Mobile app for targeted selective treatment of haemonchosis in sheep

Abstract

Livestock is an important part of many countries gross domestic product, and sanitary control impacts herd management costs. To contribute to incorporating new technologies into this economic chain, this work presents a mobile application for decision assistance to treatment against parasitic infection by Haemonchus contortus in small ruminants. Based on the Android system, the proposed software is a semi-automated computer-aided procedure to assist Famacha© pre-trained farmers in applying anthelmintic treatment. It mimics the two-class decision procedure performed by the veterinarian with the help of the Famacha© card. The embedded cell phone camera was employed to acquire an image from the ocular conjunctival mucosa, classifying the animal as healthy or anemic. Two machine-learning strategies were assessed, resulting in an accuracy of 83 % for a neural network and 87 % for a support vector machine (SVM). The SVM classifier was embedded into the app and made available for evaluation. This work is particularly interesting to small property owners from regions with difficult access or restrictions on obtaining continuous post-training technical guidance to use the Famacha© method effectively.