The welfare of layer hens in cage and cage-free housing systems

Hartcher, Kate; Jones, Bidda

doi:10.1017/s0043933917000812

Cited by 74 publications

(70 citation statements)

References 65 publications

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“…The HW hens showed a laying behaviour significantly different from that of HB, as shown by higher percentages at almost all the ages (p < 0.01). Causes affecting this behaviour during the first weeks of activity may be inexperience, while for the later periods this may be due to possible conditions of stress or disturbance among the birds [8,28]. The group size could be a factor affecting the rate of mislaid eggs by hens, as in presence of the same nesting area per hen a less competition for the nest in larger groups should occur, but the results are not conclusive as observed in hens reared in enriched cages and aviaries [24].…”

Section: Egg Defects Of Behavioural and Physiological Originmentioning

confidence: 99%

“…The importance of purebreds is now increasing in industrialized countries as people and rural tourism become more interested in typical food products, with particular characteristics that allow them to distinguish a farm product from an industrial product [4,7]. According to the animals' welfare goals, outdoor rearing conditions allow the hens to better perform their behavioural traits in comparison to intensive production [8,9] and the farms involved in tourism and animal welfare usually rear chickens and hens under outdoor and pasture conditions.…”

Section: Introductionmentioning

confidence: 99%

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Yield Performance, Laying Behaviour Traits and Egg Quality of Purebred and Hybrid Hens Reared under Outdoor Conditions

Rizzi

2020

Animals

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This study compared the yield performance, laying behavioural traits and egg quality of purebred and hybrid hens (from 28 until 44 weeks of age, considering four periods) reared under outdoor conditions. The four genotypes were reared on the same trial station, on four areas (one genotype/area), and under the same environmental conditions from hatching until the end of the trial. Italian dual-purpose purebred (Ermellinata di Rovigo—ER and Robusta maculata—RM) and hybrid (Hy-Line Brown—HB and Hy-Line White 36—HW) hens (flock size: 70 birds/genotype) were allowed outdoors (4 m2/bird, good pasture during the growing period and poor pasture throughout the laying period, according to the season) and indoors (0.20 m2/bird, five birds/individual nest) and fed commercial feed. Significant (p < 0.01) differences among genotypes were found. The hybrids showed a higher laying rate and hen-day edible egg mass, and a lower body weight than the purebreds. Broken and out-of-nest egg% were higher in RM and HW than ER and HB, respectively. Double-yolk egg% was higher in hybrids than in purebreds. The eggshell colour varied among brown eggshell ER, RM, and HB. The ER showed the lowest shape index. With aging, the yolk to albumen ratio linearly increased in all groups, eggshell% changed in ER, HW, RM (cubic) and in HB (linear). The purebreds showed meat spots% higher than blood spots; HW showed the lowest total inclusion%. In conclusion, according to an egg scoring evaluation (egg weight = medium-large size, yolk to albumen ratio = 0.5, total inclusions = none), HW showed a higher quality than HB and RM, and ER was intermediate. The RM hens showed the highest% of defective eggs, especially for overcrowding at nest, HB showed the lowest. Under outdoor conditions the laying behaviour of the purebred hens and the nest management are important factors for the saleable egg rate.

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Section: Egg Defects Of Behavioural and Physiological Originmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Yield Performance, Laying Behaviour Traits and Egg Quality of Purebred and Hybrid Hens Reared under Outdoor Conditions

Rizzi

2020

Animals

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“…Hatcher and Jones (2017) [115] The risk of the emergence and spreading of infectious diseases, as well as feather pecking, is the lowest in non-cage systems.…”

Section: Stadig Et Al (2016) [114]mentioning

confidence: 99%

Sustainability and Quality Aspects of Different Table Egg Production Systems: A Literature Review

Molnár

Szöllősi

2020

Sustainability

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Eggs are of considerable importance in feeding the population, as they are a relatively inexpensive and complex food source of very high biological value. The daily animal protein requirement for the human body can be covered with eggs in the cheapest way and with the lowest environmental impact. As animal welfare, as well as environmental and health awareness issues, become increasingly prominent in developed countries, consumer demand for eggs has also changed significantly in recent years, with an increasing number of consumers buying eggs produced in non-cage housing systems. In recent years, cage housing has been more frequently debated in EU member states. An initiative was launched in 2018 to end cage housing technologies and the sale of eggs produced in this way. However, in addition to animal welfare, a number of other factors need to be considered in relation to sustainable production. For this reason, the aim of this research is to provide a comprehensive overview of the sustainability issues of various housing technologies, as well as quality factors affecting consumer health and egg consumption based on the relevant international references and databases. Although there is a growing demand for products produced in non-cage housing systems due to the increasing relevance of environmental protection, health awareness and animal welfare issues in Western societies, research has shown that non-caged production is not the best solution for environmentally, socially and economically sustainable egg production.

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“…For brown and white egg detection, the RMSE results show that the deviation of the predicted egg center from the actual egg center increased at larger camera heights and tilting angles. Table 5 shows the precision, recall, accuracy, and RMSEs of the faster R-CNN detector for floor egg detection under different light intensities (1,5,10,15, and 20 lux) and litter conditions (w/or w/o feather presence) using the five folds of the validation sets. The detector generally performed greatly at most light intensities; however, the recall and accuracy of the detector for brown egg detection were poor (less than 35%) at the 1-lux light intensity.…”

Section: Generalizability Of the Optimal Cnn Floor-egg Detectormentioning

confidence: 99%

“…The US egg industry is transitioning to alternative hen housing systems due to subpar bird welfare conditions in conventional cage housing systems. Cage-free (CF) housing systems are among the alternative systems that provide hens with larger living spaces and welfare enrichments, such as perches, nestboxes, and litter floor [1]. While hens have accesses to a litter floor in CF systems, they may lay eggs on the floor [2,3], namely floor eggs.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Convolutional Neural Networks for Cage-Free Floor Egg Detection

Zhao

et al. 2020

Sensors

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The manual collection of eggs laid on the floor (or ‘floor eggs’) in cage-free (CF) laying hen housing is strenuous and time-consuming. Using robots for automatic floor egg collection offers a novel solution to reduce labor yet relies on robust egg detection systems. This study sought to develop vision-based floor-egg detectors using three Convolutional Neural Networks (CNNs), i.e., single shot detector (SSD), faster region-based CNN (faster R-CNN), and region-based fully convolutional network (R-FCN), and evaluate their performance on floor egg detection under simulated CF environments. The results show that the SSD detector had the highest precision (99.9 ± 0.1%) and fastest processing speed (125.1 ± 2.7 ms·image−1) but the lowest recall (72.1 ± 7.2%) and accuracy (72.0 ± 7.2%) among the three floor-egg detectors. The R-FCN detector had the slowest processing speed (243.2 ± 1.0 ms·image−1) and the lowest precision (93.3 ± 2.4%). The faster R-CNN detector had the best performance in floor egg detection with the highest recall (98.4 ± 0.4%) and accuracy (98.1 ± 0.3%), and a medium prevision (99.7 ± 0.2%) and image processing speed (201.5 ± 2.3 ms·image−1); thus, the faster R-CNN detector was selected as the optimal model. The faster R-CNN detector performed almost perfectly for floor egg detection under a wide range of simulated CF environments and system settings, except for brown egg detection at 1 lux light intensity. When tested under random settings, the faster R-CNN detector had 91.9–94.7% precision, 99.8–100.0% recall, and 91.9–94.5% accuracy for floor egg detection. It is concluded that a properly-trained CNN floor-egg detector may accurately detect floor eggs under CF housing environments and has the potential to serve as a crucial vision-based component for robotic floor egg collection systems.

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The welfare of layer hens in cage and cage-free housing systems

Cited by 74 publications

References 65 publications

Yield Performance, Laying Behaviour Traits and Egg Quality of Purebred and Hybrid Hens Reared under Outdoor Conditions

Yield Performance, Laying Behaviour Traits and Egg Quality of Purebred and Hybrid Hens Reared under Outdoor Conditions

Sustainability and Quality Aspects of Different Table Egg Production Systems: A Literature Review

Evaluating Convolutional Neural Networks for Cage-Free Floor Egg Detection

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