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APPLICATION OF NEAR-INFRARED REFLECTANCE SPECTROSCOPY FOR DETERMINATION OF NUTRIENT CONTENTS IN LIQUID AND SOLID MANURES

机译:近红外反射光谱法在液体和固体肥料中营养含量测定中的应用

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Proper application of livestock manure to agricultural land converts waste to fertilizer, but relies on knowing the nutrient content of the manure. Manure samples (111 solid poultry layer, 95 solid poultry broiler litter, 39 swine solid hoop, 72 beef cattle, 85 swine slurry, and 88 swine liquid lagoon) were collected from farms in three states to investigate the feasibility and limitations for using near-infrared reflectance spectroscopy (NIRS) to analyze manure nutrients. Spectral data in the near-infrared (NIR) region (1100-2500 nm) from manure samples were correlated with chemical analytical data from the same samples using partial least squares regression techniques in conjunction with six mathematical data pretreatments. The best calibration equations were selected on the basis of the smallest standard error of prediction (SEP) and the largest coefficient of determination (R 2 ) of cross-validation. The ratio (abbreviated as RPD) of the standard deviation (SD) of the constituent in the sample population to the SEP was used to evaluate the future prediction performance of calibration models. After using the mathematical pretreatments, the R 2 values of the one-out cross-validation for total solids (TS), volatile solid (VS), total nitrogen (TN), and ammonia nitrogen (NH 3 -N) were between 0.80 and 0.97 for all manure samples. The R 2 values of the one-out cross-validation for minerals ranged from 0.71 to 0.81, 0.50 to 0.78, 0.74 to 0.94, 0.66 to 0.91, 0.73 to 0.91, and 0.70 to 0.90 in poultry solid layer, poultry broiler litter, swine solid hoop, beef cattle, swine liquid lagoon, and swine slurry manure samples, respectively. The RPD values indicate that NIRS can predict TS, VS, TN, NH 3 -N, and some minerals in manures. NIRS has potential to predict some nutrient concentrations in manure rapidly and accurately
机译:适当地将牲畜粪肥施用到农田上,会将废物转化为肥料,但要依靠了解粪肥的营养成分。从三个州的农场收集了粪便样本(111个固体家禽层,95个固体家禽肉鸡垫料,39头猪固体圈,72头肉牛,85头猪粪和88头猪粪池),以调查使用近地粪便的可行性和局限性红外反射光谱(NIRS)分析肥料中的养分。使用偏最小二乘回归技术结合六种数学数据预处理,将粪便样品的近红外(NIR)区域(1100-2500 nm)中的光谱数据与相同样品的化学分析数据相关联。根据交叉验证的最小标准预测误差(SEP)和最大确定系数(R 2 )选择最佳的校准方程式。样本总体中成分的标准偏差(SD)与SEP的比率(缩写为RPD)用于评估校准模型的未来预测性能。使用数学预处理后,对总固体(TS),挥发性固体(VS),总氮(TN)和氨氮(NH < sub> 3 -N)在所有粪便样品中都在0.80和0.97之间。家禽固体矿物质的一次性交叉验证的R 2 值范围为0.71至0.81、0.50至0.78、0.74至0.94、0.66至0.91、0.73至0.91和0.70至0.90层,家禽肉仔鸡,猪固体箍,肉牛,猪液体泻湖和猪粪便粪便样品。 RPD值表明,NIRS可以预测TS,VS,TN,NH 3 -N和肥料中的某些矿物质。 NIRS具有快速准确地预测肥料中某些养分浓度的潜力

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