Buchumschlag

Drone‐based polarization imaging system for leaf spot severity determination in peanut plants

Fuente: Wiley Open Access

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Joshua Larsen, Jeffrey. Dunne, Robert Austin, Cassondra Newman, Michael Kudenov
Format:	Artículo Open Access
Veröffentlicht:	Wiley 2025
Schlagworte:	The Plant Phenome Journal
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Enhancing peanut pre‐sizing with PodTracker: A multiple pod tracking algorithm
von: Enrique E. Pena Martinez, et al.
Veröffentlicht: (2025)

High‐throughput classification and quantification of skinning phenotype in sweet potatoes
von: Zachary A. Bloom, et al.
Veröffentlicht: (2025)

Drone‐based imaging sensors, techniques, and applications in plant phenotyping for crop breeding: A comprehensive review
von: Boubacar Gano, et al.
Veröffentlicht: (2024)

Drone‐based phenotyping of maize for multiple disease resistance and yield in breeding field trials
von: Danilo E. Moreta, et al.
Veröffentlicht: (2026)

Deployment and analysis of instance segmentation algorithm for in‐field yield estimation of sweet potatoes
von: Hoang M. Nguyen, et al.
Veröffentlicht: (2025)

Use of arduino‐based potentiometric sensors to measure changes in leaf apoplastic pH in common bean ( Phaseolus vulgaris L.)
von: Robert McGee, et al.
Veröffentlicht: (2025)

Phenotypic scoring of canola blackleg severity using machine learning image analysis
von: Qiao Hu, et al.
Veröffentlicht: (2026)

Hyperspectral reflectance‐based partial least squares regression models for predicting cotton leaf physiological traits
von: Ved Parkash, et al.
Veröffentlicht: (2025)

Sorghum segmentation and leaf counting using in silico trained deep neural model
von: Ian Ostermann, et al.
Veröffentlicht: (2024)

Robustness of high‐throughput prediction of leaf ecophysiological traits using near infrared spectroscopy and poro‐fluorometry
von: Eva Coindre, et al.
Veröffentlicht: (2026)

A highly accurate, low‐cost method for detecting and quantifying soybean leaf flipping phenotype during drought stress
von: Mohammad Anisur Rahaman, et al.
Veröffentlicht: (2026)

UAV image acquisition and processing for high‐throughput phenotyping in agricultural research and breeding programs
von: Ocident Bongomin, et al.
Veröffentlicht: (2024)

Assessing robustness and transferability of image‐based semantic segmentation models for major field crops
von: Gustavo N. Santiago, et al.
Veröffentlicht: (2026)

Class‐specific data augmentation for plant stress classification
von: Nasla Saleem, et al.
Veröffentlicht: (2024)

Estimating Fusarium head blight severity in winter wheat using deep learning and a spectral index
von: Riley McConachie, et al.
Veröffentlicht: (2024)

Radiometric calibration of UAV multispectral images under changing illumination conditions with a downwelling light sensor
von: Vaishali Swaminathan, et al.
Veröffentlicht: (2024)

Deep learning and computer vision for image‐based high‐throughput phenotyping of canning quality traits in dry beans
von: Lovepreet Singh, et al.
Veröffentlicht: (2026)

Miscanthus‐AI: Applying computational argumentation for decision support in plant breeding
von: Oliver Hardy, et al.
Veröffentlicht: (2025)

Affordable phenomics: Expanding access to enhancing genetic gain in plant breeding
von: V. Hoyos‐Villegas, et al.
Veröffentlicht: (2025)

Utilizing QGIS for open‐source UAS imagery plant classification and plot segmentation
von: Erik Z. Killian, et al.
Veröffentlicht: (2025)

Developing and deploying an unmanned aerial system–based phenotyping program for maturity to support soybean breeding
von: Nathaniel Burner, et al.
Veröffentlicht: (2026)

The future role of regional research infrastructures and networks toward the global plant phenotyping community
von: Stijn Dhondt, et al.
Veröffentlicht: (2025)

Spatial and temporal scales in plant phenotyping for crop water stress assessment: A review
von: Daniel Kingsley Cudjoe, et al.
Veröffentlicht: (2026)

GWAS analysis for plant height and stem diameter in sorghum using multiple phenotyping approaches
von: Lucas Boatwright, et al.
Veröffentlicht: (2024)

Hyperspectral imaging combined with machine learning for high‐throughput phenotyping in winter wheat
von: Sehijpreet Kaur, et al.
Veröffentlicht: (2024)

Adoption of unoccupied aerial systems in agricultural research
von: Jennifer Lachowiec, et al.
Veröffentlicht: (2024)

Rapid estimation of DON content in wheat flour using close‐range hyperspectral imaging and machine learning
von: Dinesh Kumar Saini, et al.
Veröffentlicht: (2024)

A root system architecture measurement pipeline for apple rootstocks
von: Jean Sabety, et al.
Veröffentlicht: (2024)

Spatial analysis with unoccupied aircraft systems data in wheat breeding yield trials
von: Andrew W. Herr, et al.
Veröffentlicht: (2024)

Large‐scale breeding applications of unoccupied aircraft systems enabled genomic prediction
von: Andrew W. Herr, et al.
Veröffentlicht: (2024)

High temporal resolution unoccupied aerial systems phenotyping provides unique information between flight dates
von: Jacob D. Washburn, et al.
Veröffentlicht: (2024)

Prediction of symbiotic nitrogen fixation in common bean ( Phaseolus vulgaris L.) using unmanned aerial system remote sensing
von: Madison Whyte, et al.
Veröffentlicht: (2025)

Unmanned aerial vehicle–based spatiotemporal phenotyping and growth modeling for forecasting potato yield
von: Yuto Imachi, et al.
Veröffentlicht: (2026)

Computer vision‐based recognition and distinction of Arabidopsis thaliana ecotypes using supervised deep learning models
von: Rijad Sarić, et al.
Veröffentlicht: (2025)

Selection of appropriate multispectral camera exposure settings and radiometric calibration methods for applications in phenotyping and precision agriculture
von: Vaishali Swaminathan, et al.
Veröffentlicht: (2024)

Soybean maturity prediction using two‐dimensional contour plots from drone‐based time series imagery
von: Bitgoeul Kim, et al.
Veröffentlicht: (2025)

Pixel‐level supervision resolves overlap: Benchmarking YOLOv12 segmentation for accurate multi‐cluster dry bean stand counting from time series unoccupied aerial systems imagery
von: Aliasghar Bazrafkan, et al.
Veröffentlicht: (2026)

UAV‐based deep transfer learning to improve grain yield prediction in winter wheat across temporal and spatial variability
von: Swas Kaushal, et al.
Veröffentlicht: (2026)

UAV‐based high‐throughput phenotyping for crop growth analysis and seed yield prediction in a nested association mapping population of lentils
von: Sandesh Neupane, et al.
Veröffentlicht: (2025)

Deep learning‐based high‐throughput detection of flowered maize ( Zea mays L.) plots from UAS imagery across environments
von: Nicholas R. Shepard, et al.
Veröffentlicht: (2025)