scholarly journals Characterizing Sounds of Different Sources in a Commercial Broiler House

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 916
Author(s):  
Xiao Yang ◽  
Yang Zhao ◽  
Hairong Qi ◽  
George T. Tabler
Keyword(s):  
Discrete Wavelet ◽  
Frequency Range ◽  
Feed System ◽  
Time Duration ◽  
Sound Sources ◽  
Commercial Broiler ◽  
Audio Data ◽  
Behavioral Frequencies ◽  
Different Sources ◽  
Broiler House

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.

scholarly journals Impact of feed system augering on physical segregation of pelleted feed throughout an entire commercial broiler house

2020 ◽  
Vol 29 (4) ◽  
pp. 886-894
Author(s):  
R.B. Sellers ◽  
A.T. Brown ◽  
T. Tabler ◽  
C. McDaniel ◽  
K.G.S. Wamsley
Keyword(s):  
Feed System ◽  
Commercial Broiler ◽  
Pelleted Feed ◽  
Broiler House

scholarly journals THE PECULIARITIES OF THE SOUND FIELD ENERGY DECAY IN A ROOM WITH THE USE OF DIFFERENT PULSED SOUND SOURCES/GARSO LAUKO ENERGIJOS SLOPIMO PATALPOJE YPATUMAI, NAUDOJANT SKIRTINGUS IMPULSINIUS GARSO ŠALTINIUS

1999 ◽  
Vol 5 (2) ◽  
pp. 135-140
Author(s):  
Vytautas Stauskis
Keyword(s):  
Noise Level ◽  
Sound Field ◽  
Maximum Energy ◽  
Reverberation Time ◽  
Frequency Range ◽  
Sound Sources ◽  
Low Frequencies ◽  
High Frequencies ◽  
The Difference ◽  
Field Decay

The paper deals with the differences between the energy created by four different pulsed sound sources, ie a sound gun, a start gun, a toy gun, and a hunting gun. A knowledge of the differences between the maximum energy and the minimum energy, or the signal-noise ratio, is necessary to correctly calculate the frequency dependence of reverberation time. It has been established by investigations that the maximum energy excited by the sound gun is within the frequency range of 250 to 2000 Hz. It decreases by about 28 dB at the low frequencies. The character of change in the energy created by the hunting gun differs from that of the sound gun. There is no change in the maximum energy within the frequency range of 63–100 Hz, whereas afterwards it increases with the increase in frequency but only to the limit of 2000 Hz. In the frequency range of 63–500 Hz, the energy excited by the hunting gun is lower by 15–30 dB than that of the sound gun. As frequency increases the difference is reduced and amounts to 5–10 dB. The maximum energy of the start gun is lower by 4–5 dB than that of the hunting gun in the frequency range of up to 1000 Hz, while afterwards the difference is insignificant. In the frequency range of 125–250 Hz, the maximum energy generated by the sound gun exceeds that generated by the hunting gun by 20 dB, that by the start gun by 25 dB, and that by the toy gun—by as much as 35 dB. The maximum energy emitted by it occupies a wide frequency range of 250 to 2000 Hz. Thus, the sound gun has an advantage over the other three sound sources from the point of view of maximum energy. Up until 500 Hz the character of change in the direct sound energy is similar for all types of sources. The maximum energy of direct sound is also created by the sound gun and it increases along with frequency, the maximum values being reached at 500 Hz and 1000 Hz. The maximum energy of the hunting gun in the frequency range of 125—500 Hz is lower by about 20 dB than that of the sound gun, while the maximum energy of the toy gun is lower by about 25 dB. The maximum of the direct sound energy generated by the hunting gun, the start gun and the toy gun is found at high frequencies, ie at 1000 Hz and 2000 Hz, while the sound gun generates the maximum energy at 500 Hz and 1000 Hz. Thus, the best results are obtained when the energy is emitted by the sound gun. When the sound field is generated by the sound gun, the difference between the maximum energy and the noise level is about 35 dB at 63 Hz, while the use of the hunting gun reduces the difference to about 20–22 dB. The start gun emits only small quantities of low frequencies and is not suitable for room's acoustical analysis at 63 Hz. At the frequency of 80 Hz, the difference between the maximum energy and the noise level makes up about 50 dB, when the sound field is generated by the sound gun, and about 27 dB, when it is generated by the hunting gun. When the start gun is used, the difference between the maximum signal and the noise level is as small as 20 dB, which is not sufficient to make a reverberation time analysis correctly. At the frequency of 100 Hz, the difference of about 55 dB between the maximum energy and the noise level is only achieved by the sound gun. The hunting gun, the start gun and the toy gun create the decrease of about 25 dB, which is not sufficient for the calculation of the reverberation time. At the frequency of 125 Hz, a sufficiently large difference in the sound field decay amounting to about 40 dB is created by the sound gun, the hunting gun and the start gun, though the character of the sound field curve decay of the latter is different from the former two. At 250 Hz, the sound gun produces a field decay difference of almost 60 dB, the hunting gun almost 50 dB, the start gun almost 40 dB, and the toy gun about 45 dB. At 500 Hz, the sound field decay is sufficient when any of the four sound sources is used. The energy difference created by the sound gun is as large as 70 dB, by the hunting gun 50 dB, by the start gun 52 dB, and by the toy gun 48 dB. Such energy differences are sufficient for the analysis of acoustic indicators. At the high frequencies of 1000 to 4000 Hz, all the four sound sources used, even the toy gun, produce a good difference of the sound field decay and in all cases it is possible to analyse the reverberation process at varied intervals of the sound level decay.

Heritability Estimates for Juvenile Body weight by Least Squares and DFREML in a Commercial Broiler Breeder Dam Population

1994 ◽  
Vol 1994 ◽  
pp. 51-51
Author(s):  
A.J. Morris ◽  
G.E. Pollott
Keyword(s):  
Growth Rate ◽  
Body Weight ◽  
Least Squares ◽  
Production Efficiency ◽  
Early Growth ◽  
Broiler Breeder ◽  
Derivative Free ◽  
Commercial Broiler ◽  
Body Weight Measure ◽  
Different Sources

To date commercial broiler breeders have focused primarily on increasing early growth rate in selection programmes aimed at improving overall production efficiency. In commercial programmes, early growth rate is simplified to a single body weight measure taken at a fixed age during the growth phase approaching common slaughter weights. Most recent selection studies report heritabilities from experimental populations that are at best, synthesised from crossing modern broiler material from several different sources (Leenstra et al, 1986; Wang et al, 1991). Therefore, such populations are likely to exhibit greater heterozygosity than many commercial lines which have undergone many generations of intense selection in closed populations. This paper reports heritabilities estimated using both least squares and derivative-free maximum likelihood techniques for data from a commercial breeder dam line which has remained closed since its inception in 1975.

Active Control of Low-Frequency Sound Radiation From Vibrating Panel Using Planar Sound Sources

2001 ◽  
Vol 124 (1) ◽  
pp. 2-9 ◽  
Author(s):  
Kean Chen ◽  
Gary H. Koopmann
Keyword(s):  
Active Control ◽  
Near Field ◽  
Low Frequency ◽  
Sound Radiation ◽  
Sound Field ◽  
Sound Power ◽  
Frequency Range ◽  
Sound Sources ◽  
Frequency Sound ◽  
Secondary Sources

Active control of low frequency sound radiation using planar secondary sources is theoretically investigated in this paper. The primary sound field originates from a vibrating panel and the planar sources are modeled as simply supported rectangular panels in an infinite baffle. The sound power of the primary and secondary panels are calculated using a near field approach, and then a series of formulas are derived to obtain the optimum reduction in sound power based on minimization of the total radiate sound power. Finally, active reduction for a number of secondary panel arrangements is examined and it is concluded that when the modal distribution of the secondary panel does not coincide with that of the primary panel, one secondary panel is sufficient. Otherwise four secondary panels can guarantee considerable reduction in sound power over entire frequency range of interest.

HEART MURMURS DETECTION AND CHARACTERIZATION USING WAVELET ANALYSIS WITH RENYI ENTROPY

2017 ◽  
Vol 17 (06) ◽  
pp. 1750093 ◽  
Author(s):  
BOUTANA DAOUD ◽  
KOURAS NAYAD ◽  
BARKAT BRAHAM ◽  
BENIDIR MESSAOUD
Keyword(s):  
Aortic Stenosis ◽  
Heart Diseases ◽  
Pulmonary Stenosis ◽  
Peak Frequency ◽  
Renyi Entropy ◽  
Rényi Entropy ◽  
Discrete Wavelet ◽  
Time Duration ◽  
Time Frequency ◽  
Main Components

Phonocardiogram signals (PCGs) represent a nonstationary signal due to their complicated production. Also, during the registration they may be added with different noise and pathological murmurs. Indeed, in real situation, the heart sound signal (HSs) may present some abnormal murmur characterizing a variety of heart diseases. This work deals with the segmentation of pathological PCGs based on the Discrete Wavelet Transform (DWT) which permits signal decomposition in different frequency bands. After the decomposition step, we estimate the Renyi Entropy (RE) of the detail coefficients. Then, we apply a threshold allowing detecting the murmur of the PCGs. After the detection, we characterize the results in time–frequency domain in order to extract some features such as frequency band, peak frequency and time duration of the abnormal murmur. The validation of the method is evaluated and proved using some pathological PCGs such as: Early Aortic Stenosis (EAS), Late Aortic Stenosis (LAS), Mitral Regurgitation (MR), Aortic Regurgitation (AR), Opening Snap (OS) and Pulmonary Stenosis (PS). The method presents good results in terms of the detection and the characterization of the main components and the abnormal murmurs associated with some valves disease.

scholarly journals Spatial variability of enthalpy in broiler house during the heating phase

2016 ◽  
Vol 20 (6) ◽  
pp. 570-575 ◽  
Author(s):  
Patrícia F. P. Ferraz ◽  
Tadayuki Yanagi Junior ◽  
Gabriel A. e S. Ferraz ◽  
Leonardo Schiassi ◽  
Alessandro T. Campos
Keyword(s):  
Spatial Variability ◽  
Thermal Environment ◽  
Great Influence ◽  
Heating System ◽  
Economic Losses ◽  
Thermal Discomfort ◽  
Heating Phase ◽  
Commercial Broiler ◽  
Geostatistical Techniques ◽  
Broiler House

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.

Ammonia and Nitrous Oxide Emissions from a Commercial Broiler House

2014 ◽  
Vol 43 (4) ◽  
pp. 1119-1124 ◽  
Author(s):  
D. M. Miles ◽  
P. A. Moore ◽  
R. T. Burns ◽  
J. P. Brooks
Keyword(s):  
Nitrous Oxide ◽  
Nitrous Oxide Emissions ◽  
Commercial Broiler ◽  
Broiler House
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