Environmental Complexity: Additional Human Visual Contact Reduced Meat Chickens' Fear of Humans and Physical Items Altered Pecking Behavior

Visual access to an outdoor range early in life, but not environmental complexity, increases meat chicken ranging behavior

Not all chickens access an outdoor range when the opportunity is provided. This may be related to the abrupt change in environments from the stable rearing conditions to the complexity of the outdoor range. We aimed to prepare chickens to range by increasing the complexity of the indoor environment early in life with the intention to encourage range use. Mixed sex Cobb500 chickens were allocated to 1 of 3 treatment groups: visual access (VA) treatment provided VA to the outdoor range from day old via transparent pop-hole covers; environmental complexity (EC) treatment provided an artificial haybale, fan with streamers and a solid vertical barrier; Control treatment was a representative conventional environment. Chickens were given access to the outdoor range at 21 d of age. Behavior in the home pen was assessed in wk 1, 2 and 5 and individual ranging behavior was monitored through radio frequency identification (RFID) technology. The VA chickens were more active compared to EC (P = 0.006) and Control (P = 0.007) chickens and spent more time foraging than control chickens (P = 0.036) during the first week of life. More VA chickens accessed the range area compared to EC chickens (P = 0.015). VA chickens accessed the range sooner after they were first provided access and spent more time on the range than EC and control chickens (P < 0.001). Mortality was lower in the VA treatment compared to EC (P = 0.024) and control group (P = 0.002). There was evidence that VA chickens weighed less than Control and EC chickens, however results were inconsistent between age and sex. Hence, providing meat chickens with VA to an outdoor range early in life increased activity in early life, decreased latency to first access the range and increased time on the range and lowered mortality. Future work should aim to understand the mechanism behind these changes in behavior to develop recommendations for producers to implement in commercial conditions.

Enhancing their quality of life: environmental enrichment for poultry

Providing environmental enrichments that increase environmental complexity can benefit poultry welfare. This Poultry Science Association symposium paper is structured around four themes on 1) poultry preferences and affective states 2) species-specific behavior, including play behavior and the relationship between behavior, activity level and walking ability, 3) environmental enrichment and its relationship with indicators of welfare, and 4) a case study focusing on the application of enrichments in commercial broiler chicken production. For effective enrichment strategies, the birds' perspective matters most, and we need to consider individual variation, social dynamics, and previous experience when assessing these strategies. Play behavior can be a valuable indicator of positive affect, and while we do not yet know how much play would be optimal, absence of play suggests a welfare deficit. Activity levels and behavior can be improved by environmental modifications and prior research has shown that the activity level of broilers can be increased, at least temporarily, by increasing the environmental complexity. However, more research on impacts of enrichments on birds' resilience, on birds in commercial conditions, and on slow(er)-growing strains is needed. Finally, incorporating farmers' expertise can greatly benefit enrichment design and implementation on commercial farms.

A High-Precision Method for 100-Day-Old Classification of Chickens in Edge Computing Scenarios Based on Federated Computing

Due to the booming development of computer vision technology and artificial intelligence algorithms, it has become more feasible to implement artificial rearing of animals in real production scenarios. Improving the accuracy of day-age detection of chickens is one of the examples and is of great importance for chicken rearing. This paper focuses on the problem of classifying the age of chickens within 100 days. Due to the huge amount of data and the different computing power of different devices in practical application scenarios, it is important to maximize the computing power of edge computing devices without sacrificing accuracy. This paper proposes a high-precision federated learning-based model that can be applied to edge computing scenarios. In order to accommodate different computing power in different scenarios, this paper proposes a dual-ended adaptive federated learning framework; in order to adapt to low computing power scenarios, this paper performs lightweighting operations on the mainstream model; and in order to verify the effectiveness of the model, this paper conducts a number of targeted experiments. Compared with AlexNet, VGG, ResNet and GoogLeNet, this model improves the classification accuracy to 96.1%, which is 14.4% better than the baseline model and improves the Recall and Precision by 14.8% and 14.2%, respectively. In addition, by lightening the network, our methods reduce the inference latency and transmission latency by 24.4 ms and 10.5 ms, respectively. Finally, this model is deployed in a real-world application and an application is developed based on the wechat SDK.