Scientific reports
Jun 18, 2024
Globally, tea production and its quality fundamentally depend on tea leaves, which are susceptible to invasion by pathogenic organisms. Precise and early-stage identification of plant foliage diseases is a key element in preventing and controlling th...
Journal of the science of food and agriculture
Jun 15, 2024
BACKGROUND: With the rapid development of deep learning, the recognition of rice disease images using deep neural networks has become a hot research topic. However, most previous studies only focus on the modification of deep learning models, while l...
Environmental science & technology
Jun 11, 2024
Foliar assimilation of elemental mercury (Hg) from the atmosphere plays a critical role in the global Hg biogeochemical cycle, leading to atmospheric Hg removal and soil Hg insertion. Recent studies have estimated global foliar Hg assimilation; howev...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jun 9, 2024
Precision nutrient management in orchard crops needs precise, accurate, and real-time information on the plant's nutritional status. This is limited by the fact that it requires extensive leaf sampling and chemical analysis when it is to be done over...
Brazilian journal of biology = Revista brasleira de biologia
May 24, 2024
C. sintoc is a plant that has a high essential oil content. Essential oils have many health benefits. Mount Ciremai National Park is an area that has abundant vegetation, especially C. sintoc. The purpose of this study was to predict the volume of oi...
Network (Bristol, England)
May 22, 2024
Nowadays, Deep Learning (DL) techniques are being used to automate the identification and diagnosis of plant diseases, thereby enhancing global food security and enabling non-experts to detect these diseases. Among many DL techniques, a Deep Encoder-...
Plant physiology and biochemistry : PPB
May 22, 2024
The primary challenges in tea production under multiple stress exposures have negatively affected its global market sustainability, so introducing an infield fast technique for monitoring tea leaves' stresses has tremendous urgent needs. Therefore, t...
Scientific reports
May 22, 2024
The growth of plants is threatened by numerous diseases. Accurate and timely identification of these diseases is crucial to prevent disease spreading. Many deep learning-based methods have been proposed for identifying leaf diseases. However, these m...
Scientific reports
May 3, 2024
The difficulty of collecting maize leaf lesion characteristics in an environment that undergoes frequent changes, suffers varying illumination from lighting sources, and is influenced by a variety of other factors makes detecting diseases in maize le...
Sensors (Basel, Switzerland)
May 1, 2024
In order to efficiently identify early tea diseases, an improved YOLOv8 lesion detection method is proposed to address the challenges posed by the complex background of tea diseases, difficulty in detecting small lesions, and low recognition rate of ...