Results 141 to 150 of about 12,614,384 (261)

UAV‐based RGB and multispectral vegetation indices as alternatives to light box‐derived dark green color index for turfgrass color assessment

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Traditionally, turfgrass color has been assessed through visual ratings or light box‐based digital image analysis, methods that are either subjective or labor‐intensive. In this study, we evaluated the potential of unmanned aerial vehicle (UAV)‐based multispectral and red‐green‐blue (RGB) imagery as a high‐throughput alternative for capturing ...
Ved Parkash, Phillip L. Vines, Sameer Khanal, Jing Zhang, Joann Conner, Susana R. Milla‐Lewis, Nino Brown, David Jespersen, Jodi Johnson‐Maynard, Brian M. Schwartz   +9 more
wiley   +1 more source

Unmanned aerial vehicle–based spatiotemporal phenotyping and growth modeling for forecasting potato yield

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Monitoring spatial variations in plant growth and forecasting yield before harvest provides valuable insights for optimizing agronomic decision‐making in potato (Solanum tuberosum L.) cultivation. Although unmanned aerial vehicle (UAV)‐based remote sensing has recently enabled the development of tuber fresh weight (TW) estimation models, their
Yuto Imachi, Kunihiro Tanaka, Minato Miyauchi, Kyosuke Miyamoto, Masahiro Okada, Pieter M. Blok, Wei Guo, Hiroyoshi Iwata   +7 more
wiley   +1 more source

Phenotype imputation using high‐throughput phenotyping produces a new secondary trait for further selection modeling

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Data from high‐throughput phenotyping (HTP) could be used for phenotype imputation to enhance genomic selection (GS) or gene discovery, but this has not been explored in crop species. Three machine learning models: multiple linear regression (MLR), missForest, and k‐nearest neighbors, were evaluated for grain yield (GY) phenotype imputation in
Raysa Gevartosky, Lucas Berger Munaro, Jessica E. Rutkoski   +2 more
wiley   +1 more source

UAV‐based deep transfer learning to improve grain yield prediction in winter wheat across temporal and spatial variability

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Accurate prediction of grain yield (GY) remains a major challenge in plant breeding due to complex interactions between genotype, environment, and management (G × E × M) factors. Remote sensing data from unmanned aerial vehicles (UAVs) equipped with multispectral sensors have emerged as a pivotal resource for high‐throughput phenotyping.
Swas Kaushal, Mohammad Maruf Billah, Mandeep Singh, Dante Koupal, Pradeep Raj Sitaula, Jyotirmoy Halder, Jagdeep Sidhu, Maitiniyazi Maimaitijiang, Sunish K. Sehgal   +8 more
wiley   +1 more source

High‐throughput assessment of plant stand establishment, seedling vigor, and light interception in peanut using UAV‐based RGB and multispectral imagery

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract In peanut (Arachis hypogaea L.), plant stand establishment, seedling vigor, and canopy growth are key determinants of crop performance; yet traditional ground‐based assessment methods can be destructive, labor‐intensive, and limited in throughput.
Ved Parkash, Jessie H. Adams, Javier Rodriguez‐Sanchez, John L. Snider, Phillip L. Vines, Brian M. Schwartz, Nino Brown   +6 more
wiley   +1 more source

Proceedings New Technology for Ground Control in Retreat Mining [PDF]

"The proceedings of a series of technology transfer seminars entitled New Technology for Ground Control in Retreat Mining sponsored by NIOSH were presented.

core  

Evaluation of uncrewed aerial system‐derived vegetation indices for forage trait phenomic prediction in oat–pea intercrop breeding trials

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Accelerating genetic gain in intercrop forage breeding requires scalable phenotyping approaches that can capture both yield and quality variation across complex genotype combinations. This study evaluated the use of uncrewed aerial system (UAS)‐derived multispectral vegetation indices (VIs) for predicting forage yield and nutritive quality in ...
Milcah Kigoni, Raysa Gevartosky, Lucas B. Munaro, Tim Mies, Luis Gehrke, Jessica Rutkoski, Juan David Arbelaez   +6 more
wiley   +1 more source

GCP Placement Methods for Improving the Accuracy of Shoreline Extraction in Coastal Video Monitoring

한국해양공학회지
In coastal video monitoring, the direct linear transform (DLT) method with ground control points (GCPs) is commonly used for geo-rectification. However, current practices often overlook the impact of GCP quantity, arrangement, and the geographical ...
Changyul Lee, Kideok Do, Inho Kim, Sungyeol Chang   +3 more
doaj   +1 more source

Phenomic prediction I: Plot‐level prediction of lodging severity in sorghum breeding trials using UAV‐based photogrammetric height data

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Lodging in sorghum (Sorghum bicolor (L.) Moench) presents a significant challenge for plant breeders due to the trade‐off between lodging resistance and grain yield. Manually measuring lodging across thousands of plots is time‐consuming, expensive, and error‐prone, making selection for lodging resistance challenging in breeding programs ...
Srinivasa Reddy Mothukuri, Sean Reynolds Massey‐Reed, Andries Potgieter, Kenneth Laws, Colleen Hunt, Esinam Nancy Amuzu‐Aweh, Mark Cooper, Emma Mace, David Jordan   +8 more
wiley   +1 more source

Extracting photogrammetric ground control from lidar DEMs for change detection

Research has shown the importance of measuring topography for surface change detection and that the use of remote sensing methods is ideal for this application.
Murray T, Barrand NE, Barr SL, James TD
core   +4 more sources