Collaborative project: Measuring system for an automated early diagnosis of lameness in cattle through analysis of the sound of movement in cattle - subproject 3 | FISA - Forschungsinformationssystem Agrar und Ernährung

Collaborative project: Measuring system for an automated early diagnosis of lameness in cattle through analysis of the sound of movement in cattle - subproject 3

Project

Project code: 2817902215
Contract period: 01.08.2016 - 31.07.2019
Budget: 153,474 Euro
Purpose of research: Experimental development

Animal welfare is one oft he most important quality indicators in livestock production for many consumers and of rapidly growing social relevance. Still measuring animal welfare can be quite difficult. An important factor for animal welfare in cattle farming is the detection of lameness, which is caused by diseases of the claws and limbs. The aim of this project is therefore to develop a system which is capable of an automated early diagnosis of lamness in cattle. The modular design of the proposed system, which consists of a measuring platform and an data evaluation unit, allows the adaptation to all practically relevant forms of husbandry. Therfore it is planned to develop both mobile test stands with coupled hardware or smartphone apps for flexible measurements, as well as a fixed installation. The noise detected by the systems will be analysed directly within its own analysis software,so that the farmer can be given direct management options. The proposed research project is divided into four sections. In the first section, a special test stand and a specific scoring scheme for classifying lameness are developed. In the second phase the developed test stand is used to record walking noises of cattle. To determine the different degrees of lameness, all animals will be classified according to the specially developed scoring scheme. The results from the trial will be incorporated directly into the development of a mobile test stand, which in the third section is testet on working farms and important parameters for the practical feasibility will be identified. This creates a closed and optimization-oriented process cycle. In the fourth and last section the complete system composed of the hardware and software will be tested on farms.

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