Results 151 to 160 of about 62,073 (218)

Assessing functional diversity and composition using multispectral images in Atlantic Forest restoration sites

Restoration Ecology, EarlyView.
Abstract Introduction By focusing on the specific functional traits of species, we can better understand how ecosystems function and respond to environmental change. However, field measurements of functional traits can be time‐consuming and costly, whereas remote sensing data can serve as viable alternatives for studying biodiversity at larger scales ...
Júlia Ayres de Oliveira, Ângelo Mantovani Amorim de Freitas Oliveira, André Quintão de Almeida, Catherine Torres de Almeida, Eric Bastos Gorgens, Vinicius Nunes Henrique Silva, Luiz Fernando Duarte de Moraes, Gustavo Bastos Lyra, Jerônimo Boelsums Barreto Sansevero   +8 more
wiley   +1 more source

Microbial mats and thalassinid shrimp: Spatial and geochemical interactions in a modern intertidal environment

Sedimentology, EarlyView.
ABSTRACT This research examines the spatial and geochemical interactions between mat‐forming microorganisms and thalassinid shrimp in an intertidal flat situated on the shores of Willapa Bay, Washington, USA. The study serves as a contemporary analog for the relationships between mats and burrowing organisms in deep time.
Brette S. Harris, Sara K. Biddle, Maya T. LaGrange, Scott Melnyk, Cody N. Lazowski, Jenifer S. Spence, Daniel Alessi, Jeffrey Kavanaugh, Kurt O. Konhauser, Murray K. Gingras   +9 more
wiley   +1 more source

A highly accurate, low‐cost method for detecting and quantifying soybean leaf flipping phenotype during drought stress

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract A genome‐wide association study (GWAS) using digital images was conducted to delineate regions of the genome that govern the leaf flipping quantitative trait in soybean (Glycine max (L.) Merr). However, converting the digital data to numerical scores for downstream analyses was challenging.
Mohammad Anisur Rahaman, Atit Parajuli, Adnan Hossain Khan, Liang Dong, Madan K Bhattacharyya   +4 more
wiley   +1 more source

High‐throughput phenotyping for the prediction and quantification of flower‐related traits in sugarcane

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Sugarcane (Saccharum spp.), a C4 plant, is a vital renewable biofuel and sugar source for industries worldwide. However, synchronizing flowering between parental lines often poses challenges for breeders, hindering effective crossbreeding efforts.
Paulo H. da Silva Santos, João R. Vieira Manechini, Carlos Augusto Dias Kanthack Jr., Mauro Alexandre Xavier, Samira Domingues Carlin, Dilermando Perecin, Thiago G. Marconi, Leandro G. Marconi, Elisson Antonio da Costa Romanel, Stephen Derek Jackson, Marcos. G. A. Landell, Luciana R. Pinto   +11 more
wiley   +1 more source

Spatial and temporal scales in plant phenotyping for crop water stress assessment: A review

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Water stress is a major limiting factor for crop productivity worldwide, and its impacts are intensifying due to climate variability and increasing water scarcity. This review focuses on the spatial and temporal scales in plant phenotyping as a critical approach to improving crop water‐stress assessment and supporting precision water ...
Daniel Kingsley Cudjoe, Yazhou Sun, Sanai Li, Wenxuan Guo   +3 more
wiley   +1 more source

Insights into biomass accumulation and challenges in grain yield prediction of elite breeding materials using UAV‐based vegetation indices in soft red winter wheat

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract High‐throughput phenotyping (HTP) techniques have brought new opportunities to understand and evaluate key traits in plant breeding programs. Combining multiple measures through time and random regression models permits a more comprehensive understanding of the genetic and environmental effects on trait expression over time. This study aims to
Felipe Sabadin, Amelia Loeb, Francis Reith, Alexis Perry, Sunilda Frias, Demetrius Ragland, Limei Liu, Wynse Brooks, Ranjita Thapa, Julie Hansen, Christopher Pierce, Virginia M. Moore, Gina Brown‐Guedira, Ian Ray, Michael A. Gore, Kelly Robbins, Nicholas Santantonio   +16 more
wiley   +1 more source

Predicting soybean aboveground biomass in the short‐season region of Canada: Integrating vegetative cover and canopy height

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Aboveground biomass (ABM) is a key determinant of soybean (Glycine max [L.] Merr.) yield and can be used to select for stress‐resilient cultivars. The objective of our study was to develop a predictive model describing ABM in short‐season soybean from vegetative cover (VC) and canopy height (CH).
Malcolm J. Morrison, Thomas L. Hotte, A. Claire Gahagan, Nathaniel W. W. Ort, Elroy R. Cobber   +4 more
wiley   +1 more source

Developing a simple soil erosion model including spatial variability in headwater catchments

Agrosystems, Geosciences &Environment, Volume 9, Issue 2, June 2026.
Abstract Hillslopes and stream channels are tightly linked in headwater catchments, where soil erosion on slopes is transported to channels depending on topography, soil properties, and ground cover conditions. Because these environments are highly spatially variable, geographic information system (GIS)‐based modeling approaches are effective for ...
Binyam Alemu Yosef, Takashi Gomi, Mitsuru Ohira, Yoshimi Uchiyama, Katsushige Shiraki   +4 more
wiley   +1 more source

An Improved ELOS Guidance Law for Path Following of Underactuated Unmanned Surface Vehicles. [PDF]

Sensors (Basel)
Wu S, Ye H, Liu W, Yang X, Liu Z, Zhang H.   +5 more
europepmc   +1 more source

Context‐aware UAV LiDAR reveals forest structure and improves tree diameter estimates in subalpine forest

Ecological Solutions and Evidence, Volume 7, Issue 2, April–June 2026.
In this study we show how, in natural forests, tree heights adapt across environmental gradients as a response to environmental and biotic factors. Awareness of such local adaptations can be encoded into predictive features and leveraged by shallow learning methods to enhance predictions of tree diameter and tree‐level aboveground biomass.
Jaime C. Revenga, Stefan Oehmcke, Mana Gharun, Flurin Sutter, Fabian Gieseke, Katerina Trepekli, Nina Buchmann, Alexander Damm   +7 more
wiley   +1 more source