Results 31 to 40 of about 5,783 (249)

Utilization of Remote Sensing Dataset and a Deep Learning Object Detection Model to Map Siam Weed Infestations

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Remote sensing data are valuable for detecting, mapping, and managing invasive weed species. This article introduces an innovative algorithm for mapping Siam weed infestations using a bounding box approach from a deep learning object detection model ...
Zulfadli Mawardi, Deepak Gautam, Timothy G. Whiteside   +2 more
doaj   +1 more source

Distribution Map and Community Characteristics of Weeds in Barley Fields of Ardabil Province [PDF]

Ikufīziyuluzhī-i Giyāhān-i Zirā̒ī, 2013
Surveying weeds of irrigated barley fields is one of the most important practices in weed management. Based on cultivated areas irrigated barley in all counties of Ardabil province during six years (2000-2005), 46 sample barley fields were selected and ...
B. Soheili, M. Minbashi, D. Hasanpanah, N. Razmi   +3 more
doaj  

Examining Deep Learning Pixel-Based Classification Algorithms for Mapping Weed Canopy Cover in Wheat Production Using Drone Data

Geomatics
Deep learning models offer valuable insights by leveraging large datasets, enabling precise and strategic decision-making essential for modern agriculture.
Judith N. Oppong, Clement E. Akumu, Samuel Dennis, Stephanie Anyanwu   +3 more
doaj   +1 more source

Distribution and Biology of the Invasive Weed Parthenium hysterophorus L. in Israel

Frontiers in Agronomy, 2021
Parthenium weed (Parthenium hysterophorus L.) (Asteraceae; Heliantheae) is an invasive allergenic species that has invaded many countries worldwide, probably through an imported pasture, grain seeds, and livestock feed.
Maor Matzrafi, Hagai Raz, Hagai Raz, Baruch Rubin, Tuvia Yaacoby, Hanan Eizenberg   +5 more
doaj   +1 more source

Mapping and monitoring of weeds using unmanned aircraft systems and remote sensing

Plant Protection Science
Effective weed management relies on frequent field monitoring, which is difficult to perform in vast areas. Integrating red-green-blue, thermal, hyperspectral, and multispectral sensors with unmanned aircraft systems and artificial intelligence ensures ...
A. Pon Arasan, S. Radhamani, S. Pazhanivelan, R. Kavitha, R. Raja, R. Kumaraperumal   +5 more
doaj   +1 more source

Weeding and disposal in Academic Labraries

Brazilian Journal of Information Science, 2013
The aim of this study is to raise and discuss the literature on weeding and disposal in academic libraries. A survey of documents in databases of national and international scientific articles that address this issue. Items recovered on disposal and weeding were filtered and separated into four categories, namely: physical space, the current collection,
Márcia Regina Silva, Cláudio Marcondes Castro Filho, Paula Oliveira Quirino   +2 more
openaire   +4 more sources

Underground Signals: The Ecological Power of Root Volatiles

Advanced Science, EarlyView.
Root volatiles mediate rhizosphere chemical communication, shaping interactions among plants, microbes, herbivores, and natural enemies. Their production, transport, and perception underpin ecological adaptation, multitrophic interactions, and plant resilience, offering opportunities for sustainable crop protection, resilient agroecosystems, and ...
Xueyao Cao, Nanli Song, François Verheggen, Meritxell Pérez‐Hedo, Andrea Clavijo McCormick, Antonino Cusumano, Arthur de Fouchier, Bing Wang, Chen‐Zhu Wang, Emmanuelle Jacquin‐Joly, Gary W. Felton, Geoff M. Gurr, Hao Guo, Jiancai Li, Jin Zhang, Li Chen, Manqun Wang, Michele Ricupero, Peng Han, Peng He, Qi Yan, Qingbo Tang, Qingsong Liu, Shiheng An, Xiangbo Kong, Xiaoling Sun, Xueming Ren, Yuanyuan Song, Yang Liu, Yanhui Guo, Yunhe Li, Xiao Sun   +31 more
wiley   +1 more source

An Autonomous Robotic System for Mapping Weeds in Fields [PDF]

IFAC Proceedings Volumes, 2013
Abstract The ASETA project develops theory and methods for robotic agricultural systems. In ASETA, unmanned aircraft and unmanned ground vehicles are used to automate the task of identifying and treating weeds in sugar beet fields. The framework for a working automatic robotic weeding system is presented along with the implemented computer vision ...
Karl D. Hansen, Francisco Garcia-Ruiz, Wajahat Kazmi, Morten Bisgaard, Anders la Cour-Harbo, Jesper Rasmussen, Hans Jørgen Andersen   +6 more
openaire   +1 more source

Distribution, Density, and Abundance of Parthenium Weed (Parthenium hysterophorus L.) at Kuala Muda, Malaysia

International Journal of Agronomy, 2018
Knowledge of distribution, density, and abundance of weed in a place is a prerequisite for its proper management. Parthenium hazard is a national agenda in Malaysia, and Kedah is the worst infested state in the country.
C. M. Maszura, S. M. R. Karim, M. Z. Norhafizah, F. Kayat, M. Arifullah   +4 more
doaj   +1 more source

The Landscape of Long Non‐Coding RNAs Provides Insights Into the Domestication and Improvement of Pear Fruit

Advanced Science, EarlyView.
This study reveals that long non‐coding RNAs represent important regulatory components underlying pear domestication and improvement. Integrative multi‐omics analyses identify selected lncRNAs associated with fruit traits, while functional validation uncovers a lignin‐related lncRNA, lncRNA‐pys, that promotes lignin accumulation.
Bobo Song, Peilin Han, Jiaming Li, Xiaolong Li, Xiang Zhang, Jing Fan, Dongliang Liu, Jianfa Cai, Lingchao Zhang, Jun Wu   +9 more
wiley   +1 more source