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Effects of sample processing on ash content determination in solid cattle manure with visibleear-infrared spectroscopy.

机译:样品处理对可见/近红外光谱法测定固体牛粪中灰分含量的影响。

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摘要

Visible and near-infrared (VisNIR, 350-2500 nm) diffuse reflectance spectroscopy (DRS) may be a useful tool for determining crude ash content of solid cattle manure. However, the effect of sample preprocessing protocols on the predictive ability of the VisNIR-DRS models is unknown. In this study we explored the effects of drying and milling on the prediction of crude ash in feedyard manure using VisNIR-DRS. Samples (n=120) of beef manure from open lots were evaluated for ash content by dry oxidation and then subjected to four preprocessing treatment protocols: oven-dried and milled, air-dried and milled, oven-dried and not milled, and air-dried and not milled. Each treatment protocol was used to calibrate partial least squares regression models for prediction of ash content by VisNIR-DRS. Two thirds of the samples were randomly selected to build calibration models, and the remaining third was used for validation. The root mean squared deviation (RMSD) and the ratio of the standard deviation over the RMSD (RPD) for each treatment were assessed to determine the best pretreatment protocol for ash determination of manure. The first derivative of the reflectance from air-dried, unmilled samples consistently generated the best predictive models with an RMSD of 5% crude ash (d.b.), an RPD of 2, and a bias of 0% crude ash (d.b.).
机译:可见和近红外(VisNIR,350-2500 nm)漫反射光谱法(DRS)可能是确定固体牛粪中粗灰分含量的有用工具。但是,样品预处理协议对VisNIR-DRS模型的预测能力的影响尚不清楚。在这项研究中,我们探索了干燥和研磨对使用VisNIR-DRS预测饲料厂粪便中粗灰分的影响。通过干式氧化对露天场所的牛肉粪便样品(n = 120)进行灰分含量评估,然后进行四种预处理处理方案:烤箱干燥和碾碎,风干和碾碎,烤箱干燥而不碾碎以及空气-干而不磨。每种处理方案均用于校准偏最小二乘回归模型,以通过VisNIR-DRS预测灰分含量。随机选择三分之二的样品来建立校准模型,其余的三分之一用于验证。评估每种处理的均方根偏差(RMSD)和标准偏差与RMSD的比率(RPD),以确定灰分测定肥料的最佳预处理方案。风干未研磨样品的反射率的一阶导数始终以5%的粗灰分(d.b.)的RMSD,2的RPD和0%的粗灰分(d.b.)的偏差始终生成最佳的预测模型。

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