Note on a method for individual recording of laying performance in groups of hens

Burel, Christine; Ciszuk, P.; Wiklund, Bo-Sören; Brännäs, Eva; Kiessling, Anders

doi:10.1016/s0168-1591(02)00045-x

Cited by 6 publications

(16 citation statements)

References 6 publications

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“…Many recording systems have been developed and tested [ 2 , 8 , 12 – 27 ] to collect data about laying performance and the behavior of hens. Among these studies, the most cited system is the funnel nest box (FNB) [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

“…Combining the transponder ID, the egg sensor signal and the position of the egg in the egg collection tube, the system can figure out the “egg-to-hen” assignment. Another type of recording system was instead developed by Burel [ 12 ]. In this system, each hen carries two passive transponders, one injected into its neck and the other glued to its leg band.…”

Section: Introductionmentioning

confidence: 99%

“…The resulting system, therefore, has many mechanical components for each nest. In addition, the data collected for breeding programs may be less accurate, since normal laying behaviors could be discouraged by the presence of the trap devices [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

“…Other systems, instead, do not try to avoid a double occupation of the nest through specific trap devices at the nest entrance. They only prevent more than one hen from occupying the nest at the same time by narrowing the nest [ 12 ]. In this way, the nest construction is simplified, but double nest occupations are not entirely avoided.…”

Section: Introductionmentioning

confidence: 99%

“…Imaging analysis has never been used in this context, and it is an interesting approach, since it could allow the detection of the concurrent occupation of the nest without the use of any mechanical components, such as a double tilting floor. The nest construction for the recording systems, such as the FNB, could be simplified, while the recording systems that are not equipped with trap devices [ 12 ] and for which double nest occupations are not managed could be improved by the use of this sensor.…”

Section: Introductionmentioning

confidence: 99%

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Preliminary Evaluation of a Nest Usage Sensor to Detect Double Nest Occupations of Laying Hens

Zaninelli

Costa

Tangorra

et al. 2015

Sensors

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Conventional cage systems will be replaced by housing systems that allow hens to move freely. These systems may improve hens' welfare, but they lead to some disadvantages: disease, bone fractures, cannibalism, piling and lower egg production. New selection criteria for existing commercial strains should be identified considering individual data about laying performance and the behavior of hens. Many recording systems have been developed to collect these data. However, the management of double nest occupations remains critical for the correct egg-to-hen assignment. To limit such events, most systems adopt specific trap devices and additional mechanical components. Others, instead, only prevent these occurrences by narrowing the nest, without any detection and management. The aim of this study was to develop and test a nest usage “sensor”, based on imaging analysis, that is able to automatically detect a double nest occupation. Results showed that the developed sensor correctly identified the double nest occupation occurrences. Therefore, the imaging analysis resulted in being a useful solution that could simplify the nest construction for this type of recording system, allowing the collection of more precise and accurate data, since double nest occupations would be managed and the normal laying behavior of hens would not be discouraged by the presence of the trap devices.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Preliminary Evaluation of a Nest Usage Sensor to Detect Double Nest Occupations of Laying Hens

Zaninelli

Costa

Tangorra

et al. 2015

Sensors

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Nest acceptance, clutch, and oviposition traits are promising selection criteria to improve egg production in cage-free system

et al. 2021

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In cage-free systems, laying hens must lay their eggs in the nests. Selecting layers based on nesting behavior would be a good strategy for improving egg production in these breeding systems. However, little is known about the genetic determinism of nest-related traits. Laying rate in the nests (LRN), clutch number (CN), oviposition traits (OT), and nest acceptance for laying (NAL) of 1,430 Rhode Island Red (RIR) hens and 1,008 White Leghorn (WL) hens were recorded in floor pens provided with individual electronic nests. Heritability and genetic and phenotypic correlations of all traits were estimated over two recording periods–the peak (24–43 weeks of age) and the middle (44–64 weeks of age) of production–by applying the restricted maximum likelihood method to an animal model. The mean oviposition time (MOT) ranged from 2 h 5 min to 3 h and from 3 h 35 min to 3 h 44 min after turning on the lights for RIR and WL hens, respectively. The mean oviposition interval ranged from 24 h 3 min to 24 h 16 min. All heritability and correlation estimates were similar for RIR and WL. Low to moderate heritability coefficients were estimated for LRN (0.04–0.25) and moderate to high heritability coefficients for CN and OT (0.27–0.68). CN and OT were negatively genetically correlated with LRN (-0.92 to -0.39) except during peak production for RIR (-0.30 to +0.43). NAL was weakly to moderately heritable (0.13–0.26). Genetic correlations between NAL and other traits were low to moderate (-0.41 to +0.44). In conclusion, CN and OT are promising selection criteria to improve egg production in cage-free systems. NAL can be also used to reduce the number of eggs laid off-nest in these breeding systems. However, variability in MOT must be maintained to limit competition for the nests.

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An IoT-Based Breeding Egg Identification and Coding System for Selection of High-Quality Breeding Geese

Zhang

Tian

et al. 2022

Animals

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The selection of breeding geese requires the recording of egg production information to correspond to the identity of the breeding geese. However, due to the special physiological characteristics of breeding geese, manual recording in practice can affect the egg-laying performance of breeding geese and can also lead to problems of missing and confusing individual breeding goose data with the number of eggs laid by the geese. For contactless recording of breeding goose identity and egg production information for high-quality breeding, this paper proposes an Internet of things (IoT)-based breeding egg identification and coding method for the selection of high-quality breeding geese. At the sensing level, we deployed a radiofrequency identification (RFID)-based sensor. Each breeding goose wore a foot ring RFID tag on its leg, and the individual information was read by foot ring RFID readers placed at the bottom of the devices. Individual information was uploaded to the cloud server for database management through structured query language (MySQL). The target detection modules were mounted on top of the devices, and the breeding geese and eggs were detected in the delivery rooms by an improved single-shot multi-box detector (SSD) target detection algorithm. The egg body limit transmission device and contactless coding device were activated only in the case of breeding eggs, and the breeding goose information was printed on the egg bodies in the form of quick response codes (QR codes), which enabled the breeding egg information to correspond with the breeding goose information. An evaluative experiment was performed using a system for the selection of high-quality breeding geese, with web cameras and a cloud monitoring platform. The breeding geese were allowed 14 days to become accustomed to the experimental environment before monitoring began. The evaluative experiment results showed that the pass rate of egg body coding reached 98.25%, the improved SSD algorithm was 8.65% more accurate and 62.6 ms faster than traditional SSD, and the accuracy rate corresponding to the individual information of the breeding geese and the surface information of the goose eggs was 97.8%. The experimental results met the requirements of accurate marking of individual information of breeding geese, which can provide technical support for the selection of high-quality breeding geese.

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Note on a method for individual recording of laying performance in groups of hens

Cited by 6 publications

References 6 publications

Preliminary Evaluation of a Nest Usage Sensor to Detect Double Nest Occupations of Laying Hens

Preliminary Evaluation of a Nest Usage Sensor to Detect Double Nest Occupations of Laying Hens

Nest acceptance, clutch, and oviposition traits are promising selection criteria to improve egg production in cage-free system

An IoT-Based Breeding Egg Identification and Coding System for Selection of High-Quality Breeding Geese

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