PDF(Pubmed)
Abstract：
Behavior analysis is a widely used non-invasive tool in the practical production routine, as the animal acts as a biosensor capable of reflecting its degree of adaptation and discomfort to some environmental challenge. Conventional statistics use occurrence data for behavioral evaluation and well-being estimation, disregarding the temporal sequence of events. The Generalized Sequential Pattern (GSP) algorithm is a data mining method that identifies recurrent sequences that exceed a user-specified support threshold, the potential of which has not yet been investigated for broiler chickens in enriched environments. Enrichment aims to increase environmental complexity with promising effects on animal welfare, stimulating priority behaviors and potentially reducing the deleterious effects of heat stress. The objective here was to validate the application of the GSP algorithm to identify temporal correlations between heat stress and the behavior of broiler chickens in enriched environments through a proof of concept. Video image collection was carried out automatically for 48 continuous hours, analyzing a continuous period of seven hours, from 12:00 PM to 6:00 PM, during two consecutive days of tests for chickens housed in enriched and non-enriched environments under comfort and stress temperatures. Chickens at the comfort temperature showed high motivation to perform the behaviors of preening (P), foraging (F), lying down (Ld), eating (E), and walking (W); the sequences <{Ld,P}>; <{Ld,F}>; <{P,F,P}>; <{Ld,P,F}>; and <{E,W,F}> were the only ones observed in both treatments. All other sequential patterns (comfort and stress) were distinct, suggesting that environmental enrichment alters the behavioral pattern of broiler chickens. Heat stress drastically reduced the sequential patterns found at the 20% threshold level in the tested environments. The behavior of lying laterally \"Ll\" is a strong indicator of heat stress in broilers and was only frequent in the non-enriched environment, which may suggest that environmental enrichment provides the animal with better opportunities to adapt to stress-inducing challenges, such as heat.
摘要：
行为分析是在实际生产中广泛使用的非侵入性工具,因为动物充当生物传感器，能够反映其对某些环境挑战的适应和不适程度。常规统计使用发生数据进行行为评估和幸福感估计，无视事件的时间顺序。广义序列模式（GSP）算法是一种数据挖掘方法，用于识别超过用户指定支持阈值的循环序列，在丰富的环境中，尚未对肉鸡的潜力进行研究。浓缩旨在增加环境复杂性，对动物福利产生有希望的影响，刺激优先行为，并可能减少热应激的有害影响。这里的目的是通过概念证明来验证GSP算法的应用，以识别热应激与丰富环境中肉鸡行为之间的时间相关性。连续48小时自动采集视频图像,分析连续七个小时的时间，从12:00PM到6:00PM,在连续两天的测试中，在舒适和压力温度下饲养在丰富和非丰富环境中的鸡。在舒适的温度下，鸡表现出很高的动机来执行打扮（P）的行为，觅食（F），躺下（Ld），吃（E），和行走(W)；序列<{Ld，P}>;<{Ld,F}>;<{P,F,P}>;<{Ld,P,F}>;和<{E,W,F}>是在两种处理中观察到的唯一的。所有其他顺序模式（舒适和压力）是不同的，表明环境富集改变了肉鸡的行为模式。在测试环境中，热应力大大降低了在20％阈值水平下发现的顺序模式。横向躺着“Ll”的行为是肉鸡热应激的强烈指标，仅在非富集环境中频繁出现，这可能表明环境的丰富为动物提供了更好的机会来适应压力引发的挑战，如热。
