem 6500 instrument, scanning over the wavelength range 400-2500 nm. Validation studies for quantitative analytical models were carried out to estimate the relevance of method performance associated to reference values to obtain an appropriate, accuracy and precision. The results for prediction of gross calorific value (GCV) of NIRS calibrations obtained for individual species showed high correlation coefficients comparing chemical analysis and NIRS predictions, ranged from 0.92 to 0.97 for poultry and pig. For external validation, the ratio between the standard error of cross validation (SECV) and the standard error of prediction (SEP) varied between 0.73 and 0.86 for poultry and pig respectively, indicating a sufficiently precision of calibrations. In addition a global model to estimate GCV in both species was developed and externally validated. It showed correlation coefficients of 0.99 for calibration, 0.98 for cross-validation and 0.97 for external validation. Finally, relative uncertainty was calculated for NIRS developed prediction models with the final value when applying individual NIRS species model of 1.3% and 1.5% for NIRS global prediction. This study suggests that NIRS is a suitable and accurate method for the determination of GCV in faeces, decreasing cost, timeless and for convenient handling of unpleasant samples.
机译:为了证明能量平衡研究中作为输出产品的粪便总热值的估算,使用了来自不同实验试验的220份粪便猪和家禽样品,以证明其适用性。使用Foss NIRSystem 6500仪器分析干燥和磨碎的粪便样品的NIR光谱,在400-2500 nm的波长范围内进行扫描。进行了定量分析模型的验证研究,以评估与参考值相关的方法性能的相关性,以获得适当的准确性和精确度。单个物种的NIRS校准的总发热量(GCV)预测结果显示,与化学分析和NIRS预测相比,相关系数高,家禽和猪的相关系数在0.92至0.97之间。对于外部验证,家禽和猪的交叉验证标准误差(SECV)与预测标准误差(SEP)之间的比率分别在0.73和0.86之间变化,表明校准具有足够的精度。此外,还开发了一个全球模型来估算两个物种的GCV,并进行了外部验证。校正的相关系数为0.99,交叉验证的相关系数为0.98,外部验证的相关系数为0.97。最后,当将单独的NIRS物种模型用于NIRS全局预测时,将对NIRS开发的预测模型计算出相对不确定性,并具有最终值。这项研究表明,NIRS是测定粪便中GCV的合适且准确的方法,可降低成本,节省时间并方便处理不愉快的样品。

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