Abstract: Returning to the field was the optimal way out for the great deal of slurry from dairy farms in China at the moment. Nitrogen and phosphorus were important nutrient measurable indicators. Variation in nitrogen and phosphorus content was influenced by many natural factors involved in temperature, wind speed, and rainfall so that it was hard to quickly and accurately quantify, leading to the difficulty of returning the slurry to the field. Therefore, aimed at learning the influence of typical seasonal factors on the variation of nitrogen and phosphorus contents in the slurry of large-scale dairy farms together with the prediction results of near-infrared spectroscopy models, it was significantly meaningful that provide the basis of setting up the testing method and standard system for guiding them safely and scientifically returning the slurry to the field. 250 slurry samples were gathered in the whole process of slurry treatment from 27 large-scale dairy farms in Tianjin both in spring and autumn. The influence of season on the distribution characteristics of chemical values of nitrogen and phosphorus in the slurry was analyzed, meanwhile the near-infrared spectra of the whole samples were collected and subjected to the principal component analysis. Then the Partial Least Squares (PLS) was used to establish the seasonal models that involved the spring model, autumn model, and mixed model of both, as well as the demi-season models for the quantified analysis of the nitrogen and phosphorus contents in the slurry. The results showed that the nitrogen and phosphorus contents of the samples appeared varying degrees of variability with seasonal changes. In the seasonal models, the Root Mean Squared Error of prediction set (RMSEP) of three Total Nitrogen (TN) models was 338.26, 334.23, and 382.29 mg/L, respectively. The correlation coefficients of calibration set (Rp) was 0.98, 0.94, and 0.96, respectively. The Residual Predictive Deviations (RPD) was 4.67, 2.83, and 3.56, respectively. RMSEP of three Total Phosphorus (TP) models was 20.04, 22.73, and 23.51 mg/L, respectively. Rp was 0.90, 0.81 and 0.83, respectively. RPD was 2.03, 1.68, and 1.80, respectively. As a whole, the spring model showed a better result than the autumn model, which highlighted the effect of seasonal influence on the prediction. RMSEP of two TN models for mutual prediction between spring and autumn was 934.57 and 845.82 mg/L, respectively. Rp was 0.97 and 0.92, respectively. RPD was 2.28 and 2.58, respectively. RMSEP of two TP models for mutual prediction between spring and autumn was 50.06 and 24.81 mg/L, respectively. Rp was 0.84 and 0.48, respectively. RPD was 0.94 and 1.64, respectively. The overall effect of the demi-season model was inferior compared to the seasonal models. And the performance of the demi-season model was too poor to be used for the determination of nitrogen and phosphorus content in the slurry. In summary, the interior seasonal model of nitrogen and phosphorus in the slurry was superior to the demi-season model and the prediction results of the nitrogen and phosphorus model in the slurry were influenced by the seasonal factors. All the results indicated that the nitrogen and phosphorus contents of slurry were influenced by the seasons. Further objective would be designed to establish the comprehensive forecast models with overall seasonal elements to enhance the feasibility and stability of models that providing the technical support for the development of portable measurement facilities, breaking through the dilemma of quantified analysis under the complicated situation in numerous intensive dairy farms, leading to the slurry recycling back to the field in safely and scientifically meanwhile controlling over the environmental pollution risk.