학술논문
Analysis of the Factors Influencing Body Weight Variation in Hanwoo Steers Using an Automated Weighing System
Document Type
Report
Author
Source
Animals (Basel). August 2020, Vol. 10 Issue 8
Subject
Language
English
ISSN
2076-2615
Abstract
1. Introduction The body weight (BW) of animals represents their physiological status and growth rate and is an important basis on which animal management strategies are decided. In the field, [...]
Simple Summary: The body weight (BW) of animals is an important indicator of their physiological status and productivity. The BW of animals varies from day to day and even within a day due to various factors. However, these variations have not been fully tested because it is challenging to measure the BW of animals repeatedly at various time points. This study used an automated weighing scale (AWS) to overcome these difficulties and generated a large number of BW measurements. We found that differences between individual animals had the greatest impact on BW deviations in Hanwoo steers. Additionally, it was found that changes in the BW of Hanwoo steers during the day were influenced by feeding patterns. To the best of our knowledge, this is the first study to report the diurnal pattern of changes in the BW of Hanwoo steers. Our results suggest that variations in individual animals and their feeding patterns need to be considered when applying precision-farming technologies with real-time BW measurements in cattle. This study aimed to determine the factors affecting the body weight (BW) of Hanwoo steers by collecting a large number of BW measurements using an automated weighing system (AWS). The BW of 12 Hanwoo steers was measured automatically using an AWS for seven days each month over three months. On the fourth day of the BW measurement each month, an additional BW measurement was conducted manually. After removing the outliers of BW records, the deviations between the AWS records (a) and manual weighing records (b) were analyzed. BW measurement deviations (a - b) were significantly (p < 0.05) affected by month, day and the time within a day as well as the individual animal factor; however, unexplained random variations had the greatest impact (70.4%). Excluding unexplained random variations, the difference between individual steers was the most influential (80.1%). During the day, the BW of Hanwoo steers increased before feed offerings and significantly decreased immediately after (p < 0.05), despite the constant availability of feeds in the feed bunk. These results suggest that there is a need to develop pattern recognition algorithms that consider variations in individual animals and their feeding patterns for the analysis of BW changes in animals. Keywords: analysis of variance components; automated weighing system; Hanwoo
Simple Summary: The body weight (BW) of animals is an important indicator of their physiological status and productivity. The BW of animals varies from day to day and even within a day due to various factors. However, these variations have not been fully tested because it is challenging to measure the BW of animals repeatedly at various time points. This study used an automated weighing scale (AWS) to overcome these difficulties and generated a large number of BW measurements. We found that differences between individual animals had the greatest impact on BW deviations in Hanwoo steers. Additionally, it was found that changes in the BW of Hanwoo steers during the day were influenced by feeding patterns. To the best of our knowledge, this is the first study to report the diurnal pattern of changes in the BW of Hanwoo steers. Our results suggest that variations in individual animals and their feeding patterns need to be considered when applying precision-farming technologies with real-time BW measurements in cattle. This study aimed to determine the factors affecting the body weight (BW) of Hanwoo steers by collecting a large number of BW measurements using an automated weighing system (AWS). The BW of 12 Hanwoo steers was measured automatically using an AWS for seven days each month over three months. On the fourth day of the BW measurement each month, an additional BW measurement was conducted manually. After removing the outliers of BW records, the deviations between the AWS records (a) and manual weighing records (b) were analyzed. BW measurement deviations (a - b) were significantly (p < 0.05) affected by month, day and the time within a day as well as the individual animal factor; however, unexplained random variations had the greatest impact (70.4%). Excluding unexplained random variations, the difference between individual steers was the most influential (80.1%). During the day, the BW of Hanwoo steers increased before feed offerings and significantly decreased immediately after (p < 0.05), despite the constant availability of feeds in the feed bunk. These results suggest that there is a need to develop pattern recognition algorithms that consider variations in individual animals and their feeding patterns for the analysis of BW changes in animals. Keywords: analysis of variance components; automated weighing system; Hanwoo