Publications by authors named "Mohammed BenAouda"

This study highlights the importance of monitoring cattle feeding behavior using the YOLO algorithm for object detection. Videos of six Charolais bulls were recorded on a French farm, and three feeding behaviors (biting, chewing, visiting) were identified and labeled using Roboflow. YOLOv8 and YOLOv10 were compared for their performance in detecting these behaviors.

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Japanese black Wagyu cattle are renowned for producing some of the world's most highly valued and recognized beef with exceptional marbling. Therefore, the primary focus of genetic selection for Wagyu cattle has historically been on meat quality, particularly achieving high marbling levels. However, even when the price of the final product is high, production costs also remain high, especially considering that most of the feed has to be imported.

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In recent years, machine learning (ML) algorithms have emerged as powerful tools for predicting and modeling complex data. Therefore, the aim of this study was to evaluate the prediction ability of different ML algorithms and a traditional empirical model to estimate the parameters of lactation curves. A total of 1186 monthly records from 156 sheep lactations were used.

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This paper aims to describe the construction and operation of a respiration chamber of the head-box type for methane (CH) measurements in bovines. The system consists of (1) a head box with a stainless steel frame and acrylic walls, floor, and ceiling; (2) a stainless steel feeder; (3) an automatic drinking water bowl; (4) a hood made from reinforced canvas; (5) an infrared (IR) CH gas analyzer, a mass flow generator, a data-acquisition system; and (6) a steel metabolic box. Six assays were conducted to determine the pure CH recovery rate of the whole system in order to validate it and comply with standards of chamber operation.

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