The discrimination-learning task determines the kind of frustration-related behaviours in laying hens (Gallus gallus domesticus)

Kühne, Franziska; Sauerbrey, Annika F.C.; Adler, S.

doi:10.1016/j.applanim.2013.09.003

Cited by 11 publications

(7 citation statements)

References 36 publications

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“…A higher activity index and a higher occupation index appeared during the daytime. This can be explained by chickens being active in the daytime along with a high activity index, and they expressed their natural instincts, such as stretching, preening and pacing (Kuhne et al 2013;Pereira et al 2013). However, chickens tend to be silent at night and gather together for resting and inactivity, which might result in a lower occupation index (Du et al 2018b).…”

Section: Resultsmentioning

confidence: 99%

An Automatic Detection Method for Abnormal Laying Hen Activities Using a 3d Depth Camera

Teng

2021

Eng. Agríc.

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With the increasing scale of farms and the correspondingly higher number of laying hens, it is increasingly difficult for farmers to monitor their animals in a traditional way. Early warning of abnormal animal activities is helpful for farmers' fast response to the negative impact on animal health, animal welfare and daily management. This study introduces an automatic and non-invasive method for detecting abnormal poultry activities using a 3D depth camera. A typical region including eighteen Hy-line brown laying hens was continuously monitored by a top-view Kinect during 49 continuous days. A mean prediction model (MPM), based on the frame difference algorithm, was built to monitor animal activities and occupation zones. As a result, this method reported abnormal activities with an average accuracy of 84.2% and a rate of misclassifying abnormal events of 15.8% (PFPR). Additionally, it was found that the flock showed a diurnal change pattern in the activity and occupation quantified index. They also presented a similar changing pattern each week.

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Section: Resultsmentioning

confidence: 99%

An Automatic Detection Method for Abnormal Laying Hen Activities Using a 3d Depth Camera

Teng

2021

Eng. Agríc.

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“…The second objective of this study was to identify subtle behavioural indicators of motivational conflict in chickens. Such behaviours may reflect ambivalence or frustration when an animal simultaneously wants to access a reward and avoid an aversive event or condition [ 20 , 21 ]. In this study, looking into the TC appeared to be a useful behaviour for recognizing motivational conflict.…”

Section: Discussionmentioning

confidence: 99%

Validation of a combined approach-avoidance and conditioned stimulus aversion paradigm for evaluating aversion in chickens

et al. 2021

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Understanding animals’ aversion is important to improving their welfare. Aversion is often assessed using an approach-avoidance (AA) test in which animals have to forfeit a reward if they want to avoid an event or environment presented in the same place. However, sometimes the event/environment suspected to be aversive may physically impair the animal’s ability to withdraw from that place (i.e. its ability to express aversion), leading to incorrect interpretations. Combining AA with a Conditioned-Stimulus that predicts the event/environment may overcome this problem by allowing animals to demonstrate aversion without exposure to the stimulus. We aimed to validate this paradigm for testing aversion in chickens. Seven Hyline-Brown chickens were trained to obtain a food reward from a coloured bowl located in the test chamber (TC) of a two-chambered box; the reward was presented in a green bowl with an inactivated air canister or a red bowl with the canister activated to deliver an air puff. Two 5-minute tests were conducted, one with each bowl colour and both with the canister inactivated. All chickens entered TC with the green bowl. With the red bowl, two chickens entered on their first attempt, one fully entered after a partial entry (3/7 fully entered), two made only partial entries and two made no attempts to enter. Chickens spent less time in the TC with the red bowl (median 31s, IQR 7–252) compared to the green bowl (293s, IQR 290–294; p = 0.008). The higher ratio of partial to full entries, failure to enter the TC and less time spent in TC reflected chickens’ aversion to the air puff, signalled by the red bowl. The paradigm allowed chickens to demonstrate aversion without exposure to the aversive stimulus during testing.

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“…Sounds of pecking for water from birds in abnormal status might be a kind of redirected behaviour when they cannot get access to food. Additionally, these vocalisations produced by pecking water nipples might be a kind of stereotyped behaviour [ 37 ]. By analysing the number of vocalisations and their area distributions via SSL, we can seek out abnormal sounds (e.g., if the flock’s number of vocalisations is higher than the normal night-time level) and find feeding problems.…”

Section: Discussionmentioning

confidence: 99%

A Sound Source Localisation Analytical Method for Monitoring the Abnormal Night Vocalisations of Poultry

Lao

Teng

2018

Sensors

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Due to the increasing scale of farms, it is increasingly difficult for farmers to monitor their animals in an automated way. Because of this problem, we focused on a sound technique to monitor laying hens. Sound analysis has become an important tool for studying the behaviour, health and welfare of animals in recent years. A surveillance system using microphone arrays of Kinects was developed for automatically monitoring birds’ abnormal vocalisations during the night. Based on the principle of time-difference of arrival (TDOA) of sound source localisation (SSL) method, Kinect sensor direction estimations were very accurate. The system had an accuracy of 74.7% in laboratory tests and 73.6% in small poultry group tests for different area sound recognition. Additionally, flocks produced an average of 40 sounds per bird during feeding time in small group tests. It was found that, on average, each normal chicken produced more than 53 sounds during the daytime (noon to 6:00 p.m.) and less than one sound at night (11:00 p.m.–3:00 a.m.). This system can be used to detect anomalous poultry status at night by monitoring the number of vocalisations and area distributions, which provides a practical and feasible method for the study of animal behaviour and welfare.

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The discrimination-learning task determines the kind of frustration-related behaviours in laying hens (Gallus gallus domesticus)

Cited by 11 publications

References 36 publications

An Automatic Detection Method for Abnormal Laying Hen Activities Using a 3d Depth Camera

An Automatic Detection Method for Abnormal Laying Hen Activities Using a 3d Depth Camera

Validation of a combined approach-avoidance and conditioned stimulus aversion paradigm for evaluating aversion in chickens

A Sound Source Localisation Analytical Method for Monitoring the Abnormal Night Vocalisations of Poultry

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