The present study explored the efficiency of quantitative analysis forthe contents of total nitrogen (TN), total phosphorus (TP) and total potassium(TK) during chicken manure composting with chrysanthemum residue in a plant fieldusing a Thermo Nicolet Antaris near-infrared reflectance spectral apparatusequipped with InGaAs detectors (Thermo Nicolet Corporation, Chicago, USA). Thesamples used in this study were collected from different positions duringcomposting and were scanned in polyethylene bags at 2 cm-1 interval from 10 000to 4 000 cm-1 with 32 co-added scans. Regression models were developed usingspectral data and reference data by partial least square (PLS). In order toenhance chemical information and reduce data systemic noise, different datapreprocessing methods such as smoothing, 1st and 2nd derivative, standard normalvariety (SNV) and multiplicative scatter correction (MSC) were tested. Theoptimum preprocessing method was selected with the lowest root mean square errorof cross-validation (RMSECV). Outliers were removed on the basis of being labeledas compositional outliers by the criteria that the predicted-actual differencefor the sample was three standard deviations from the mean difference. Accordingto the concentration gradient of each parameter, all samples were divided into acalibration set (3/4 samples) and a validation set (1/4 samples). Leave-one-outcross validation was performed to avoid over-fitting on the calibration sets.Based on the values of determination coefficient (Ｒ2) and relative predictiondeviation (RPD) in validation sets, the prediction results were evaluated asexcellent for TP and TK, and approximate for TN. Hereinto, Ｒ2 and RPD valueswere greater than 0.82 and 2.0 for TN, and greater than 0.90 and 3.0 for TP andTK, respectively.Plant-field composting