Drought stress (DS) is one of the most frequently occurring stresses in tomato plants. Detecting tomato plant DS is vital for optimizing irrigation and improving fruit quality. In this study, a DS identification method using the multi-features of hyperspectral imaging (HSI) and subsample fusion was proposed. First, the HSI images were measured under imaging condition with supplemental blue lights, and the reflectance spectra were extracted from the HSI images of young and mature leaves at different DS levels (well-watered, reduced-watered, and deficient-watered treatment). The effective wavelengths (EWs) were screened by the genetic algorithm. Second, the reference image was determined by ReliefF, and the first four reflectance images of EWs that are weakly correlated with the reference image and mutually irrelevant were obtained using Pearson's correlation analysis. The reflectance image set (RIS) was determined by evaluating the superposition effect of reflectance images on identification. The spectra of EWs and the image features extracted from the RIS by LeNet-5 were adopted to construct DS identification models based on support vector machine (SVM), random forest, and dense convolutional network. Third, the subsample fusion integrating the spectra and image features of young and mature leaves was used to improve the identification further. The results showed that supplemental blue lights can effectively remove the high-frequency noise and obtain high-quality HSI images. The positive effect of the combination of spectra of EWs and image features for DS identification proved that RIS contains feature information pointing to DS. Global optimal classification performance was achieved by SVM and subsample fusion, with a classification accuracy of 95.90% and 95.78% for calibration and prediction sets, respectively. Overall, the proposed method can provide an accurate and reliable analysis for tomato plant DS and is hoped to be applied to other crop stresses.
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http://dx.doi.org/10.3389/fpls.2023.1073530 | DOI Listing |
Sensors (Basel)
November 2024
College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266000, China.
A driver in road hypnosis has two different types of characteristics. One is the external characteristics, which are distinct and can be directly observed. The other is internal characteristics, which are indistinctive and cannot be directly observed.
View Article and Find Full Text PDFAnimals (Basel)
November 2024
Department of Electrical Engineering, North Carolina State University, 890 Oval Dr., Raleigh, NC 27695, USA.
Guide dogs play a crucial role in enhancing independence and mobility for people with visual impairment, offering invaluable assistance in navigating daily tasks and environments. However, the extensive training required for these dogs is costly, resulting in a limited availability that does not meet the high demand for such skilled working animals. Towards optimizing the training process and to better understand the challenges these guide dogs may be experiencing in the field, we have created a multi-sensor smart collar system.
View Article and Find Full Text PDFJ Cogn Psychother
July 2024
Fairleigh Dickinson University, Teaneck, NJ, USA.
Increased emphasis has been placed on elucidating the contribution of client variables, such as treatment preference, to optimize evidence-based practice. This analog study sought to better understand variables associated with treatment preference using a convenience sample of college students ( = 54) who read brief descriptions of three interventions for negative thoughts-defusion, noticing, and restructuring. They rated each on acceptability and practicality and completed measures of cognitive fusion, emotional distress, and experiential avoidance as possible moderating variables.
View Article and Find Full Text PDFMed Biol Eng Comput
September 2024
Computer Science and Engineering, Thapar Institute of Engineering & Technology, Patiala, 147004, Punjab, India.
This paper proposes a medical image fusion method in the non-subsampled shearlet transform (NSST) domain to combine a gray-scale image with the respective pseudo-color image obtained through different imaging modalities. The proposed method applies a novel improved dual-channel pulse-coupled neural network (IDPCNN) model to fuse the high-pass sub-images, whereas the Prewitt operator is combined with maximum regional energy (MRE) to construct the fused low-pass sub-image. First, the gray-scale image and luminance of the pseudo-color image are decomposed using NSST to find the respective sub-images.
View Article and Find Full Text PDFBrain Spine
March 2024
Department of Trauma and Reconstructive Surgery, BG Klinikum Bergmannstrost Halle, Germany.
Introduction: Percutaneous techniques for the surgical treatment of vertebral fractures are constantly progressing. There are different biomechanics involved.
Research Question: Two percutaneous, monoaxial fixation systems with different reduction tools were analyzed in relation to their reduction capacity.
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