Harnessing the power of machine learning for crop improvement and sustainable production

SMH Khatibi, J Ali - Frontiers in Plant Science, 2024 - frontiersin.org
Crop improvement and production domains encounter large amounts of expanding data
with multi-layer complexity that forces researchers to use machine-learning approaches to …

Research on species identification of wild grape leaves based on deep learning

B Pan, C Liu, B Su, Y Ju, X Fan, Y Zhang, L Sun… - Scientia …, 2024 - Elsevier
There are more than 70 species of Vitis in the world, and 40 species, 1 subspecies and 13
varieties of Vitis native from China. Wild grapes are diverse and complex, and it is difficult to …

An improved YOLOv5 method for clam seedlings biological feature detection under the microscope

Y Zhao, J Fan, Y Jiang, X Guo, W Gou, W Wen… - … and Electronics in …, 2023 - Elsevier
In order to monitor the early growth status of clam seedlings and meet the demands of
precision seedling cultivation in a factory setting, this study improves the YOLOv5s model …

Automatic localization of image semantic patches for crop disease recognition

H Li, H Zhang, J Zhao, L Huang, C Ruan, Y Dong… - Applied Soft …, 2024 - Elsevier
Crop disease recognition plays a crucial role in agricultural production. However, disease
images are large in scale and have a lot of redundant information, which reduces the …

[HTML][HTML] Identification of varieties in Camellia oleifera leaf based on deep learning technology

Z Dong, F Yang, J Du, K Wang, L Lv, W Long - Industrial Crops and …, 2024 - Elsevier
Camellia oleifera, a woody oil tree, is widely recognized for its valuable oil. Different cultivars
of C. oleifera exhibit distinct growth characteristics, oil content, and oil composition …

YOLO-RDS: An efficient algorithm for monitoring the uprightness of seedling transplantation

X Jin, X Zhu, L Xiao, M Li, S Li, B Zhao, J Ji - Computers and Electronics in …, 2024 - Elsevier
During the mechanized transplanting process, the planting angle and standing posture of
seedlings are essential factors in evaluating the survival of the planting, and the uprightness …

From Organelle Morphology to Whole-Plant Phenotyping: A Phenotypic Detection Method Based on Deep Learning

H Liu, H Zhu, F Liu, L Deng, G Wu, Z Han, L Zhao - Plants, 2024 - mdpi.com
The analysis of plant phenotype parameters is closely related to breeding, so plant
phenotype research has strong practical significance. This paper used deep learning to …

A deep multi-task learning approach to identifying mummy berry infection sites, the disease stage, and severity

H Qu, C Zheng, H Ji, R Huang, D Wei, S Annis… - Frontiers in Plant …, 2024 - frontiersin.org
Introduction Mummy berry is a serious disease that may result in up to 70 percent of yield
loss for lowbush blueberries. Practical mummy berry disease detection, stage classification …

IPMCNet: A Lightweight Algorithm for Invasive Plant Multiclassification

Y Chen, X Qiao, F Qin, H Huang, B Liu, Z Li, C Liu… - Agronomy, 2024 - mdpi.com
Invasive plant species pose significant biodiversity and ecosystem threats. Real-time
identification of invasive plants is a crucial prerequisite for early and timely prevention. While …

Maize leaf disease recognition based on improved MSRCR and OSCRNet

P Wang, Y Xiong, H Zhang - Crop Protection, 2024 - Elsevier
Accurate identification of maize pests and diseases plays a crucial role in the growth and
yield of maize. The recognition method of maize leaf diseases based on deep learning is …