As global land surface temperature continues to rise and heatwave events increase in
frequency, duration, and/or intensity, our key food and fuel cropping systems will likely face …

Inability to efficiently implement high-throughput field phenotyping is increasingly perceived
as a key component that limits genetic gain in breeding programs. Field phenotyping must …

This paper reviews advanced Neural Network (NN) techniques available to process
hyperspectral data, with a special emphasis on plant disease detection. Firstly, we provide a …

Global food security depends on three main cereal crops (wheat, rice and maize) achieving
and maintaining high yields, as well as increasing their future yields. Fundamental to the …

The word phenotyping can nowadays invoke visions of a drone or phenocart moving swiftly
across research plots collecting high-resolution data sets on a wide array of traits. This has …

Partial least squares regression (PLSR) modelling is a statistical technique for correlating
datasets, and involves the fitting of a linear regression between two matrices. One …

The rate with which crop yields per hectare increase each year is plateauing at the same
time that human population growth and other factors increase food demand. Increasing yield …

Plant phenotyping forms the core of crop breeding, allowing breeders to build on
physiological traits and mechanistic science to inform their selection of material for crossing …

Identifying traits for improving sink strength is a bottleneck to increasing wheat yield. The
interacting processes determining sink strength and yield potential are reviewed and …

Background Hyperspectral reflectance data in the visible, near infrared and shortwave
infrared range (VIS–NIR–SWIR, 400–2500 nm) are commonly used to nondestructively …