Results 221 to 230 of about 59,716 (313)

Drone‐based phenotyping of maize for multiple disease resistance and yield in breeding field trials

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Improving selection for multiple disease resistance (MDR) and yield in maize (Zea mays L.) requires high‐throughput, objective phenotyping tools, particularly under field conditions where several foliar diseases co‐occur. We evaluated drone‐based multispectral vegetation indices (VIs) for predicting resistance to northern leaf blight (NLB ...
Danilo E. Moreta, Nina Blahut, Nicholas Kaczmar, Judith M. Kolkman, Gary Bergstrom, Margaret Smith, Michael A. Gore, Rebecca Nelson   +7 more
wiley   +1 more source

Exploring pathways between residential greenness and antepartum stillbirth: A mediation analysis. [PDF]

Environ Epidemiol
Elias DE, de Almeida MF, Francisco RPV, Novaes HMD, Marques LJP, Schultz R, Hoshida MS, Pereira da Silva Z, Alves Dos Santos O, Figueiredo GM, Buralli RJ, Ferreira Demarque G, Machado CM, Meireles LR, Zerbinati RM, Jimenez Galisteo Junior A, Cunha Rodrigues L, Gouveia N, Pereira Alencar G.   +18 more
europepmc   +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

The mortality impacts of implementing the 3-30-300 greenness rule and the WHO air quality guidelines in Bari, Southern Italy. [PDF]

Sci Rep
Giannico OV, Nannavecchia AM, Stafoggia M, Bisceglia L.   +3 more
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

Quantifying responses of climatic and anthropogenic factors on vegetation normalized difference vegetation index variabilities over Yellow River Basin, China. [PDF]

Front Plant Sci
Yu Z, Wang L, Yan J, Yuan Z, Zhang X.
europepmc   +1 more source

Pathways to Mental Health: Exploring the Relationships Among Neighborhood Hostility, Crime, Built Environment, and Perceived Safety

Journal of Community Psychology, Volume 54, Issue 5, July 2026.
ABSTRACT Neighborhood crime‐related stressors and the built environment are important determinants of mental health, yet research on the pathways through which they affect individuals remains limited. This study draws on structural equation modeling and high‐quality measures to test the pathways linking a novel measure of neighborhood‐level hostility ...
Paul Rodrigues, Carolyn Côté‐Lussier
wiley   +1 more source

Do Forms of Silicon Other than Orthosilicic Acid, Application Date and Dose Have a Beneficial Effect on Sugar Beet Yield? [PDF]

Plants (Basel)
Artyszak A, Gozdowski D, Litwińczuk-Bis M.   +2 more
europepmc   +1 more source

Density‐dependent habitat selection in plains bison

The Journal of Wildlife Management, Volume 90, Issue 5, July 2026.
Using GPS collar data, we tested whether habitat selection of plains bison in Grasslands National Park, Canada, was density dependent. Bison selected for areas of high vegetation productivity far from human activity when population density was low and increased use of lower productivity habitat closer to disturbance as density increased.
Michelle L. Sawatzky, Branden T. Neufeld, Stefano Liccioli, Philip D. McLoughlin   +3 more
wiley   +1 more source

Deep learning-based phenology extraction and crop classification in arid oasis using Sentinel-2 time series. [PDF]

J Zhejiang Univ Sci B
Wang C, Chi J, Zhang X, Zhang N.
europepmc   +1 more source