Ammonia concentration and emissions in a commercial broiler house at different seasons in China

2010 ◽  
Author(s):  
Zhiping Zhu ◽  
Hongmin Dong ◽  
Zhongkai Zhou ◽  
Jialin Xi ◽  
Ruijuan Ma ◽  
...  
2020 ◽  
Vol 50 (10) ◽  
Author(s):  
Antonise Mariely Jaguezeski ◽  
Ana Martiele Engelmann ◽  
Ivna Nalério dos Reis Machado ◽  
Beatriz Pavei Bez Batti

ABSTRACT: Condemnations in the broilers abattoirs can represent an overview farms health and effectiveness of welfare programs, as well as predisposition between hybrids. The aim of this study was to investigate the prevalence of condemnation among four commercial broiler hybrids and the oscillation of condemnations in different seasons in a poultry abattoir. Data from condemnations of the Federal Inspection Service of a slaughterhouse were analyzed during one year, in which a total of 12.81% of partial condemnations were observed and total condemnations represented 0.41% of slaughtered broiler. There was a difference in total and partial condemnation among the hybrids evaluated, with Hubbard hybrid being the one with the highest number of condemnations (0.67% - 17.71%), followed by Ross 95 (0.42% - 14.21%), Cobb (0.30% - 10.03%); and Cobb Fast (0.26% - 9.29%). The analysis between the seasons showed a higher conviction rate in winter and a lower rate in autumn for both total and partial condemnation. Hubbard had the highest rates and Cobb Fast the lowest for most causes of condemnation. We concluded that the metabolic cause led to higher losses by total condemnation, while contamination or technopathies represented the highest rates in partial losses. The broiler hybrid and the time of year may influence the causes of condemnation in the abattoir. This information should be considered by the abattoir and the farms in sanitary planning, considering the financial impact due to losses by condemnations of carcasses.


Author(s):  
Patrícia F. P. Ferraz ◽  
Tadayuki Yanagi Junior ◽  
Gabriel A. e S. Ferraz ◽  
Leonardo Schiassi ◽  
Alessandro T. Campos

ABSTRACT The thermal environment inside a broiler house has a great influence on animal welfare and productivity during the production phase. Enthalpy is a thermodynamic property that has been proposed to evaluate the internal broiler house environment, for being an indicator of the amount of energy contained in a mixture of water vapor and dry air. Therefore, this study aimed to characterize the spatial variability of enthalpy in a broiler house during the heating phase using geostatistics. The experiment was conducted in the spring season, in a commercial broiler house with heating system consisting of two furnaces that heat the air indirectly, in the first 14 days of the birds' life. It was possible to characterize enthalpy variability using geostatistical techniques, which allowed observing the spatial dependence through kriging maps. The analyses of the maps allowed observing problems in the heating system in regions inside the broiler house, which may cause a thermal discomfort to the animals besides productive and economic losses.


2020 ◽  
Vol 61 (2) ◽  
pp. 59-70
Author(s):  
Zeying Xu ◽  
Xiuguo Zou ◽  
Zhengling Yin ◽  
Shikai Zhang ◽  
Yuanyuan Song ◽  
...  

In winter, the poor ventilation conditions in broiler houses may lead to high ammonia concentration, which affects the health of yellow-feather broilers or even causes the death of many broilers. This research used a machine learning model to predict the ammonia concentration in a broiler house during winter. After analysis, it was found that the ammonia generation in the broiler house was a gradual accumulation featured by non-linear data. After the broilers entered the broiler house for several days, and the ammonia concentration reached a certain value, a ventilation system was used for regulating the concentration. Firstly, the back-propagation (BP) neural network model and gated recurrent unit (GRU) model were used for predicting the ammonia concentration, respectively. Then, ensemble empirical mode decomposition (EEMD) was performed on the time series data of ammonia concentration in the broiler house. After that, the EEMD-GRU prediction model has been established for the intrinsic mode function (IMF) components and the temperature and humidity data in the broiler house. Finally, all component results were summarized to obtain the final prediction result. A comparison was conducted among the prediction results obtained by the above three models. The results show that the root mean square errors of the above three models are 6.2 ppm, 4.4 ppm, and 2.4 ppm, respectively, and the average absolute errors were 4.9 ppm, 2.8 ppm, and 1.6 ppm, respectively. It could be seen that the EEMD-GRU model had higher accuracy in predicting the ammonia concentration in the broiler house. The EEMD-GRU model can effectively predict the ammonia concentration in broiler houses, facilitating the feedback to the central system for timely adjustment.


2014 ◽  
Vol 43 (4) ◽  
pp. 1119-1124 ◽  
Author(s):  
D. M. Miles ◽  
P. A. Moore ◽  
R. T. Burns ◽  
J. P. Brooks

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 916
Author(s):  
Xiao Yang ◽  
Yang Zhao ◽  
Hairong Qi ◽  
George T. Tabler

Audio data collected in commercial broiler houses are mixed sounds of different sources that contain useful information regarding bird health condition, bird behavior, and equipment operation. However, characterizations of the sounds of different sources in commercial broiler houses have not been well established. The objective of this study was, therefore, to determine the frequency ranges of six common sounds, including bird vocalization, fan, feed system, heater, wing flapping, and dustbathing, at bird ages of week 1 to 8 in a commercial Ross 708 broiler house. In addition, the frequencies of flapping (in wing flapping events, flaps/s) and scratching (during dustbathing, scratches/s) behaviors were examined through sound analysis. A microphone was installed in the middle of broiler house at the height of 40 cm above the back of birds to record audio data at a sampling frequency of 44,100 Hz. A top-view camera was installed to continuously monitor bird activities. Total of 85 min audio data were manually labeled and fed to MATLAB for analysis. The audio data were decomposed using Maximum Overlap Discrete Wavelet Transform (MODWT). Decompositions of the six concerned sound sources were then transformed with the Fast Fourier Transform (FFT) method to generate the single-sided amplitude spectrums. By fitting the amplitude spectrum of each sound source into a Gaussian regression model, its frequency range was determined as the span of the three standard deviations (99% CI) away from the mean. The behavioral frequencies were determined by examining the spectrograms of wing flapping and dustbathing sounds. They were calculated by dividing the number of movements by the time duration of complete behavioral events. The frequency ranges of bird vocalization changed from 2481 ± 191–4409 ± 136 Hz to 1058 ± 123–2501 ± 88 Hz as birds grew. For the sound of fan, the frequency range increased from 129 ± 36–1141 ± 50 Hz to 454 ± 86–1449 ± 75 Hz over the flock. The sound frequencies of feed system, heater, wing flapping and dustbathing varied from 0 Hz to over 18,000 Hz. The behavioral frequencies of wing flapping were continuously decreased from week 3 (17 ± 4 flaps/s) to week 8 (10 ± 1 flaps/s). For dustbathing, the behavioral frequencies decreased from 16 ± 2 scratches/s in week 3 to 11 ± 1 scratches/s in week 6. In conclusion, characterizing sounds of different sound sources in commercial broiler houses provides useful information for further advanced acoustic analysis that may assist farm management in continuous monitoring of animal health and behavior. It should be noted that this study was conducted with one flock in a commercial house. The generalization of the results remains to be explored.


2002 ◽  
Author(s):  
John W Worley ◽  
Michael Czarick ◽  
Anna M Cathey

2006 ◽  
Author(s):  
Brian D. Fairchild ◽  
John W. Worley ◽  
Mike Czarick ◽  
Casey W. Ritz

2012 ◽  
Author(s):  
Brian D Luck ◽  
Jeremiah D Davis ◽  
Joseph L Purswell ◽  
Jonathan W. W Olsen

2013 ◽  
Vol 22 (2) ◽  
pp. 211-216 ◽  
Author(s):  
Y. Liang ◽  
M.T. Kidd ◽  
S.E. Watkins ◽  
G.T. Tabler

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