Floor Eggs Research Articles

Conditions contributing to the incidence of floor eggs in commercial cage-free egg production in Australia

Conditions contributing to the incidence of floor eggs in commercial cage-free egg production in Australia

Floor eggs in goose breeders: patterns, genetic and environmental influences, and physiological indexes

A floor egg is an egg that is not laid in the nest, which is a prevalent issue in many fowl breeder farms, lowering egg collection efficiency, hatching performance, and economic benefits. Although the pattern and influencing factors of floor laying have been extensively reported in chickens and ducks, it is not clear in geese. Herein, the Yangzhou goose breeders were selected, and the time and location preferences, genetic and environmental influences, and physiological indexes in floor laying were investigated. The results revealed distinct time and location preferences existed. More floor eggs were laid from 2:00 to 5:00 and 8:00 to 12:00 am, with a concentration observed in the feed trough. Moreover, the proportion of floor eggs was higher at the early stage than at other stages of the laying cycle, and the fast-growing line laid more floor eggs than dual-purpose and high-yielding lines (P < 0.05). In addition to genetic factors, the effect of environmental influences on floor eggs was also surveyed. More floor eggs were observed in the family housing system than in large-group and small-population housing systems, and geese who reared in north-facing houses laid more floor eggs than in south-facing houses (P < 0.05). Physiological indexes were compared between floor-laying and nest-laying geese. Significantly decreased serum progesterone and prolactin levels were detected, alongside down-regulated gene expressions of progesterone receptor in ovaries, oxytocin receptor in both pituitary and ovaries, corticotropin-releasing hormone in ovaries, and dopamine receptor D2 in hypothalamus and ovaries in floor-laying geese compared to nest-laying geese (P < 0.05). In addition, a practical and inexpensive approach of adding a single decoy egg to the nest box effectively reduced the proportion of floor eggs (P < 0.05). Taken together, these data provide scientific information for patterns, genetic and environmental influences, and physiological indexes of floor eggs, thereby contributing to effective control of floor laying in goose breeders' production.

The Effect of Hatching Eggs Sanitization and Flock Age on Microbial Load and Hatchability Parameters

Chick performance and hatchability are adversely affected by microbial contamination of hatching eggs. Egg disinfection is therefore crucial to limiting bacterial numbers and optimizing production. The present study was applied to detect the effect of hatching eggs spraying (nest and floor) with two commercial disinfectants: A (H2O2, peracetic and acetic acid) and B (glutraldehyde and Benzalkonium chloride) on hatching parameters and eggshell microbial counts. Hatching eggs were collected from broiler breeder flocks at different ages (37, 47 and 57 weeks). The obtained results indicated that both disinfectants reduced the levels of bacteria in similar ways, but there were no significant differences between them. Concerning the hatching parameters; hatchability percentages (total and true) were lower than standard in both nest and floor eggs, and higher hatchability percentages were found in eggs sanitized with disinfectant A. However, the lowest values were reported in eggs of 57 weeks old breeders with both disinfectants. Conclusively, disinfectants A and B reduced the microbial load of hatching eggs of different ages, and some hatchability parameters were affected with flock age and the used disinfectants.

Providing elevated structures in the pullet rearing environment affects behavior during initial acclimation to a layer aviary

Spatial abilities of hens are particularly sensitive to development during early life. Experiences in pullet housing may have lasting consequences on adult hens' movements in cage-free environments. We tested whether opportunities to access elevated spaces during rearing improved hens' use of a multitiered aviary. Female Dekalb White pullets were reared in either floor pens (FL), single-tiered aviaries (ST), or 2-tiered aviaries (TT; n=5 pens/environment) through 16 wk of age. Rearing structures were replaced with identical multitiered aviaries at 17 wk. The distribution of the flock within the aviary and the vertical transitions of 10 focal hens/pen across the aviary were determined from videos recorded during their first (D1) and seventh (D7) day of aviary access, as well as at 19, 23, and 27 wk of age. Prevalence of floor eggs was recorded weekly from 17 to 28 wk of age. On D1, more ST and TT hens utilized the aviary during the daytime (P=0.0077), made more vertical transitions when searching for a roosting spot in the evening (P=0.0021), and maintained a consistent distance traveled during transitions compared to FL hens (P=0.02). These differences disappeared by D7, except that ST and TT hens continued to roost on the highest perches of the aviary more (P < 0.0001) than FL hens through 27 wk of age. FL hens laid more floor eggs than ST and TT hens for the first 2 wk of lay (P < 0.0001). The majority (97.9%) of vertical transitions was controlled. Uncontrolled transitions were highest at D1 and decreased by D7 (P=0.0009) and were not affected by rearing (P=0.33). The results suggest that hens reared with minimal height are hesitant to use the laying hen aviaries when they are first transferred. They acclimate within 1 to 2 wk, but continue to roost less in the highest accessible level.

A Computer Vision-Based Automatic System for Egg Grading and Defect Detection.

Defective eggs diminish the value of laying hen production, particularly in cage-free systems with a higher incidence of floor eggs. To enhance quality, machine vision and image processing have facilitated the development of automated grading and defect detection systems. Additionally, egg measurement systems utilize weight-sorting for optimal market value. However, few studies have integrated deep learning and machine vision techniques for combined egg classification and weighting. To address this gap, a two-stage model was developed based on real-time multitask detection (RTMDet) and random forest networks to predict egg category and weight. The model uses convolutional neural network (CNN) and regression techniques were used to perform joint egg classification and weighing. RTMDet was used to sort and extract egg features for classification, and a Random Forest algorithm was used to predict egg weight based on the extracted features (major axis and minor axis). The results of the study showed that the best achieved accuracy was 94.8% and best R2 was 96.0%. In addition, the model can be used to automatically exclude non-standard-size eggs and eggs with exterior issues (e.g., calcium deposit, stains, and cracks). This detector is among the first models that perform the joint function of egg-sorting and weighing eggs, and is capable of classifying them into five categories (intact, crack, bloody, floor, and non-standard) and measuring them up to jumbo size. By implementing the findings of this study, the poultry industry can reduce costs and increase productivity, ultimately leading to better-quality products for consumers.

Effects of Perching on Poultry Welfare and Production: A Review

Perching is one of the essential natural behaviors for avian species. Providing an optimal perching design (e.g., shape, dimension, and materials) for commercial poultry production is critical for maintaining bird health, welfare, and production efficiency. This review paper summarized poultry perching studies and discussed the relationship between perch design, bird welfare, and production efficiency. Providing perches at an early stage may ensure optimum use during adulthood, reduce perching accidents, and lower the risk of floor eggs in cage-free (CF) hen houses. Therefore, a perch space of 15 cm per bird is recommended for the CF hen house. Similarly, rectangular perches are preferred to circular perches as the rectangular perch provides hens with an excellent tendon-locking mechanism to prevent slipping. In addition, perches with softer materials such as polyurethane and rubber coverings are recommended to increase the contact surface on the chicken’s toes. Perching behavior (PB) promotes a musculocutaneous system and reduces the incidences of footpad dermatitis and lesions. Generally, providing perching may reduce aggression and stress in birds and improve welfare and production efficiency. In the case of broilers, it is found that the broiler perches less during the latter stage of their lives because they are comparatively heavier and exhibit a more inactive lifestyle. Studies have investigated the effect of the surface temperature of the perch on broilers’ welfare. Perches with lower temperatures help improve performance and welfare by relieving heat stress and leg issues. Overall, PB is required to improve bird health and welfare.

Tracking floor eggs with machine vision in cage-free hen houses

Some of the major restaurants and grocery chains in the United States have pledged to buy cage-free (CF) eggs only by 2025 or 2030. While CF house allows hens to perform more natural behaviors (e.g., dust bathing, perching, and foraging on the litter floor), a particular challenge is floor eggs (i.e., mislaid eggs on litter floor). Floor eggs have high chances of contamination. The manual collection of eggs is laborious and time-consuming. Therefore, precision poultry farming technology is necessary to detect floor eggs. In this study, 3 new deep learning models, that is, YOLOv5s-egg, YOLOv5x-egg, and YOLOv7-egg networks, were developed, trained, and compared in tracking floor eggs in 4 research cage-free laying hen facilities. Models were verified to detect eggs by using images collected in 2 different commercial houses. Results indicate that the YOLOv5s-egg model detected floor eggs with a precision of 87.9%, recall of 86.8%, and mean average precision (mAP) of 90.9%; the YOLOv5x-egg model detected the floor eggs with a precision of 90%, recall of 87.9%, and mAP of 92.1%; and the YOLOv7-egg model detected the eggs with a precision of 89.5%, recall of 85.4%, and mAP of 88%. All models performed with over 85% detection precision; however, model performance is affected by the stocking density, varying light intensity, and images occluded by equipment like drinking lines, perches, and feeders. The YOLOv5x-egg model detected floor eggs with higher accuracy, precision, mAP, and recall than YOLOv5s-egg and YOLOv7-egg. This study provides a reference for cage-free producers that floor eggs can be monitored automatically. Future studies are guaranteed to test the system in commercial houses.

Fear, anxiety, and production in laying hens with healed keel bone fractures

For laying hens, the immediate aftermath and healing period of a keel fracture (KF) is characterized by reduced ability to perform species-specific behavior, access resources, and pain. However, the longer-term impacts, once the fracture is completely healed, are less clear. As well as acute pain and behavioral changes, a negative experience can shape future responses to putatively threatening stimuli, raising future fear, and anxiety levels during husbandry-related events. We aimed to determine whether hens that had previously sustained keel bone fractures, but were now outside of the peak age range for new fractures, showed higher fear and anxiety levels compared to intact hens. We also determined if healed keel bone fractures were associated with reduced production, changes in behavior and resource use. One hundred and fifty hens with a palpation score of 1 ( "KF") and 150 hens with a palpation score of 0 (keel fracture free, "KFF") were selected from a commercial farm at 63 wk of age and housed in 6 groups (3×KF and 3×KFF). We compared production (hen weight and feed consumption, egg quantity, quality and weight, floor eggs, shell thickness, and weight) and home pen behavior (behaviors and transitional movements) in both groups. Finally, we measured the responses of KF (n=75) and KFF (n=75) during tonic immobility, novel arena, and novel object tests. KF and KFF hens did not differ in their responses to the tonic immobility, novel arena, and novel object tests, nor were there differences between the 2 groups in home pen behavior and transitional movements. KFF birds were lighter and laid eggs with less eggshell membrane compared KF birds, but no differences were found between KF and KFF in any other production measures. We found no evidence that healed KFs were associated with detrimental welfare effects in laying hens, but further work is required to determine the mechanisms and implications of the lower body weight and egg shell membrane.

An approach for goose egg recognition for robot picking based on deep learning

ABSTRACT 1. In a non-cage environment, goose eggs are buried in litter and goose feathers, leading to contamination and discolouration. Such random distribution of goose eggs poses a great challenge to the recognition and location for intelligent picking by robot systems on farm. 2. In order to assist in recognition and location of goose eggs in non-cage environments, a novel method was proposed which used three-channel convolutional neural network (T-CNN), composed of improved AlexNet, combined with ‘you only look once’ (YOLOv5), egg contour curve creation and support vector machine (SVM). 3. Using this method, the original goose egg images were put into the YOLOv5 model for target detection and segmentation. In parallel, the median filter and maximum interclass variance method (OTSU) were applied to egg segmentation images to obtain the main pixels for each, and the Kirsch operator was used for edge extraction and contour curves fitting by designing the fitting curve equation to obtain segmentation images with goose egg contour curves. 4. In order to further enrich the differences between goose eggs and background, the goose egg segmentation images were divided into three colour components: R, G and B, which were put into T-CNN for feature extraction. Then the eggs were classified by vector stitching and SVM, by adding goose egg contour curve images. 5. The recognition and location results showed that about 95.65% of the goose egg pixel blocks in the segmented images were recognised correctly. About 3.81% of the pixel blocks in the segmented images were recognised incorrectly, and the centre of mass offset was about 4.45 pixels. 6. This study demonstrated accurate goose egg recognition and location using the proposed method in a non-cage environment. This highlighted its application prospect in intelligent goose egg picking as well as a possible method to use in other species laying eggs outside the nest (floor eggs) as for example laying hens in non cage systems.

Nest preference and laying duration traits to select against floor eggs in laying hens

BackgroundFloor eggs, which are defined as eggs that hens lay off-nest, are a major issue in cage-free layer poultry systems. They create additional work for farmers because they must be collected by hand. They are also usually soiled or broken, which results in economic losses. Nonetheless, knowledge about the genetics of nesting behavior is limited. The aim of this study was to estimate genetic parameters for traits related to nest preference for laying and to time spent in the nests used for laying (laying duration).MethodsTwo pure lines of laying hens were studied: 927 Rhode Island Red and 980 White Leghorn. Electronic nests were used to record the nesting behavior of these hens in floor pens from 24 to 64 weeks of age. Nest preference was studied based on the mean distance between nests used for laying and the percentage of nests used for laying. Laying duration was studied based on mean laying duration, mean duration in the nest before laying, and mean duration in the nest after laying. Genetic parameters were estimated for each line using a restricted maximum-likelihood method applied to a pedigree-based multi-trait animal model.ResultsEstimates of genetic parameters were similar for the two lines. Estimates of heritability ranged from 0.18 to 0.37 for nest preference traits and from 0.54 to 0.70 for laying duration traits. Estimates of genetic correlations of these traits with clutch number or mean oviposition time were favorable. Positive genetic correlations were estimated between nest preference and laying rate in the nests or nest acceptance for laying (+ 0.06 to + 0.37).ConclusionsThese results show that genetics influences traits related to nest preference and laying duration. Selecting hens that have no preference for particular nests and spend little time laying in the nests could help optimize nest use, reduce their occupation rate, and thus decrease the incidence of floor eggs in cage-free systems. Genetic correlations of these traits with other traits of interest related to hen welfare and egg quality have yet to be estimated.

Factors affecting space use by laying hens in a cage-free aviary system: effect of nest lighting at pullet housing and of curtain nest color during laying

At 17 wk of age, 1,800 Lohman brown hens were housed in 8 pens of an experimental aviary system, specifically set up for the purposes of the present study, and kept until 26 wk without or with nest lighting (lights inside the nest 1.5 h before the lighting of the installation) for training in the nest use. Then, at 27 wk, 4 combinations of nest curtains were adopted to evaluate the effects on hens' distribution, that is, nests with red (RR) or yellow (YY) curtains at all tiers; nests with red and yellow curtains at the first and second tier, respectively (RY); or nests with yellow and red curtains at the first and second tier, respectively (YR). The use of enlightened compared to dark nests at housing increased the oviposition rate (P < 0.001) and decreased the rate of broken (P < 0.001) and dirty eggs (P < 0.05) from 27 to 45 wk, while increasing the rate of eggs laid inside the nests (P < 0.001). The presence of yellow nest curtains increased the rate of hens on the floor in pens YY and YR compared to pens RR and RY (35.3 and 35.5% vs. 34.1 and 33.3%, respectively; P=0.05) and the rate of floor eggs in pens YR (2.23% vs. 1.63 and 1.65% in pens RR and RY; P < 0.05). In pens RY, a higher rate of eggs was always found on the second tier compared to the first one with the most inhomogeneous distribution compared to pens RR, YY, and YR (+10.8 vs. +3.4, +1.9, and +4.6 percentage points of eggs laid on the second tier compared to the first one, respectively). In conclusion, nest lighting at housing trained hens to the use of nests while improving egg production in terms of quantity and quality. The use of yellow curtains on nests moved hens between the different levels of the aviary but this was not associated with an increased nest use for laying.

Effects of Energy and Protein Levels on Laying Performance, Egg Quality, Blood Parameters, Blood Biochemistry, and Apparent Total Tract Digestibility on Laying Hens in an Aviary System.

This study was performed to investigate the effects of apparent metabolizable energy (AMEn) and protein levels on laying performance, egg quality, blood parameters, blood biochemistry, and apparent total tract digestibility of energy and nutrients in diets fed to laying hens in an aviary system. A total of 560 Hy-Line Brown laying hens (age = 30 week) were distributed in a completely randomized experimental design in 2 × 2 factorial arrangements with 2 metabolizable energy levels (2700 and 2800 kcal AMEn/kg) and 2 protein levels (16.5 and 14.5% CP). Four treatments and four replicates of 40 birds each (stocking density = 15 birds/m2) were prepared. Results revealed no significant interaction between AMEn and CP in the diet in terms of egg production, floor eggs, broken and dirty egg production, egg mass, feed intake, and feed conversion ratio of laying hens. However, egg weight was affected. As dietary energy and CP levels (2800 kcal of AMEn/kg and 16.5% CP) increased, egg weight increased (p &lt; 0.05). Egg weight, feed intake, and feed conversion ratio significantly differed (p &lt; 0.05) as the energy content in the feed increased. Ether extract significantly varied (p &lt; 0.05) as the energy content in the feed increased. In conclusion, laying performance and egg quality of Hy-Line Brown laying hens in the middle stage of egg production (30 to 50 weeks) were not affected by different dietary energy and protein levels, but feed intake decreased with an increasing level of AMEn in diets. Ether extract significantly varied as the energy content in the feed increased.

Floor eggs: Hatchability, microbiological analysis, and effects of post-hatch use of ceftiofur on performance of broiler chicks

The present study aimed to determine the effects of egg type (nest clean or floor eggs) on eggshell microbiological, hatching performance, chick quality, yolk sac microbiology, and the interaction between egg type and post-hatch use of ceftiofur on broiler performance at 7, 14, 21, 28 and 35 days. A total of 2500 fertile eggs were obtained from a commercial flock of Cobb Slow® broiler breeders. Half of the eggs were collected directly from the floor, and the other half were collected from the nests. Microbiological evaluation of eggshells was performed before and after sanitization. After hatching, 420 male chicks were randomly selected and distributed in a completely randomized design in a 2 × 2 factorial scheme, separated by the type of egg (clean nest or floor) and the inclusion or not of subcutaneous ceftiofur, totaling four treatments. Egg type did not influence hatchability although the contamination level was 1.3% higher. The body weight and body weight gain of chicks at seven days were greater for chicks from nest eggs that received ceftiofur than chicks from floor eggs that also received ceftiofur. There was no interaction between the studied factors or individual effects for performance at 14, 21, 28, and 35 days. It is concluded that incubation of floor eggs, after standard sanitization, does not influence the hatch results and chick quality. Furthermore, it has been proven that the use of ceftiofur is unnecessary when there is correct management during broiler rearing.

Effect of perch access on perching, health and production outcomes in commercial broiler breeder flocks

There is a need for more knowledge about perch use in broiler breeders and the potential effects of perches on health and production outcomes. The aim of this study was to investigate the use of perches by commercial broiler breeders, effect of perch access on keel bone fractures (KBF), footpad dermatitis (FPD) and number of floor eggs. Two commercial breeder flocks (Ross 308) reared at the same facility were observed during the production period. Half of each flock was provided with 15 cm perch/bird and the other half had no perches. The perch group had two types of perches; a steel plate mounted on the hen feeder lines “feeder perch” (15 cm high) and elevated plastic perches (5 cm high). Perching by hens and roosters was recorded during the dark period by counting birds on each of the two perch types in 10 sections and in the corresponding patches on the control side at 25, 35, and 45 wk of age (WOA). FPD was scored in 100 random hens in each group at 30 WOA and end of lay, KBF was scored by postmortem in 100 random hens in each group at end of lay, and number of floor eggs (n) in each treatment was scored daily. More hens perched on the feeder perch with the steel plate mounted, compared to the feeder line without the steel plate, but this difference decreased with age (P < 0.0001). Within the perch treatment, more hens perched on the feeder lines compared to the plastic perches at all ages (P < 0.0001). When combining number of hens on the plastic and feeder perches, on average 6.7 birds perched per meter perch, which is full capacity given an average shoulder width of 15 cm/bird. Perch use among the roosters was low overall, but more roosters perched in the perch group compared to the control group at 35 WOA (P = 0.007). Between 47 and 53% of the hens had KBF at the end of the lay. At 30 WOA, birds housed with perches were more likely to have lower FPD. Perch treatment did not affect number of floor eggs. In conclusion, broiler breeder hens perch when the perches are sufficiently high and allow all birds to perch simultaneously, and access to perches may have positive effects on FPD.

Effects of flock age, place of oviposition and cleaning treatments of hatching eggs on hatchability in broiler breeders

Floor eggs are of economical importance within the broiler breeder industry since they are less suitable for the incubation because of the higher risk of contamination and lower hatchability. The aim of this study was to establish the effects of the flock age and place of oviposition on hatching parameters, and to show whether cleaning practices can improve the incubation results of floor eggs. A total of 4,950 eggs were collected from 3 commercial Cobb 500 breeder flocks at the age of 29 and 64 wk. Eggs were divided into groups depending on the place of oviposition (nest eggs, floor eggs or eggs laid in the nest and put on the floor after cooling). Floor eggs were further divided on eggs with visually clean or dirty shells. Dirty floor eggs were cleaned either by washing or brushing the eggshell. After incubation the basic hatching parameters were measured (fertility, egg weight loss, embryo mortality, contaminated eggs, hatching percentage) as well as the day-old chick weight and length. The results showed that hatchability rate deteriorates with advancing bird age and that place of egg cooling is a critical point for contamination. Eggs cooling down on the floor have a higher risk of contamination than eggs cooling down in the nest. Clean floor eggs had significantly higher degree of contamination compared to nest eggs. It is established that brushing the shell of floor eggs can reduce their contamination and early embryonic mortality in young flocks, although this reduction did not significantly affect the overall hatchability.

Exposure to a Virtual Environment Induces Biological and Microbiota Changes in Onset-of-Lay Hens

Increasing demand for cage-free eggs arises from goals to provide hens with better welfare, particularly in terms of natural behavior. However, most laying hens are kept in conventional cages, and cage-free systems can present challenges, such as injuries, floor eggs, and bacterial infections. We proposed using virtual reality (VR) as a feasible means for combining the positive attributes of natural environments while mitigating health risks. To our knowledge, no animal study has provided evidence that VR can trigger biological changes to improve animal health and well-being nor whether VR can affect the gut microbiota. In this study, we used VR technology to simulate a natural environment in laying hen housing. Early-lay White Leghorn hens were placed in pens with (VR) or without (CON) video projections displaying free-range chickens interacting with indoor and outdoor environmental features over 5 days. Using in vitro blood bactericidal assays, VR hens exhibited higher resistance against avian pathogenic Escherichia coli versus CON (p &amp;lt; 0.05), which was positively associated with corticosterone levels (p &amp;lt; 0.01). Analyzing intestinal neurochemicals via ultra-high pressure liquid chromatography, salsolinol was the only neurochemical metabolite affected by VR, being greater in CON ileal content (p &amp;lt; 0.0001), in VR ileal mucus (p &amp;lt; 0.01), and in VR ceca tissue (p &amp;lt; 0.05). Using 16S rRNA sequencing and QIIME2 analyses, no differences in alpha nor beta diversity were determined between groups. Although several genera (Megamonas, Ruminococcus, Slackia) were reduced in VR hens versus CON, Mucispirillum schaedleri (member of Deferribacteres Phylum) was the only taxon increased in VR hens, being elevated in ileal mucus (p &amp;lt; 0.05). Lastly, using the QIIME2 plugin mmvec to map microbe-metabolite co-occurrences, we identified several positive relationships between bacterial phyla and neurochemical metabolites, notably finding dopamine and salsolinol levels were related to Deferribacteres and Tenericutes levels. In conclusion, we found that several biological parameters were influenced by VR treatment in hens, suggesting that VR can be used to improve host resistance to pathogens and gut health in poultry.

Why-Oh-Why? Dark Brooders Reduce Injurious Pecking, Though Are Still Not Widely Used in Commercial Rearing of Layer Pullets.

Simple SummaryDark brooders mimic some aspects of maternal care, such as the provision of heat and a dark resting area. Dark brooders have a long-lasting reducing effect on injurious pecking, which improves feather cover and reduces mortality due to cannibalism into adulthood. The economic benefits include a reduction of costs for heating in the first weeks of life, and in adult layers, they improve the total egg production and may reduce floor egg laying. Despite the well-accepted knowledge of the positive effects of dark brooders on the prevention of injurious pecking, few farmers actually use them in their rearing facilities. In this paper, we review the effects of dark brooders on the welfare of pullets and layers and discuss the factors that likely contribute to their low usage in commercial systems, including the lack of commercially available brooder options and the size of the brooders, as well as the lack of information on the direct economic aspects.Dark brooders, i.e., horizontal heating elements for chicks equipped with curtains, mimic some aspects of maternal care, such as the provision of heat and a dark area for chicks to rest. Thus, they can be considered as artificial passive replacements of a mother hen. Despite their advantages in animal welfare and the likely positive outcomes in production and economy, dark brooders are rarely used in commercial layer pullet facilities. The main positive effect on welfare is a reduction of injurious pecking during the rearing and laying periods, which results in improved feather cover and reduced skin injuries and mortality due to cannibalism. Other welfare benefits include improved rest in dark-brooded chicks and reduced fearfulness at all ages tested (i.e., from 4 to 26 weeks). The impact on production and economy is seen in a reduction of the energy costs in the first weeks of life due to radiant heating, as well as improved total egg production and reduced floor egg laying. The aim of this paper is to review the existing literature on the effects of dark brooders on injurious pecking and other welfare issues in layers, including speculations on the possible explanations for improved welfare. We also discuss the possible reasons for why dark brooders are not applied more commonly in commercial practice, including insufficient information on the economic aspects of using brooders and the lack of commercially available brooder options.

Effects of ground robot manipulation on hen floor egg reduction, production performance, stress response, bone quality, and behavior.

Reducing floor eggs in cage-free (CF) housing systems is among primary concerns for egg producers. The objective of this research was to evaluate the effects of ground robot manipulation on reduction of floor eggs. In addition, the effects of ground robot manipulation on production performance, stress response, bone quality, and behavior were also investigated. Two successive flocks of 180 Hy-Line Brown hens at 34 weeks of this age were used. The treatment structure for each flock consisted of six pens with three treatments (without robot running, with one-week robot running, and with two-weeks robot running), resulting in two replicates per treatment per flock and four replicates per treatment with two flocks. Two phases were involved with each flock. Phase 1 (weeks 35-38) mimicked the normal scenario, and phase 2 (weeks 40-43) mimicked a scenario after inadvertent restriction to nest box access. Results indicate that the floor egg reduction rate in the first two weeks of phase 1 was 11.0% without the robot treatment, 18.9% with the one-week robot treatment, and 34.0% with the two-week robot treatment. The effect of robot operation on floor egg production was not significant when the two phases of data were included in the analysis. Other tested parameters were similar among the treatments, including hen-day egg production, feed intake, feed conversion ratio, live body weight, plasma corticosterone concentration, bone breaking force, ash percentage, and time spent in nest boxes. In conclusion, ground robot operation in CF settings may help to reduce floor egg production to a certain degree for a short period right after being introduced. Additionally, robot operation does not seem to negatively affect hen production performance and well-being.

45 Imaging and Phenotyping Technologies for Poultry Welfare Evaluation

Abstract United States is currently the world’s largest broiler producer and the second largest egg producer (e.g., poultry and eggs had a sale value of $40 billion in 2021), but poultry and egg productions are facing grand challenges of animal welfare concerns, food safety issues, and environmental impacts. The rapid growth rate of broilers is associated with welfare concerns such as leg issues and lameness. Broilers with lameness suffer behavior restrictions, physical discomforts, and impingement of fundamental freedoms. Those welfare concerns have triggered the attention of the general public and the food industry to improve broiler well-being, and well-being evaluation. Animal welfare evaluation is currently performed manually by farm workers daily or occasionally in the poultry houses, which is time consuming, labor intensive, and subject to human errors. This task calls for the design of an automated system that can monitor poultry welfare automatically. Sensing technologies, such as ultra-wideband, radio frequency identification, accelerometer, and computer vision-based monitoring, have been and are being adapted and tested for livestock and poultry farming systems to aide well-being evaluation. Computer vision-based phenotyping technologies have been tested efficient in monitoring large animals such as cattle and pigs. However, it is technically challenging to monitor smaller animals such as broiler and layer chickens. Researchers at the University of Georgia are developing specific imaging and phenotyping technologies (e.g., deep learning models) for monitoring/tracking floor distribution patterns of broiler chickens and individual birds’ moving in different zones of feeding, drinking, and resting. The imaging technologies have also been applied to monitor laying hen’s behaviors of perching, pecking, and floor egg laying in the cage-free houses. Those imaging and phenotyping technologies will be further innovated for developing integrative sensing systems to evaluate poultry welfare indicators in commercial broiler and cage-free layer houses.

Floor Eggs: Hatchability, Microbiological Analysis, and Effects of Post-Hatch Use of Ceftiofur on Performance of Broiler Chicks

Floor Eggs: Hatchability, Microbiological Analysis, and Effects of Post-Hatch Use of Ceftiofur on Performance of Broiler Chicks