WeChat Mini Program
Old Version Features

Animal Welfare and Biosecurity Correlation in Buffalo Farm Evaluated by ClassyFarm System

Revista Científica(2023)

Cited 0|Views0
Abstract
ClassyFarm is an integrated system for categorizing farms according to the risk assessment (RA) methodology. It is an Italian innovation aimed at improving the synergy between breeders and competent authorities to improve the safety and quality of food of animal origin. ClassyFarm gathers and processes data referred to in the following areas: biosecurity, animal welfare, health, and antimicrobial usage. It can be applied to livestock species, including water buffaloes. Upon request of the Italian Ministry of Health (IMH), the National Reference Centre on Water Buffalo Farming and Production Hygiene and Technologies (CreNbuf), in collaboration with the Italian Reference Centre for Animal Welfare (CreNBA), developed a RA-based checklist (CL) for the on-farm assessment of buffalo welfare and farm biosecurity level, included in the ClassyFarm system. The multiple- choice CL consists of 79 items. Each item is scored according to 3 categories: “insufficient”, “acceptable” and “excellent”. The assessment system for animal welfare includes non-animal-based (N-ABMs) and animal-based measures (ABMs). N-ABMs are divided into two macro-areas: Area A (32 items): “Management factors” and Area B (31 items): “Housing factors”. ABMs are assessed in Area C (17 items). Biosecurity was assessed using 15 indicators. The CL has been tested in 102 farms, with an average size of 412 heads. On average, the overall welfare value was 61.55% (on a scale from 0 to 100%), and the average biosecurity score was 43.31%. The statistical analysis was performed by Spearman Rank correlation coefficient using GraphPad Prism 8.0.1. (GraphPad Software, San Diego, CA, USA). The two variables were positively correlated (Spearman’s Rho=0.501; p<0.001). The average welfare values of the specific areas were: A, 61.76%; B, 42.17%; C, 70.43%. At least one potential legislative non-compliance was recorded in 39.80% of the farms. The highest correlations between the different areas of well-being and biose-curity are found for the management areas, highlighting how management is essential to ensure both the levels of well-being and those of biosecurity. These CLs represent a functional and effective tool to assign animal welfare and biosecurity indexes to farms, improving farm management and housing conditions, giving answers to consumers, and adding value to farmers’ good practices. The IMH is promoting the application of this system at European and international levels.
More
Translated text
Key words
animal welfare,biosecurity,buffalo,Classyfarm
求助PDF
上传PDF
Bibtex
收藏
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined