Results 201 to 210 of about 17,694,616 (233)

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

Chemical Control of Garlic Leaf Blight Through Unmanned Aerial Vehicle Based Application. [PDF]

Plant Pathol J
Park SW, An W, Choi S, Park S, Choi H, Choi JH, Liu H, Jang HR, Lee SY, Park J, Hong SW, Sang H.   +11 more
europepmc   +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

Joint UAV Placement and Active IRS Gain Optimization for Covert Communications. [PDF]

Sensors (Basel)
Qu G, Shen M, Liu K, Xu B, Qian Y.
europepmc   +1 more source

AGIcam: An open‐source Internet of Things–based camera system for automated in‐field phenotyping and yield prediction

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Continuous, high‐frequency monitoring is essential to capture rapid phenological transitions and dynamic crop responses to the environment. However, most phenotyping platforms lack the temporal resolution and automation required for consistent, season‐long trait assessment.
Worasit Sangjan, Nisit Pukrongta, Trevor Buchanan, Arron H. Carter, Michael O. Pumphrey, Sindhuja Sankaran   +5 more
wiley   +1 more source

Using unmanned aerial vehicles (drones) to improve access to blood in low- and middle-income countries: Current challenges and opportunities. [PDF]

Vox Sang
Datta SS, Mondal R, Deb S, Tortora G, Pirri A.   +4 more
europepmc   +1 more source

Automatic measurement of rice tiller angle from unmanned aerial vehicle images

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Rice (Oryza sativa L.) tiller angle is an important trait that influences plant architecture, canopy light interception, and yield potential. In this study, we proposed a deep learning‐based pipeline for automated measurement of rice tiller angle and plant base width using unmanned aerial vehicle (UAV) imagery.
Tan‐Hanh Pham, Yubin Yang, Jing Zhang, Sanai Li, Stanley Omar P. B. Samonte, Fugen Dou, Darlene Sanchez, Lloyd T. Wilson, Tanumoy Bera, Jing Wang, Kim‐Doang Nguyen   +10 more
wiley   +1 more source

UAV-Based Coverage Path Planning for Unmanned Agricultural Vehicles. [PDF]

Sensors (Basel)
Xue G, Zhang E, An G, Du J, Yin X, Zhou P, Zhang X.   +6 more
europepmc   +1 more source

Fault-tolerant control of quadrotor unmanned aerial vehicle by using adaptive fuzzy T-S and linear matrix inversion approach. [PDF]

Sci Rep
Taimoor M, Wang H, Bibi S, Sheng C, Shah UH, Lu X, Zhang Z, Hussain I.   +7 more
europepmc   +1 more source

UAV-applied fluopyram enables rapid translocation and long-lasting efficacy for control of pine wilt disease. [PDF]

Pest Manag Sci
Zhou X, Liang Z, Zhang S, He H, He X, Gu T, Bai J, Zhang QH, Wickham JD, Zhang L.   +9 more
europepmc   +1 more source