牛のバッファローバエ負荷を評価するための従来の視覚スコアリングとデジタルオブジェクト計数アプローチの比較

Buffalo fly (Haematobia irritans exigua) is recognised for its impact on cattle health, welfare, and production. It is ranked the number one endemic pest for the Australian beef cattle industry by Meat and Livestock Australia. An accurate estimation of fly numbers is essential to evaluate treatment efficacy, phenotyping of susceptible animals for genetic improvement and determining threshold levels to guide integrated pest management strategies. Traditionally, fly numbers are estimated through visual scoring which is inherently challenging as it involves estimating moving flies on a restless host. This study used digital photography and an open-source, semi-automated software package DotDotGoose to count fly numbers on individual animal images. These were then compared to the visual fly scores on the same animals. A random selection of 98 images was used and fly numbers were counted on these images in duplicate by four assessors, one experienced field researcher and three novice assessors. The fly counts on individual images were analysed for consistency and agreement and a consistency and agreement of 99 % was achieved within the four assessors, classified as excellent. The analysis further showed that visual assessments and manual visual counts by experienced assessors consistently underestimated fly numbers compared to the digital image counts. Our results suggest that a digital counting platform offers a more reliable alternative to visual scoring for buffalo fly counts. It improves accuracy and consistency and enables remote image analysis, lowers time and labour costs, and provides the potential for automated real-time monitoring and reporting of fly numbers.