Determining the chemical composition of animal manure rapidly is essential to manage fertilisation and decrease environmental pollution. Near infrared (NIR) spectroscopy is a non-destructive, inexpensive and rapid method to determine several components of manure simultaneously. This study investigated the ability of NIR spectroscopy to analyse the dry matter, total and ammonium nitrogen, phosphorus, calcium, potassium and magnesium contents in a database of heterogeneous cattle and poultry solid manures. The accuracy of calibration models obtained from different sample preparation methods (dried ground vs. fresh homogenized) and multivariate regression methods (partial least squares (PLS) vs. local regression) were compared. The results showed that using local regression with NIR spectra of fresh homogenized manure could predict dry matter (R²=0.99, RMSEV = 1.64%, RPD = 13.31), total (R²=0.98, RMSEV = 0.16%, RPD = 7.11) and ammonium nitrogen (R²=0.97, RMSEV = 0.042%, RPD = 5.57) and phosphorus (R²=0.95, RMSEV = 0.10%, RPD = 5.56) contents accurately.

快速确定动物粪便的化学成分对于管理施肥和减少环境污染至关重要。近红外（NIR）光谱法是一种无损，廉价且快速的方法，可以同时测定粪便中的几种成分。这项研究调查了近红外光谱法分析异质牛和家禽固体粪便数据库中干物质，总氮和铵态氮，磷，钙，钾和镁含量的能力。比较了从不同样品制备方法（干燥地面与新鲜均质化）和多元回归方法（偏最小二乘（PLS）与局部回归）获得的校准模型的准确性。结果表明，将局部均质与NIR光谱结合使用新鲜均质肥料可以预测干物质（R² = 0.99，RMSEV = 1.64％，RPD = 13.31），总量（R ² = 0.98，RMSEV = 0.16％，RPD = 7.11）和铵态氮（R ² = 0.97，RMSEV = 0.042％，RPD = 5.57）和磷（R ² = 0.95，RMSEV = 0.10％，RPD = 5.56）含量准确。