A Decade Of Expertise In Digital Phenotyping To Support Your Research Endeavors
Our image analysis pipeline ingests images from drones, ground based imaging systems, satellites and uses well-vetted algorithms and AI-powered deep learning modules to calculate an ever growing range of traits as we are always pushing the boundaries of plant phenotyping. Discover below our plant phenotyping portfolio of uses cases to dive deeper into Hiphen's crop assessment expertise. Also, as we have high R&D capabilities, we can develop and provide new traits upon request for your specific application.
This trait refers to the heterogeneity measured from Flower Fraction. The plot studied is first...
The Green Chlorophyll Index is used to calculate the total chlorophyll content of the leaves....
Border Effect: Computed at plant emergence, this trait measures the possibility that a plot development...
QPAR represents the accumulated quantity of PAR (Photosynthetically Active Radiation) intercepted by the plants during...
This trait represents the maximum row length measured between the first and last plant detected...
This trait represents the sum of all row length measured between the first and last...
Greenness (excess green): This trait refers to the intensity of green within the vegetation mask...
Senescence is defined as the percentage of plants that remain green. This trait is robust...
The leaf chlorophyll index (LCI) is a vegetation index involving spectral reflectance characteristics of the...
Simple Ratio is indeed the simplest vegetation index calculated by dividing reflectance recorded in the...
This trait refers to the heterogeneity measured from the Plant Cover calculation. The plot studied...
This trait refers to the heterogeneity measured from the Green Cover calculation. The plot studied...
This trait represents the average row length measured between the first and last plant detected...
Flower cover area refers to the surface of flower pixels within the plot, expressed in...