Excretion of urinary nitrogen (N) from cattle is the main source of N leaching loss from grazed pasture systems. The purpose of this study was to evaluate the suitability of non-invasive acoustic sensors to detect the time and duration of urination events from grazing cattle. The acoustic sensor identified the spectral acoustic patterns with a urination event like spectral signature and had an F1 = 0.88 in the validation study (the F1 statistic denotes the harmonic mean of precision (0.94) and sensitivity (0.83)). The acoustic prediction of urination event duration had an RMSE = 1.64 s in the validation study. The ensemble of audio recordings could also be assessed by an expert observer to provide the urination event time, event duration and the cow that generated the event with similar accuracy to the visual observation method. The urination surface type (pasture, concrete) could be detected based on the acoustic recordings (F1 = 0.93), which provides information on the environmental impact of events. The between-cow variation in urination frequency and duration has a coefficient of variation of 15–25%, which demonstrates the opportunity to identify and manage cows with increased urination frequency, lower volume per urination event, lower N load per event and reduced N leaching.

牛尿中氮 (N) 的排泄是放牧牧场系统中 N 浸出损失的主要来源。本研究的目的是评估非侵入性声学传感器检测放牧牛排尿事件的时间和持续时间的适用性。声学传感器通过排尿事件（如频谱特征）识别频谱声学模式，并且在验证研究中的 F1 = 0.88（F1 统计量表示精度 (0.94) 和灵敏度 (0.83) 的调和平均值）。在验证研究中，排尿事件持续时间的声学预测的 RMSE = 1.64 s。音频记录的集合也可以由专家观察员评估，以提供排尿事件时间、事件持续时间和产生事件的奶牛，其精度与视觉观察方法相似。可以根据声学记录 (F1 = 0.93) 检测排尿表面类型（牧场、混凝土），这提供了事件对环境影响的信息。奶牛之间排尿频率和持续时间的变化具有 15-25% 的变异系数，这表明有机会识别和管理排尿频率增加、每次排尿量较低、每次事件 N 负荷较低和 N 浸出减少的奶牛.