Abstract：
Indoor environmental control is usually applied in poultry farming to ensure optimum growth conditions for birds. However, these control methods represent a considerable share of total energy consumption, and the trend of applying new equipment in the future for precision livestock farming would further increase energy demand, resulting in an increase in greenhouse gas emissions and management costs. Therefore, to ensure optimum efficiency of both energy use and livestock productivity, a customized hourly model was developed in the present study to interpret and analyze the electronically collected data. The modules for estimating indoor gas concentrations were incorporated into the present model, as this has not been properly considered in previous studies. A validation test was performed in a manure-belt layer house using sensors and meters to measure the indoor environmental parameters and energy consumption. The predicted results, including indoor temperature, relative humidity, carbon dioxide and ammonia concentrations, showed good agreement with the measured data, indicating a similar overall trend with acceptable discrepancies. Moreover, the corresponding differences between the measured and simulated energy consumption for heating, tunnel ventilation and base ventilation were 13.7, 7.5, and 0.1%, respectively. The total energy demand estimated by the model showed a limited discrepancy of approximately 10.6% compared with that measured in reality. Although human factors, including inspection, cleaning, vaccination, etc., were not included in the model, the validation results still suggested that the customized model was able to accurately predict the indoor environment and overall energy consumption during poultry farming. The validated model provides a tool for poultry producers to optimize production planning and management strategies, increase the production rate of unit energy consumption and achieve precision livestock farming from an energy consumption standpoint.
摘要：
室内环境控制通常用于家禽养殖，以确保鸟类的最佳生长条件。然而,这些控制方法在总能耗中占有相当大的份额，未来应用新设备进行精准畜牧业的趋势将进一步增加能源需求，导致温室气体排放和管理成本的增加。因此,为了确保能源使用和牲畜生产力的最佳效率，本研究开发了一个定制的每小时模型来解释和分析电子收集的数据.估算室内气体浓度的模块被纳入本模型，因为这在以前的研究中没有得到适当的考虑。在粪肥带层房屋中使用传感器和仪表进行了验证测试，以测量室内环境参数和能耗。预测结果,包括室内温度，相对湿度,二氧化碳和氨的浓度，与实测数据表现出良好的一致性，表明类似的总体趋势，但存在可接受的差异。此外，测量的和模拟的加热能耗之间的相应差异，隧道通风和基础通风分别为13.7%、7.5%和0.1%，分别。该模型估计的总能源需求与实际测量的差异约为10.6％。虽然人为因素,包括检查,清洁,疫苗接种,等。,不包括在模型中，验证结果仍然表明，定制模型能够准确预测家禽养殖过程中的室内环境和总体能耗。经验证的模型为家禽生产者提供了优化生产计划和管理策略的工具，提高单位能耗的生产率，从能耗的角度实现精准畜牧业。
