Françoise Dalprá Dariva
Agricultural and Biological Sciences · The Ohio State University
Publications
30
Citations
155
Est. group size
—
Recurring co-author estimate
Active years
9
Publishing since 2017
This researcher works in plant breeding and crop science, focusing on crops such as tomato, pea, chickpea, carrot, and pepper. Much of the work involves identifying genes and traits linked to disease resistance, drought tolerance, and seed or fruit quality, often combining genetics with tools like machine learning, remote sensing, and imaging to speed up plant evaluation (a process called high-throughput phenotyping). This research could suit students interested in combining molecular genetics, plant physiology, and data-driven breeding techniques.
Publication output has grown somewhat unevenly over the past decade, with a low point around 2018 followed by increased and more consistent output from 2019 onward, peaking in 2024.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Improving estimation of days to maturity in field pea using RGB aerial imagery and machine learning
The Plant Phenome Journal · 2025
- Effect of biostimulants on root yield and quality of carrots across different growing seasons
New Zealand Journal of Crop and Horticultural Science · 2025
- Multi‐trait multi‐environment genomic prediction of preliminary yield trial in pulse crop
The Plant Genome · 2024
- Tomato families possessing resistance to late blight also display high-quality fruit
Acta Scientiarum Agronomy · 2024
- Identification of novel candidate genes for Ascochyta blight resistance in chickpea
Scientific Reports · 2024
- High-Throughput Phenotyping of Seed Quality Traits Using Imaging and Deep Learning in Dry Pea
bioRxiv (Cold Spring Harbor Laboratory) · 2024
- Multi-trait multi-environment genomic prediction of preliminary yield trials in pulse crops
bioRxiv (Cold Spring Harbor Laboratory) · 2024
- Identification of novel candidate genes for Ascochyta blight resistance in chickpea
Research Square · 2024
- Uncovering tomato candidate genes associated with drought tolerance using Solanum pennellii introgression lines
PLoS ONE · 2023
- Combining deep learning and X-ray imaging technology to assess tomato seed quality
Scientia Agricola · 2023
- Remote sensing and machine learning techniques for high throughput phenotyping of late blight-resistant tomato plants in open field trials
International Journal of Remote Sensing · 2023
- Advancing molecular breeding from marker-assisted selection to genomic prediction in tomato
2023
- Multi-trait selection of tomato introgression lines under drought-induced conditions at germination and seedling stages
Acta Scientiarum Agronomy · 2022
- Combining quantitative and qualitative descriptors to predict genetic diversity in Capsicum
Australian Journal of Crop Science · 2022
- Multi-trait selection of tomato introgression lines under drought-induced conditions at germination and seedling stages
Figshare · 2022
- Research Society and Development×3
- Figshare×3
- Scientia Horticulturae×2
- Scientific Reports×2
- Acta Scientiarum Agronomy×2
- Mitch Tuinstra
Agricultural and Biological Sciences · Purdue University West Lafayette
- Richard Minyo
Agricultural and Biological Sciences · The Ohio State University
- Mohsen Shahrokhi
Agricultural and Biological Sciences · The Ohio State University
- P. Karthikeyan
Agricultural and Biological Sciences · The Ohio State University
- Peter J. Bradbury
Biochemistry, Genetics and Molecular Biology · 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 19, 2026.
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