Hyper-spectral NIR and MIR data and optimal wavebands for detection of apple tree diseases
Plant diseases can lead to dramatic losses in yield and quality of food, becoming a problem of high priority for farmers. Apple scab, moniliasis, and powdery mildew are the most significant apple tree diseases worldwide and may cause between 50% and 60% in yield losses annually; they are controlled by fungicide use with huge financial and time expenses. This research proposes a modern approach for analyzing the spectral data in Near-Infrared and Mid-Infrared ranges of the apple tree diseases at different stages. Using the obtained spectra, we found optimal spectral bands for detecting particular disease and discriminating it from other diseases and healthy trees. The proposed instrument will provide farmers with accurate, real-time information on different stages of apple tree diseases, enabling more effective timing, and selecting the fungicide application, resulting in better control and increasing yield. The obtained dataset, as well as scripts in Matlab for processing data and finding optimal spectral bands, are available via the link: https://yadi.sk/d/ZqfGaNlYVR3TUA
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Maize Haploid Identification via LSTM-CNN and Hyperspectral Imaging Technology
Accurate and fast identification of seed cultivars is crucial to plant breeding, with accelerating breeding of new products and increasing its quality. In our study, the first attempt to design a high-accurate identifica…
SASSI -- Super-Pixelated Adaptive Spatio-Spectral Imaging
We introduce a novel video-rate hyperspectral imager with high spatial, and temporal resolutions. Our key hypothesis is that spectral profiles of pixels in a super-pixel of an oversegmented image tend to be very similar.…
Sen2Fire: A Challenging Benchmark Dataset for Wildfire Detection using Sentinel Data
Utilizing satellite imagery for wildfire detection presents substantial potential for practical applications. To advance the development of machine learning algorithms in this domain, our study introduces the \textit{Sen…
Hyperspectral Calibration of Art: Acquisition and Calibration Workflows
Hyperspectral imaging has become an increasingly used tool in the analysis of works of art. However, the quality of the acquired data and the processing of that data to produce accurate and reproducible spectral image cu…
Change DetectionYou Only Train Once: Learning a General Anomaly Enhancement Network with Random Masks for Hyperspectral Anomaly Detection
In this paper, we introduce a new approach to address the challenge of generalization in hyperspectral anomaly detection (AD). Our method eliminates the need for adjusting parameters or retraining on new test scenes as r…
Anomaly DetectionModel Selection