Ammonia (NH3) concentration has seldom been used for environmental control of weaner buildings despite its impact on environment, animal welfare, and workers’ health. This paper aims to determine the effects of setpoint temperature (ST) on the daily evolution of NH3 concentration in the animal-occupied zone. An experimental test was conducted on a conventional farm, with ST between 23 °C and 26 °C. NH3 concentrations in the animal-occupied zone were dependent on ST insofar as ST controlled the operation of the ventilation system, which effectively removed NH3 from the building. The highest NH3 concentrations occurred at night and the lowest concentrations occurred during the daytime. Data were fitted to a sinusoidal model using the least squares setting (LSS) and fast Fourier transform (FFT), which provided R2 values between 0.71 and 0.93. FFT provided a better fit than LSS, with root mean square errors (RMSEs) between 0.09 ppm for an ST of 23 °C and 0.55 ppm for an ST of 25 °C. A decrease in ST caused a delay in the wave and a decrease in wave amplitude. The proposed equations can be used for modeling NH3 concentrations and implemented in conventional controllers for real-time environmental control of livestock buildings to improve animal welfare and productivity.
This paper aims to study the evolution of CO2 concentrations and emissions on a conventional farm with weaned piglets between 6.9 and 17.0 kg live weight based on setpoint temperature, outdoor temperature, and ventilation flow. The experimental trial was conducted during one transition cycle. Generally, the ventilation flow increased with the reduction in setpoint temperature throughout the cycle, which caused a reduction in CO2 concentration and an increase in emissions. The mean CO2 concentration was 3.12 g m–3. Emissions of CO2 had a mean value of 2.21 mg s−1 per animal, which is equivalent to 0.195 mg s−1 kg−1. A potential function was used to describe the interaction between 10 min values of ventilation flow and CO2 concentrations, whereas a linear function was used to describe the interaction between 10 min values of ventilation flow and CO2 emissions, with r values of 0.82 and 0.85, respectively. Using such equations allowed for simple and direct quantification of emissions. Furthermore, two prediction models for CO2 emissions were developed using two neural networks (for 10 min and 60 min predictions), which reached r values of 0.63 and 0.56. These results are limited mainly by the size of the training period, as well as by the differences between the behavior of the series in the training stage and the testing stage.
Measuring animal activity is useful for monitoring animal welfare in real time. In this regard, passive infrared detectors have been used in recent years to quantify piglet activity because of their robustness and ease of use. This study was conducted on a commercial farm in Northwest Spain during six complete breeding cycles. The hourly average activity of weaned piglets with a body mass of 6–20 kg was recorded and further analyzed by using a multiplicative decomposition of the series followed by a wavelet analysis. Finally, the real series were compared to the theoretical models of activity. Results showed a high level of movement immediately after weaning and a sustained level of activity throughout the cycles. The daily behavior of the piglets followed a clear circadian pattern with several peaks of activity. No differences in behavior were observed between spring–summer cycles and autumn–winter cycles. Single-peak models achieved the best predictive results. In addition, the installed sensors were found to underestimate mild activity.
Postweaning is one of the most sensitive and energy-demanding phases of swine production. The objective of this research was to assess the energy, production and environmental characteristics of a conventional farm with temperature-based environmental control. The selected energy, environmental and production variables were measured on farm, in a high livestock density area of NW Spain, for seven production cycles. The quantification of variables was aimed at obtaining the maximum performance with the lowest possible use of resources, focusing on animal welfare and production efficiency. The Brown–Forsythe, Welch and Games-Howell tests revealed significant differences in terms of temperature, relative humidity and CO2 concentrations among production cycles, and among the critical, postcritical and final periods. Improved humidity management resulted in a 17% reduction of climate control energy, which involved energy savings in the range of 33% to 47% per kg produced at the end of the postweaning cycle. Accordingly, adding humidity as a control variable could result in higher ventilation rates, thereby improving animal welfare, reducing heating energy use and increasing weight gain per unit climate control energy. In addition, the strong correlations found between heating energy and relative humidity (R2 = 0.73) and ventilation energy and CO2 (R2 = 0.99) suggest that these variables could be readily estimated without additional sensor costs.
Measuring ammonia inside livestock buildings poses many challenges that hinder the incorporation of this variable into environmental control systems. The aim of this study was to measure various microclimate variables inside a weaned piglet building and analyse their interactions with NH3 concentrations for setpoint temperatures of 26 and 25 °C, in order to control NH3 concentrations based on other easily measurable variables. The experimental test was conducted on a conventional farm in Northwest Spain. NH3 concentrations in the animal zone were best correlated with CO2 concentrations in the animal zone (R = 0.91 and R = 0.55) and velocity of air extracted through the fan (R = 0.72 and R = 0.65) for setpoint temperatures of 26 and 25 °C, respectively. Similarly, strong correlations were found with relative humidity in the animal zone and temperature of inlet air. Because NH3 concentration in the animal zone is related to the performance of the ventilation system, strong positive correlations were found between NH3 concentration and temperature of inlet air whereas negative correlations were found between NH3 concentration and ventilation rates. Linear regression models based on CO2 concentrations in the animal zone and temperature of inlet air are recommended, because they provide a good fit for both setpoint temperatures using variables that can be readily measured.
Measuring animal activity and its evolution in real time is useful for animal welfare assessment. In addition, illuminance and noise level are two factors that can improve our understanding of animal activity. This study aims to establish relationships between animal activity as measured by passive infrared sensors, and both illuminance and noise level on a conventional weaned piglet farm. First, regression models were applied, and then cosine models with three harmonics were developed using least squares with a Generalized Reduced Gradient Nonlinear method. Finally, all the models were validated. Linear models showed positive correlations, with values between 0.40 and 0.56. Cosine models drew clear patterns of daily animal activity, illuminance and noise level with two peaks, one in the morning and one in the afternoon, coinciding with human activity inside the building, with a preference for inactivity at night-time and around midday. Cosine model fitting revealed strong correlations, both in the measurement and validation periods, for animal activity (R = 0.97 and 0.92), illuminance (R = 0.95 and 0.91) and noise level (R = 0.99 and 0.92). The developed models could be easily implemented in animal welfare monitoring systems and could provide useful information about animal activity through continuous monitoring of illuminance or noise levels.