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.
ABSTRACT
The main advantage of having livestock, for example, the laying hens, in a controlled environment is that the optimum growth conditions can be achieved with accuracy. The indoor air temperature, humidity, gases concentration, etc., would significantly affect the animal performance, thus should be maintained within an acceptable range. In order to achieve the goals of precision poultry farming, various models have been developed by researchers all over the world to estimate the hourly indoor environmental parameters so as to provide decision suggestions. However, a key parameter of hourly manure area in the poultry house was missing in the literature to predict the ammonia emission using the recently developed mechanistic model. Therefore, in order to fill the gap of the understanding of hourly manure coverage proportion and area on the manure belt, experimental measurements were performed in the present study using laying hens from 10 weeks age to 30 weeks age. For each test, six polypropylene (pp) plates were applied to collect the manure dropped by the birds every hour, and photographs of the plates were taken at the same time using a pre-fixed camera. Binary images were then produced based on the color pictures to determine the object coverage proportion. It was demonstrated that for laying hens of stocking density around 14 birds/m2, the manure coverage proportion at the 24th hour after the most recent manure removal was about 60%, while the value was approximately 82% at the 48th hour. Meanwhile, for laying hens at different ages, the hourly increment of manure coverage proportion showed a similar pattern with four distinct stages within 48 h. The statistical analyses demonstrated no significant correlation between the hourly increment of manure weight and the hourly increment of manure coverage proportion. Finally, prediction models for estimating the hourly manure coverage proportion on the manure belt in typical laying hen houses were provided.