Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, 31 Fukang Road, Tianjin 300391, China; College of Engineering and Technology, Tianjin Agricultural University, 22 Jinjing Road, Tianjin 300384, China.
Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, 31 Fukang Road, Tianjin 300391, China.
Spectrochim Acta A Mol Biomol Spectrosc. 2021 Mar 15;249:119300. doi: 10.1016/j.saa.2020.119300. Epub 2020 Dec 10.
Field monitoring technology plays a vital role for returning the animal manure back to the cropland with high-efficiency and accuracy, particular in the complex rotation system of manure management in Chinese intensive farms. The comprehensive quantitative analysis models were proposed and built for determining the content of the nitrogen (N) and the phosphorus (P) through the whole chain of manure management in different dairy farms under multiple conditions. 249 manure samples were collected from 31 intensive dairy farms in Tianjin both in summer and autumn. The effect of seasons on the distribution characteristics of the N and P in the manure was analyzed. Near infrared spectra were collected and principal component analysis (PCA) was performed. Partial least squares (PLS) was used to establish the intra-season and inter-season models. It was found that the contents of the N and P in the manure varied with seasons. The prediction performance of intra-season models was better than that of inter-season models. Fusion model of two seasons were also established. The coefficient of determination of external validation (R) for the N and P were 0.972 and 0.901, respectively. The residual predictive deviations (RPD) were 5.98 and 3.18, respectively. The results showed that the fusion model could enhance the universality and stability for predicting the N and P contents through the whole chain of manure management under the influence of various factors. The study not only supports for the development of on-spot detecting instrument but also guides for the rational recycling of manure in practice as well.
田间监测技术对于高效、准确地将动物粪便还田具有重要作用，特别是在中国集约化养殖场复杂的粪污管理轮作体系中。针对不同奶牛场在多种条件下粪污管理全链条，提出并建立了综合定量分析模型，用于确定氮（N）和磷（P）含量。在夏季和秋季，从天津 31 个集约化奶牛场采集了 249 个粪便样本。分析了季节对粪污中 N 和 P 分布特征的影响。采集了近红外光谱并进行了主成分分析（PCA）。采用偏最小二乘法（PLS）建立了季节内和季节间模型。结果表明，粪污中 N 和 P 的含量随季节而变化。季节内模型的预测性能优于季节间模型。还建立了两个季节的融合模型。N 和 P 的外部验证（R）的决定系数分别为 0.972 和 0.901，预测偏差分别为 5.98 和 3.18。结果表明，融合模型可以增强在各种因素影响下粪污管理全链条中预测 N 和 P 含量的通用性和稳定性。该研究不仅为现场检测仪器的开发提供了支持，也为实际中粪污的合理回收提供了指导。
