Deep learning (DL), a subset of machine learning approaches, has emerged as a versatile
tool to assimilate large amounts of heterogeneous data and provide reliable predictions of …

Plant stress phenotyping is essential to select stress-resistant varieties and develop better
stress-management strategies. Standardization of visual assessments and deployment of …

Background Hyperspectral imaging is emerging as a promising approach for plant disease
identification. The large and possibly redundant information contained in hyperspectral data …

Unmanned aircraft system (UAS) is a particularly powerful tool for plant phenotyping, due to
reasonable cost of procurement and deployment, ease and flexibility for control and …

The soybean cyst nematode (SCN), Heterodera glycines, is the most damaging pathogen of
soybeans in the United States. To assess the severity of nematode infestations in the field …

Background Root system architecture (RSA) traits are of interest for breeding selection;
however, measurement of these traits is difficult, resource intensive, and results in large …

Plant parasitic nematodes (PPNs) cause an important class of diseases that occur in almost
all types of crops, seriously affecting yield and quality and causing great economic losses …

Digitalization and automation of assessments in field trials are established practice for
farming product development. The use of image-based methods has provided good results …

Nematodes are among the most diverse but least studied organisms. The classic
morphology-based identification has proved insufficient to the study of nematode …

Soybeans play a key role in global food security. US soybean yields, which comprise 32% of
the total soybeans planted in the world, continue to experience unprecedented grain loss …