Results 1 to 10 of about 2,273 (218)

Improving genomic prediction for plant disease using environmental covariates

Plant Methods
Background Fusarium Head Blight (FHB) is a destructive fungal disease affecting wheat and barley, leading to significant yield losses and reduced grain quality.
Charlotte Brault, Emily J. Conley, Andrew C. Read, Andrew J. Green, Karl D. Glover, Jason P. Cook, Harsimardeep S. Gill, Jason D. Fiedler, James A. Anderson   +8 more
doaj   +3 more sources

Global Soil Salinity Prediction by Open Soil Vis-NIR Spectral Library

Remote Sensing, 2022
Soil salinization is one of the major degradation processes threatening food security and sustainable development. Detailed soil salinity information is increasingly needed to tackle this global challenge for improving soil management.
Yin Zhou, Songchao Chen, Bifeng Hu, Wenjun Ji, Shuo Li, Yongsheng Hong, Hanyi Xu, Nan Wang, Jie Xue, Xianglin Zhang, Yi Xiao, Zhou Shi   +11 more
doaj   +1 more source

Recalcitrant C Source Mapping Utilizing Solely Terrain-Related Attributes and Data Mining Techniques

Agronomy, 2022
Agricultural practices affect arbuscular mycorrhizal fungal (AMF) hyphae growth and glomalin production, which is a recalcitrant carbon (C) source in soil.
Arezou Siami, Nasser Aliasgharzad, Leili Aghebati Maleki, Nosratollah Najafi, Farzin Shahbazi, Asim Biswas   +5 more
doaj   +1 more source

Digital mapping of soil organic carbon stocks in the forest lands of Dominican Republic

European Journal of Remote Sensing, 2022
Mapping the spatial distribution of soil organic carbon (SOC) in lands covered by tropical forests is important to understand the relationship and dynamics of SOC in this type of ecosystem.
Efraín Duarte, Erick Zagal, Juan A. Barrera, Francis Dube, Fabio Casco, Alexander J. Hernández   +5 more
doaj   +1 more source

Identifying multispecies synchrony in response to environmental covariates [PDF]

Ecology and Evolution, 2016
AbstractThe importance of multispecies models for understanding complex ecological processes and interactions is beginning to be realized. Recent developments, such as those by Lahoz‐Monfort et al. (2011), have enabled synchrony in demographic parameters across multiple species to be explored.
Swallow, Ben, King, Ruth, Buckland, Stephen T., Toms, Mike P.   +3 more
openaire   +6 more sources

Geospatial Modelling for Delineation of Crop Management Zones Using Local Terrain Attributes and Soil Properties

Remote Sensing, 2022
Defining nutrient management zones (MZs) is crucial for the implementation of site-specific management. The determination of MZs is based on several factors, including crop, soil, climate, and terrain characteristics.
Roomesh Kumar Jena, Siladitya Bandyopadhyay, Upendra Kumar Pradhan, Pravash Chandra Moharana, Nirmal Kumar, Gulshan Kumar Sharma, Partha Deb Roy, Dibakar Ghosh, Prasenjit Ray, Shelton Padua, Sundaram Ramachandran, Bachaspati Das, Surendra Kumar Singh, Sanjay Kumar Ray, Amnah Mohammed Alsuhaibani, Ahmed Gaber, Akbar Hossain   +16 more
doaj   +1 more source

Associations between environmental covariates and temporal changes in malaria incidence in high transmission settings of Uganda: a distributed lag nonlinear analysis

BMC Public Health, 2021
Background Environmental factors such as temperature, rainfall, and vegetation cover play a critical role in malaria transmission. However, quantifying the relationships between environmental factors and measures of disease burden relevant for public ...
Jaffer Okiring, Isobel Routledge, Adrienne Epstein, Jane F. Namuganga, Emmanuel V. Kamya, Gloria Odei Obeng-Amoako, Catherine Maiteki Sebuguzi, Damian Rutazaana, Joan N. Kalyango, Moses R. Kamya, Grant Dorsey, Ronald Wesonga, Steven M. Kiwuwa, Joaniter I. Nankabirwa   +13 more
doaj   +1 more source

Using Udometric Network Data to Estimate an Environmental Covariate [PDF]

AIP Conference Proceedings, 2011
Many hydrological and ecological studies recognize the importance of characterizing the temporal and spatial variability of precipitation. In this study, geostatistical methodologies were developed in order to estimate a hydro‐meteorological factor by (re)building the space‐time distribution of the precipitation associated to monthly averages in a ...
A. Manuela Gonçalves, Marco Costa, Theodore E. Simos, George Psihoyios, Ch. Tsitouras, Zacharias Anastassi   +5 more
openaire   +3 more sources

Improving the spatial prediction of soil organic carbon using environmental covariates selection: A comparison of a group of environmental covariates

CATENA, 2022
Abstract In the digital soil mapping (DSM) framework, machine learning models quantify the relationship between soil observations and environmental covariates. Generally, the most commonly used covariates (MCC; e.g., topographic attributes and single-time remote sensing data, and legacy maps) were employed in DSM studies. Additionally, remote sensing
Mojtaba Zeraatpisheh, Younes Garosi, Hamid Reza Owliaie, Shamsollah Ayoubi, Ruhollah Taghizadeh-Mehrjardi, Thomas Scholten, Ming Xu   +6 more
openaire   +1 more source

Genetic and environmental influences on rumination and its covariation with depression [PDF]

Cognition and Emotion, 2014
This study examined the extent to which rumination and depression share genetic and environmental influences in a community sample of adult twins (N=663). Twins completed multiple rumination questionnaires, a depressive symptoms questionnaire and a diagnostic interview.
Daniel P, Johnson, Mark A, Whisman, Robin P, Corley, John K, Hewitt, Naomi P, Friedman   +4 more
openaire   +2 more sources