The first paradigm of plant breeding involves direct selection-based phenotypic observation,
followed by predictive breeding using statistical models for quantitative traits constructed …

Plant phenomics is a new avenue for linking plant genomics and environmental studies,
thereby improving plant breeding and management. Remote sensing techniques have …

Computer vision (CV) combined with a deep convolutional neural network (CNN) has
emerged as a reliable analytical method to effectively characterize and quantify high …

Plant phenomics (PP) has been recognized as a bottleneck in studying the interactions of
genomics and environment on plants, limiting the progress of smart breeding and precise …

Optical sensors and sensing-based phenotyping techniques have become mainstream
approaches in high-throughput phenotyping for improving trait selection and genetic gains …

Genotyping platforms, as critical supports for genomics, genetics, and molecular breeding,
have been well implemented at national institutions/universities in developed countries and …

Plant phenotyping is important for plants to cope with environmental changes and ensure
plant health. Imaging techniques are perceived as the most critical and reliable tools for …

Automated machine learning (AutoML) has been heralded as the next wave in artificial
intelligence with its promise to deliver high-performance end-to-end machine learning …

Dissecting the genetic basis of complex traits such as dynamic growth and yield potential is
a major challenge in crops. Monitoring the growth throughout growing season in a large …

In contrast to the rapid advances made in plant genotyping, plant phenotyping is considered
a bottleneck in plant science. This has promoted high-throughput plant phenotyping (HTP) …