Design of a Multispectral and Thermal Data Acquisition System for High-Throughput Phenotyping of Plant Pathology

Early detection of plant disease is a challenging research topic in crop protection and precision agriculture. Progress in remote sensing, embedded sensors and AI has enabled researchers to develop innovative data processing algorithms and models to predict plant disease symptoms. However, continuous research is required to update and develop new solutions for detecting plant disease early in the infection. It requires extensive experimentation and timelapse collection of data with different imaging sensors, platforms, plant samples, and environmental conditions before developing a robust model. This paper proposes a conceptual design of an apparatus that can be used for data collection from different imaging sensors to perform high-throughput phenotyping and analysis for early plant disease diagnosis. The paper includes two different design concepts for two distinct scenarios of data collection, 1. on-field standalone device; and 2. laboratory desktop apparatus. Each design is explained with various operational and technical considerations, an electronic block diagram and a mechanical 3D sketch. The paper aims to provide a generic design of an apparatus to enable researchers worldwide to carry out phenotypic studies and develop innovative solutions to benefit the end-user, i.e., the farmer, and reduce global economic and environmental losses.