Katy Martin Rainey
Agricultural and Biological Sciences · Purdue University West Lafayette
Publications
71
Citations
2,170
Est. group size
~2
Recurring co-author estimate
Active years
22
Publishing since 2004
Katy Martin Rainey's research focuses on soybean genetics and breeding, particularly improving seed quality traits like oil, protein, and carbohydrate content, as well as yield and disease resistance. Her work also incorporates modern technology such as drone-based (UAS) imaging and machine learning to rapidly measure plant traits (a process called phenotyping) for use in breeding programs. This combines traditional crop genetics with data-driven and remote-sensing methods to speed up the development of improved soybean varieties.
Publication output was higher around 2017-2020 and has slowed somewhat in recent years, averaging about 2-3 papers annually over the last five years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Redesigning soybean with improved oil and meal traits
Theoretical and Applied Genetics · 2024
- Presymptomatic Leaf Reflectance of <i>Fusarium virguliforme</i>-Infected Soybean Plants in Greenhouse Conditions
PhytoFrontiers™ · 2024
- Genetic architecture of protein and oil content in soybean seed and meal
The Plant Genome · 2023
- Environmental stability and genetic effect of soybeans differing in mutant allele combinations between <i>rs</i> and <i>mips1</i> genes for soluble carbohydrate profiles
Crop Science · 2023
- Physiological breeding for yield improvement in soybean: solar radiation interception-conversion, and harvest index
Theoretical and Applied Genetics · 2022
- Designing Experiments for Physiological Phenomics
Methods in molecular biology · 2022
- Correction to: Physiological breeding for yield improvement in soybean: solar radiation interception-conversion, and harvest index
Theoretical and Applied Genetics · 2022
- Genetic Relationships Among Physiological Processes, Phenology, and Grain Yield Offer an Insight Into the Development of New Cultivars in Soybean (Glycine max L. Merr)
Frontiers in Plant Science · 2021
- Yield prediction by machine learning from UAS-based multi-sensor data fusion in soybean
Plant Methods · 2020
- Canopy Roughness: A New Phenotypic Trait to Estimate Aboveground Biomass from Unmanned Aerial System
Plant Phenomics · 2020
- Mapping QTL controlling soybean seed sucrose and oligosaccharides in a single family of soybean nested association mapping (SoyNAM) population
Plant Breeding · 2020
- An Efficient Pipeline for Crop Image Extraction and Vegetation Index Derivation Using Unmanned Aerial Systems
Transactions of the ASABE · 2020
- DEEP PHENOTYPING CONSIDERING TILE DRAINAGE FROM UAS-BASED MULTISPECTRAL IMAGERY BY CONVOLUTIONAL NEURAL NETWORKS
The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · 2020
- Yield Prediction by Machine Learning From UAS-Based Multi-Sensor Data Fusion in Soybean
Research Square · 2020
- Yield Prediction By Machine Learning From Uas-Based Multi-Sensor Data Fusion In Soybean
Research Square · 2020
- Crop Science×7
- G3 Genes Genomes Genetics×4
- Frontiers in Plant Science×4
- Theoretical and Applied Genetics×4
- The Plant Genome×3
- Lianjun Sun
Agricultural and Biological Sciences · Purdue University West Lafayette
- Diana M. Escamilla
Agricultural and Biological Sciences · Purdue University West Lafayette
- Weidong Wang
Agricultural and Biological Sciences · Purdue University West Lafayette
- Liyang Chen
Agricultural and Biological Sciences · Purdue University West Lafayette
- Clay Sneller
Agricultural and Biological Sciences · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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