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

Assessing crop production in the field often requires breeders to wait until the end of the
season to collect yield-related measurements, limiting the pace of the breeding cycle. Early …

Genomics and high throughput phenomics have the potential to revolutionize the field of
wheat (Triticum aestivum L.) breeding. Genomic selection (GS) has been used for predicting …

Integrating high-throughput phenoty** (HTP) based traits into phenomic and genomic
selection (GS) can accelerate the breeding of high-yielding and climate-resilient wheat …

Predicting phenotypes from a combination of genetic and environmental factors is a grand
challenge of modern biology. Slight improvements in this area have the potential to save …

The application of remote sensing in plant breeding can provide rich information about the
growth processes of plants, which leads to better understanding concerning crop yield. It has …

Accurate predictions and representations of plant growth patterns in simulated and
controlled environments are important for addressing various challenges in plant phenomics …

Leaf area index (LAI) is an essential indicator for crop growth monitoring and yield
prediction. Real-time, non-destructive, and accurate monitoring of crop LAI is of great …

Vegetation indices (VIs) are produced as a combination of different reflectance bands that
are captured by multispectral images (MSIs). These indices, such as normalized difference …

Multispectral (MS) imaging enables the measurement of characteristics important for
increasing the prediction accuracy of genotypic and phenotypic values for yield‐related …