Assess the Diversity of Parental Lines and Their Resilience to Stress
Digital phenotyping (canopy temperature, spectral stress indices, vigor, senescence dynamics) characterizes parental diversity and stress resilience to guide crossing decisions.
Use Cases for the Whole Ecosystem
Digital crop assessment use cases from multiple environments, vectors & crops. Image analysis powered by Hiphen Intelligence.
Use Cases for Plant Breeding
DiscoverAccelerate your selection decisions with more repeatable, objective, and scalable digital traits, while paving the way toward phenomic prediction.
Key value delivered by Hiphen
- Higher selection pressure Applied from the earliest breeding stages
- Less experimental noise Objective scoring, free of rater-to-rater drift
- Earlier culling Drop non-promising genotypes sooner
- Standardized traits & analytics Comparable across trials, sites and years
- Integrated in your pipeline From nursery screens to registration trials
Digital Traits to Correct End-of-Season Yield with Plot-truth Evidence
End-of-season imagery builds a plot-truth record (stand establishment, canopy uniformity, lodging extent, senescence) and flags plots whose development is inconsistent with their measured yield.
Speed to Flowering Assessment for Better Yield Estimation
Automated phenology tracking dates flowering plot by plot (onset, flower density, BBCH progression) to improve yield estimation and maturity grouping, with no manual walkthrough.
Use Cases for Agro-Inputs Testing
DiscoverObjectively quantify your product performance using validated traits that are measured consistently and are fully comparable across trials, application rates, and environments.
Key value delivered by Hiphen
- Dose-response precision Product efficacy quantified to product rate
- Robust benchmarking Treatments compared against commercial references
- Multi-site stability Response consistency across environments
- Dossier-ready evidence Objective, statistically exploitable efficacy data
- Visual proof Real-world evidence of the product impact on crop
Time Series Analysis to Link Plant Traits to Harvest Quality in One Place
Repeated drone flights track canopy development on every plot, and Cloverfield links each time series to the quality measured on tubers, roots and vegetables at harvest.
Organ Morphology Assessment Straight from the Field
In-field imaging quantifies organ dimensions, shape descriptors, color and defect indicators on every genotype, producing repeatable morphology data without harvesting a sample.
Predict Disease Resilience in Vegetable Trials from Aerial Imagery
Repeated aerial imaging scores disease severity, green-cover retention and senescence non-destructively and reconstructs the epidemic curve for each plot.
Use Cases for Production Fields & OFE
DiscoverManage production fields at the individual field scale using a multi-vector approach that combines multiple data sources to better decide where to observe, where to intervene, and how to anticipate harvest outcomes.
Key value delivered by Hiphen
- Multi-vector imaging Several data sources fused in one single interface
- Smarter scouting Multi-layer data fusion to track scouting operations at scale
- Digital plant traits Quantified traits at scale, not just heterogeneity maps
- Harvest logistics Harvest windows and yield potential, computed at field scale
- Dashboards & APIs All you need to integrate phenotyping data into your system
Identify Best Product Usage Guidelines in Strip Trials before Commercialization
Plant-level phenotyping delivers precise morphology, architecture and vigor traits in strip and non-plot trials to define product usage guidelines before commercialization.
Predict Harvest Date to Optimize Logistics & Resources
Repeated imaging tracks maturity indicators, senescence and phenological progression across all fields and converts these dynamics into field-level harvest-date forecasts.
Identify Best Sampling Zones at Production Field Level
Field-scale imagery maps in-field variability (vegetation indices, biomass, canopy vigor) and delineates homogeneous management zones to define representative sampling zones.
Use Cases for Post-Harvest Quality Control
DiscoverTransform raw agricultural materials into objective data to better manage logistics, enhance quality valorization, and secure industrial decision-making.
Key value delivered by Hiphen
- Objective grading Reduce bias in your quality assessment
- High-throughput control Get more data without limitating your processing flow
- Industrial-grade models Consistent data generated all day every day
- Better material valuation Individuals valued on what they really are
- Traceable quality From the field to the processing line and beyond
Shelf-life & Fruit Degradation Scoring (R&D)
Samples are imaged under identical conditions on a fixed schedule; color change, shrinkage, blemishes and decay are scored to predict degradation rates and shelf-life.
Grape Harvest Quality Scoring to Optimize Logistics
Reception imaging scores incoming grapes for color, bunch morphology and ripeness proxies, producing an objective quality grade for every crate and parcel.
Score Card Generation to Rank Raw Material Quality at the Processing Facility (Linen Fibers)
Imaging at the reception line assesses color, morphology and homogeneity in a calibrated setup and compiles them into a standardized score card for each incoming batch of flax fibers.
