What is Phenomics?
Phenomics is a modern field at the intersection of science and technology, connecting biology in all its forms with IT and hardware. Its goal is to deeply analyze phenotype traits and the process of their formation during growth and development, and patterns of change in response to the environment. This is done in all kingdoms of life, but plant phenomics is the most advanced thanks to genetic diversity and the practical importance of plants.What Does Phenomics Measure and Study?
Its main subjects are agricultural, ornamental and medicinal plants, of all sizes, in laboratory, greenhouse and field conditions. Phenotyping allows automatic and objective measurement, almost without human bias, of both external signs and deep indicators: size and quantity of leaves/fruits depending on diseases or irrigation; change in chlorophyll fluorescence in drought; shape of root system in different genetic lines.
Such observations reveal basic laws of traits important to humans, for example the balance between leaves and flowers under different conditions, and enable more accurate selection – for example to choose rare-colored orchids and propagate them.
The most important use is in agriculture: there are solutions that analyze open satellite data using AI and show where in fields irrigation is lacking, where fertilization is needed and where diseases are developing – so the farmer can respond immediately. This reduces costs, increases yield and reduces chemical use.
Hardware
Phenomics has raised plant biology to a new level thanks to imaging and analysis technologies. Modern fast and automatic imaging systems combine a lot of information about plant parameters and its response in real time.
Sensors sensitive to different ranges from UV to IR are used: regular, fluorescent, thermal, hyperspectral imaging; sometimes CT, MRI, PET, laser/3D scans.
Visible cameras measure shape and size of shoots, growth dynamics, seed morphology and root system. This is critical for yield assessment and early pathogen detection. Fluorescent imaging detects pathologies and genetic sensitivity; thermal imaging (IR) provides surface temperature for examining respiration and water evaporation. Hyperspectral enables assessment of biomass, macro/micro-elements, pigments and photosynthetic activity.
Information Technologies in Phenomics
The huge amounts of data from sensors cannot be processed manually, so the field depends on specialized software, especially computer vision algorithms and machine learning.
There are hundreds of tools, databases and models. There are also proprietary systems from major manufacturers. Neural networks for phenomics are developing rapidly and will push out classical processing systems in the future.
Popular free software: ImageJ (with hundreds of plugins), platforms like Image Analysis Platform or HTPheno; Rosette Tracker for Arabidopsis. OpenCV – a free computer vision library with thousands of algorithms – is used in platforms like SmartGrain and Bellwether and even in major centers like Wageningen. There are also additional packages like JMicrovision or BioImageXD that can serve the field.
Innovation in sensors, robotics and data analytics enables huge HR data. Computer vision has made phenotype measurement a precise, fast and non-destructive tool. Algorithms identify plant boundaries, separate it from background, filter noise and extract regions by parameters: to determine fruit ripeness, detect diseases at an early stage, select the tallest plants for further propagation, etc.
Machine Learning
This is a family of AI methods based on statistics and learning from examples, enabling gradual improvement. One tool – neural networks, including convolutional networks (CNN) for image recognition.
CNNs perform convolution and pooling stages; used for recognition, classification, data compression, associative memory, prediction and decision making.
They are very common in plant biology: U‑Net, LeNet, DenseNet, ResNet, VGG, Inception and more. They are used to identify genotype‑phenotype relationships, growth tracking, stress responses, and also in field phenomics – for seed material assessment, yield prediction, detection of key life cycle stages.
The progress of phenotyping in recent decades stems from leaps in sensors, automation, and IT – computer vision, machine and deep learning. The quantity and quality of data far exceed classical measurements. Phenomics can lead to creating digital models of vitality, productivity and stress resistance processes at the organism and population level. It enables precision agriculture: targeted seed selection, minimum chemicals and maximum yield – thanks to adopting advanced IT products.
