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Piyush Pandey
Piyush Pandey
ORISE postdoctoral fellow at USDA-ARS
Verified email at usda.gov - Homepage
Title
Cited by
Cited by
Year
High throughput in vivo analysis of plant leaf chemical properties using hyperspectral imaging
P Pandey, Y Ge, V Stoerger, JC Schnable
Frontiers in plant science 8, 1348, 2017
2452017
Conventional and hyperspectral time-series imaging of maize lines widely used in field trials
Z Liang, P Pandey, V Stoerger, Y Xu, Y Qiu, Y Ge, JC Schnable
Gigascience 7 (2), gix117, 2018
562018
Hyperspectral Imaging Combined with Machine Learning for the Detection of Fusiform Rust Disease Incidence in Loblolly Pine Seedlings
P Pandey, KG Payn, Y Lu, AJ Heine, TD Walker, JJ Acosta, S Young
Remote Sensing 13 (18), 3595, 2021
152021
Frontier: Autonomy in Detection, Actuation, and Planning for Robotic Weeding Systems
P Pandey, HN Dakshinamurthy, SN Young
Transactions of the ASABE 64 (2), 557-563, 2021
152021
Prediction of Freeze Damage and Minimum Winter Temperature of the Seed Source of Loblolly Pine Seedlings Using Hyperspectral Imaging
Y Lu, TD Walker, JJ Acosta, S Young, P Pandey, AJ Heine, KG Payn
Forest Science 67 (3), 321-334, 2021
92021
Hyperspectral Imaging with Cost-Sensitive Learning for High-Throughput Screening of Loblolly Pine (Pinus taeda L.) Seedling for Freeze Tolerance
Y Lu, KG Payn, P Pandey, JJ Acosta, AJ Heine, TD Walker, S Young
Transactions of the ASABE, 0, 2021
62021
High Throughput Phenotyping for Fusiform Rust Disease Resistance in Loblolly Pine Using Hyperspectral Imaging
P Pandey, KG Payn, Y Lu, AJ Heine, TD Walker, S Young
2020 ASABE Annual International Virtual Meeting, 1, 2020
62020
Hyperspectral Imaging-Enabled High-Throughput Screening of Loblolly Pine (Pinus taeda) Seedlings for Freeze Tolerance
Y Lu, KG Payn, P Pandey, JJ Acosta, AJ Heine, TD Walker, S Young
2020 ASABE Annual International Virtual Meeting, 1, 2020
32020
Estimating fresh biomass of maize plants from their RGB images in greenhouse phenotyping
Y Ge, P Pandey, G Bai
Autonomous Air and Ground Sensing Systems for Agricultural Optimization and …, 2016
32016
Predicting foliar nutrient concentrations and nutrient deficiencies of hydroponic lettuce using hyperspectral imaging
P Pandey, P Veazie, B Whipker, S Young
Biosystems Engineering 230, 458-469, 2023
22023
Impact of Macronutrient Fertility on Mineral Uptake and Growth of Lactuca sativa ‘Salanova Green’ in a Hydroponic System
P Veazie, P Pandey, S Young, MS Ballance, K Hicks, B Whipker
Horticulturae 8 (11), 1075, 2022
22022
A Literature Review of Non-herbicide, Robotic Weeding: A Decade of Progress
P Pandey, HN Dakshinamurthy, S Young
22020
Towards aerial robotic pollination for controlled crosses in Pinus taeda
P Pandey, JJ Acosta, KG Payn, SN Young
2022 ASABE Annual International Meeting, 1, 2022
12022
High Throughput Phenotyping of Sorghum for the Study of Growth Rate, Water Use Efficiency, and Chemical Composition
P Pandey
12017
Synthetically Labeled Images for Maize Plant Detection in UAS Images
P Pandey, NB Best, JD Washburn
International Symposium on Visual Computing, 543-556, 2023
2023
Deep learning for maize mutants: Phenotyping individual plants using UAS images
P Pandey, NB Best, JD Washburn
Authorea Preprints, 2023
2023
Design Considerations for In-Field Measurement of Plant Architecture Traits Using Ground-Based Platforms
P Pandey, S Young
High-Throughput Plant Phenotyping, 171-190, 2022
2022
The Impacts of Macronutrient Fertility Concentrations on Mineral Uptake and Growth of Latuca sativa ‘Salanova Green’
P Veazie, B Whipker, S Young, P Pandey
2021 ASHS Annual Conference, 2021
2021
Lessons From Paired Data From exPVP Maize Lines in Agronomic Field Trials and RGB And Hyperspectral Time-Series Imaging In Controlled Environments
JC Schnable, P Pandey, Y Ge, Y Xu, Y Qiu, Z Liang
AGU Fall Meeting Abstracts 2017, B41J-04, 2017
2017
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Articles 1–19