The synergy between artificial intelligence (AI) and hyperspectral imaging (HSI) holds
tremendous potential across a wide array of fields. By leveraging AI, the processing and …

Machine learning is a widespread technology that plays a crucial role in digitalisation and
aims to explore rules and patterns in large datasets to autonomously solve non-linear …

Weed infestation and their management are a critical production challenge in agricultural
fields. Palmer amaranth has created management challenges because it has multiple …

Grain and forage legumes are important sources of food and feed, key for sustainable
agriculture given the environmental services they provide. However, their cultivation is …

Hyperspectral sensor adaptability in precision agriculture to digital images is still at its
nascent stage. Hyperspectral imaging (HSI) is data rich in solving agricultural problems like …

Sunflower is an annual species of the Asteraceae family, and it occupies a relevant position
in the world market business as one of the most important oilseed crops. Given the current …

Key message This study provided a non-destructive detection method with Vis–NIR
hyperspectral imaging combining with physio-biochemical parameters in Helianthus annuus …

Early detection of non‐optimal weed control is now a priority to ensure herbicide efficacy.
This study aimed to evaluate the potential of hyperspectral imaging (HSI) for early detection …

In this study, we explore spectral heterogeneity within plant canopies, a characteristic often
observed in stressed plants where certain leaves or intra-leaf regions exhibit stress …

Parasitic plants are taxonomically diverse, globally distributed, and capable of parasitizing a
wide array of host plants, often with preferences for specific hosts. Some parasitic plants are …