scholarly journals Enhancing the value of meat inspection records for broiler health and welfare surveillance: longitudinal detection of relational patterns

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
S. N. Buzdugan ◽  
P. Alarcon ◽  
B. Huntington ◽  
J. Rushton ◽  
D. P. Blake ◽  
...  

Abstract Background Abattoir data are under-used for surveillance. Nationwide surveillance could benefit from using data on meat inspection findings, but several limitations need to be overcome. At the producer level, interpretation of meat inspection findings is a notable opportunity for surveillance with relevance to animal health and welfare. In this study, we propose that discovery and monitoring of relational patterns between condemnation conditions co-present in broiler batches at meat inspection can provide valuable information for surveillance of farmed animal health and welfare. Results Great Britain (GB)-based integrator meat inspection records for 14,045 broiler batches slaughtered in nine, four monthly intervals were assessed for the presence of surveillance indicators relevant to broiler health and welfare. K-means and correlation-based hierarchical clustering, and association rules analyses were performed to identify relational patterns in the data. Incidence of condemnation showed seasonal and temporal variation, which was detected by association rules analysis. Syndrome-related and non-specific relational patterns were detected in some months of meat inspection records. A potentially syndromic cluster was identified in May 2016 consisting of infection-related conditions: pericarditis, perihepatitis, peritonitis, and abnormal colour. Non-specific trends were identified in some months as an unusual combination of condemnation reasons in broiler batches. Conclusions We conclude that the detection of relational patterns in meat inspection records could provide producer-level surveillance indicators with relevance to broiler chicken health and welfare.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Cynthia Schuck-Paim ◽  
Elsa Negro-Calduch ◽  
Wladimir J. Alonso

AbstractSocietal concern with the welfare of egg laying hens housed in conventional cages is fostering a transition towards cage-free systems in many countries. However, although cage-free facilities enable hens to move freely and express natural behaviours, concerns have also been raised over the possibility that cage-free flocks experience higher mortality, potentially compromising some aspects of their welfare. To investigate this possibility, we conducted a large meta-analysis of laying hen mortality in conventional cages, furnished cages and cage-free aviaries using data from 6040 commercial flocks and 176 million hens from 16 countries. We show that except for conventional cages, mortality gradually drops as experience with each system builds up: since 2000, each year of experience with cage-free aviaries was associated with a 0.35–0.65% average drop in cumulative mortality, with no differences in mortality between caged and cage-free systems in more recent years. As management knowledge evolves and genetics are optimized, new producers transitioning to cage-free housing may experience even faster rates of decline. Our results speak against the notion that mortality is inherently higher in cage-free production and illustrate the importance of considering the degree of maturity of production systems in any investigations of farm animal health, behaviour and welfare.


2020 ◽  
Vol 82 ◽  
pp. 161-169
Author(s):  
Norton E. Atkins ◽  
Keith E. Walley ◽  
Liam A. Sinclair

The majority of dairy cattle in Great Britain (GB) are housed during winter but replacement heifers are out-wintered on some farms, a practice that may reduce the need for high capital-cost housing and facilitate herd expansion. Dairy farmers that were out-wintering replacement heifers in GB in 2012 were surveyed to determine current practice and attitudes. A typical system involved heifers strip grazing pasture or a crop, with baled grass silage as supplementary feed; strongly resembling outdoor wintering systems in New Zealand. Many used more than one grazed forage; predominantly, pasture on 68%, kale on 53% and fodder beet on 33% of farms. Supplementary feed was 44% of the diet in younger, and 35% in older heifers. Although farms were approximately three times larger than the national average and 60% were expanding, expanding herd size was not the primary reason for out-wintering, with the main reasons being to reduce cost and improve animal health and welfare. Farmers that out-wintered heifers typically reported good animal average dairy gain of 0.6 kg/d and high body condition, however, this contrasts with some measured performance in GB. Farmers may benefit from accurate feed allocation and monitoring heifer live weight during winter to ensure high performance.  


Author(s):  
Yoonju Lee ◽  
Heejin Kim ◽  
Hyesun Jeong ◽  
Yunhwan Noh

The authors have noticed an inadvertent error in our article, ‘‘Patterns of Multimorbidity in Adults: An Association Rules Analysis Using the Korea Health Panel” [...]


2020 ◽  
Vol 7 ◽  
Author(s):  
Agnes Agunos ◽  
Sheryl P. Gow ◽  
David F. Léger ◽  
Anne E. Deckert ◽  
Carolee A. Carson ◽  
...  

2012 ◽  
Vol 9 (10) ◽  
Author(s):  
Jo Hardstaff ◽  
Annette Nigsch ◽  
Niko Dadios ◽  
Katharina Stärk ◽  
Silvia Alonso ◽  
...  

2014 ◽  
Vol 2 (1) ◽  
pp. 16-28 ◽  
Author(s):  
Wei Xu ◽  
Jiajia Wang ◽  
Ziqi Zhao ◽  
Caihong Sun ◽  
Jian Ma

AbstractAs one of the financial industries, the insurance industry is now facing a vast market and significant growth opportunities. The insurance company will generate a lot transaction data each day, thus forming a huge database. Recommending insurance products for customers accurately and efficiently can help to improve the competitiveness of insurance company. Data mining technologies such as association rules have been applied to the recommendation of insurance products. However, large policyholders’ data will be calculated when it being processed with associate rule algorithm. It not only requires higher cost of time and space, but also can lead to the final rules lack of accuracy and differentiation. In this paper, a recommendation model for insurance products based on consumer segmentation is constructed, which first divides consumer group into different classes and then processed with associate rule algorithm. The empirical results show that our proposed method not only makes the consumption of association rules analysis reduced, it has also got more effective product recommendation results.


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