Ability evaluation of a voice activity detection algorithm in bioacoustics: A case study on poultry calls

Mahdavian, Alireza; Minaei, Saeid; Yang, Ce; Almasganj, Farshad; Rahimi, Shaban; Marchetto, Peter

doi:10.1016/j.compag.2019.105100

Cited by 20 publications

(10 citation statements)

References 17 publications

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“…This capacity to use single parameters to capture distress calling in chicks, and redundancy between them, offers scope to select parameters to either generalize across or specialize within ages. Or indeed commercial contexts, where acoustics may vary among strains with different vocalization rate [49], flocks with different health status [50], or houses with different machinery noise [51].…”

Section: Discussionmentioning

confidence: 99%

Spectral entropy of early-life distress calls as an iceberg indicator of chicken welfare

Herborn

McElligott

Mitchell

et al. 2020

J. R. Soc. Interface.

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Chicks ( Gallus gallus domesticus ) make a repetitive, high energy ‘distress’ call when stressed. Distress calls are a catch-all response to a range of environmental stressors, and elicit food calling and brooding from hens. Pharmacological and behavioural laboratory studies link expression of this call with negative affective state. As such, there is an a priori expectation that distress calls on farms indicate not only physical, but emotional welfare. Using whole-house recordings on 12 commercial broiler flocks ( n = 25 090–26 510/flock), we show that early life (day 1–4 of placement) distress call rate can be simply and linearly estimated using a single acoustic parameter: spectral entropy. After filtering to remove low-frequency machinery noise, spectral entropy per minute of recording had a correlation of −0.88 with a manual distress call count. In videos collected on days 1–3, age-specific behavioural correlates of distress calling were identified: calling was prevalent (spectral entropy low) when foraging/drinking were high on day 1, but when chicks exhibited thermoregulatory behaviours or were behaviourally asynchronous thereafter. Crucially, spectral entropy was predictive of important commercial and welfare-relevant measures: low median daily spectral entropy predicted low weight gain and high mortality, not only into the next day, but towards the end of production. Further research is required to identify what triggers, and thus could alleviate, distress calling in broiler chicks. However, within the field of precision livestock farming, this work shows the potential for simple descriptors of the overall acoustic environment to be a novel, tractable and real-time ‘iceberg indicator’ of current and future welfare.

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Section: Discussionmentioning

confidence: 99%

Spectral entropy of early-life distress calls as an iceberg indicator of chicken welfare

Herborn

McElligott

Mitchell

et al. 2020

J. R. Soc. Interface.

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“…A research team developed an avian influenza monitoring system utilizing sensor network by a simulation of the spread of highly pathogenic avian influenza viruses in chickens, and the results showed the capability of sensors detecting the avian influenza virus two days earlier than conventional detection of disease outbreak [37]. Other respiratory diseases can be timely detected using appropriate sound technologies [26,38].…”

Section: Plf In Improving Management Health and Welfare And Feedingmentioning

confidence: 99%

Precision Livestock Farming: The Opportunities in Poultry Sector

Maharjan¹,

Liang²

2020

JAST-A

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Precision management of animals using technology is one innovation in agriculture that has the potential to revolutionize whole livestock industries including the poultry sector. Limited research in precision livestock farming (PLF) in the poultry production has been so far conducted and most of them are conducted within the past 5-10 years. The PLF collects real-time data from individual or group of animals or birds using sensor technology, and involves the multidisciplinary team approach to give it a reality. Poultry scientists play a central role in executing poultry PLF with collaboration from agri-engineers and computer scientists for the type of measurements to be made on biological or environmental variables. A real-time collection of environmental, behavioral and health data from bird grow-out facilities can be a strong tool for developing daily action plans for poultry management. Unlike other livestock farming, the attributes of poultry rearing such as a closed housing system and vertically integrated industry provides a greater opportunity for poultry sector to adopt technology-based farming for enhanced production output.

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“…Sound analysis using microphones can be used to monitor vocalizations and coughing, alerting farmers to welfare issues before they become severe. Microphones also have the advantage of being easily placed in barns to monitor large groups of animals without worrying visibility (Mahdavian et al, 2020). Livestock farmers are increasingly utilizing radio-frequency identification (RFID), which may be placed in ear tags and collars or implanted in animals directly to monitor a wide variety of behaviors such as general activity, eating, or drinking (Neethirajan, 2017).…”

Section: Biosensingmentioning

confidence: 99%

“…Sound analysis can provide important information about poultry welfare. Chicken vocalizations can indicate issues with thermal comfort, social disturbances, feather pecking, disease, or growth (Du et al, 2020;Mahdavian et al, 2020). Chicken vocalizations also have a distinct diurnal pattern (Du et al, 2018).…”

Section: Poultrymentioning

confidence: 99%

“…The algorithm had a high rate of accuracy in differentiating between healthy chickens and chickens with respiratory illness. Two factors that increased error in sound detection included age and onset of illness; detection accuracy was lower for chickens with respiratory illness than for healthy birds, at 95% and 72%, respectively (Mahdavian et al, 2020). One possible explanation for the decreased accuracy of vocalizations for ill chickens is that chickens with respiratory disease produce abnormal vocalizations.…”

Section: Poultrymentioning

confidence: 99%

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Digitalization of Animal Farming

Neethirajan¹

2020

Preprint

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As the global human population increases, animal agriculture must adapt to provide more animal products while also addressing concerns about animal welfare, environmental sustainability, and public health. The purpose of this review is to discuss the digitalization of animal farming with Precision Livestock Farming (PLF) technologies, specifically biosensors, big data, and block chain technology. Biosensors are noninvasive or invasive sensors that monitor an animal’s health and behavior in real time, allowing farmers to monitor individual animals and integrate this data for population-level analyses. The data from the sensors is processed using big data-processing techniques such as data modelling. These technologies use algorithms to sort through large, complex data sets to provide farmers with biologically relevant and usable data. Blockchain technology allows for traceability of animal products from farm to table, a key advantage in monitoring disease outbreaks and preventing related economic losses and food-related health pandemics. With these PLF technologies, animal agriculture can become more transparent and regain consumer trust. While the digitalization of animal farming has the potential to address a number of pressing concerns, these technologies are relatively new. The implementation of PLF technologies on farms will require increased collaboration between farmers, animal scientists, and engineers to ensure that technologies can be used in realistic, on-farm conditions. These technologies will call for data models that can sort through large amounts of data while accounting for specific variables and ensuring automation, accessibility, and accuracy of data. Issues with data privacy, security, and integration will need to be addressed before there can be multi-farm databases. Lastly, the usage of blockchain technology in animal agriculture is still in its infancy; blockchain technology has the potential to improve the traceability and transparency of animal products, but more research is needed to realize its full potential. The digitalization of animal farming can supply the necessary tools to provide sustainable animal products on a global scale.

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Ability evaluation of a voice activity detection algorithm in bioacoustics: A case study on poultry calls

Cited by 20 publications

References 17 publications

Spectral entropy of early-life distress calls as an iceberg indicator of chicken welfare

Spectral entropy of early-life distress calls as an iceberg indicator of chicken welfare

Precision Livestock Farming: The Opportunities in Poultry Sector

Digitalization of Animal Farming

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