Du Longhuan, Yang Li, Yang Chaowu, Hu Chenming, Yu Chunlin, Qiu Mohan, Liu Siyang, Zhu Shiliang, Ye Xianlin
College of Architecture and Environment, Sichuan University, Chengdu 610065, China.
Sichuan Animal Science Academy, Chengdu 610065, China.
Animals (Basel). 2022 Sep 27;12(19):2580. doi: 10.3390/ani12192580.
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.
室内环境控制通常应用于家禽养殖中，以确保禽类的最佳生长条件。然而，这些控制方法在总能源消耗中占相当大的比例，未来在精准畜牧业中应用新设备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上升。因此，为了确保能源利用和牲畜生产力的最佳效率，本研究开发了一个定制的小时模型，用于解释和分析电子收集的数据。估计室内气体浓度的模块被纳入到当前模型中，因为之前的研究没有对此进行适当考虑。在一个粪便带式蛋鸡舍中进行了验证测试，使用传感器和仪表测量室内环境参数和能源消耗。预测结果，包括室内温度、相对湿度、二氧化碳和氨浓度，与测量数据显示出良好的一致性，表明总体趋势相似，差异在可接受范围内。此外，加热、隧道通风和基础通风的测量能耗与模拟能耗之间的相应差异分别为13.7%、7.5%和0.1%。该模型估计的总能源需求与实际测量值相比，差异约为10.6%，较为有限。尽管模型中未包括检查、清洁、疫苗接种等人为因素，但验证结果仍表明，定制模型能够准确预测家禽养殖期间的室内环境和总体能源消耗。经过验证的模型为家禽生产者提供了一个工具，用于优化生产计划和管理策略，提高单位能源消耗的生产率，并从能源消耗的角度实现精准畜牧业。
