Drone imagery to create a common understanding of landscapes DOI
Fritz Kleinschroth, Kawawa Banda,

Henry Zimba

и другие.

Landscape and Urban Planning, Год журнала: 2022, Номер 228, С. 104571 - 104571

Опубликована: Сен. 15, 2022

Язык: Английский

Deep Neural Networks to Detect Weeds from Crops in Agricultural Environments in Real-Time: A Review DOI Creative Commons
Ildar Rakhmatulin, Andreas Kamilaris, Christian Andreasen

и другие.

Remote Sensing, Год журнала: 2021, Номер 13(21), С. 4486 - 4486

Опубликована: Ноя. 8, 2021

Automation, including machine learning technologies, are becoming increasingly crucial in agriculture to increase productivity. Machine vision is one of the most popular parts and has been widely used where advanced automation control have required. The trend shifted from classical image processing techniques modern artificial intelligence (AI) deep (DL) methods. Based on large training datasets pre-trained models, DL-based methods proven be more accurate than previous traditional techniques. wide applications agriculture, detection weeds pests crops. Variation lighting conditions, failures transfer learning, object occlusion constitute key challenges this domain. Recently, DL gained much attention due its advantages detection, classification, feature extraction. algorithms can automatically extract information amounts data model complex problems is, therefore, suitable for detecting classifying We present a systematic review AI-based systems detect weeds, emphasizing recent trends DL. Various discussed clarify their overall potential, usefulness, performance. This study indicates that several limitations obstruct widespread adoption AI/DL commercial applications. Recommendations overcoming these summarized.

Язык: Английский

Процитировано

60

A comprehensive review of electrochemical hybrid power supply systems and intelligent energy managements for unmanned aerial vehicles in public services DOI Creative Commons
Caizhi Zhang,

Yuqi Qiu,

Jiawei Chen

и другие.

Energy and AI, Год журнала: 2022, Номер 9, С. 100175 - 100175

Опубликована: Июнь 18, 2022

The electric unmanned aerial vehicles (UAVs) are rapidly growing due to their abilities perform some difficult or dangerous tasks as well many public services including real-time monitoring, wireless coverage, search and rescue, wildlife surveys, precision agriculture. However, the electrochemical power supply system of UAV is a critical issue in terms its energy/power densities lifetime for service endurance. In this paper, current systems used UAVs comprehensively reviewed analyzed on existing configurations energy management systems. It identified that single type source not enough support achieve long-haul flight; hence, hybrid architecture necessary. To make use advantages each increase endurance good performance UAVs, containing two three types sources (fuel cell, battery, solar supercapacitor,) have be developed. regard, selection an appropriate structure with optimized efficient operation UAV. found data-driven models artificial intelligence (AI) promising intelligent management. This paper can provide insights guidelines future research development into design fabrication advanced

Язык: Английский

Процитировано

50

Biodiversity indicators for result-based agri-environmental schemes – Current state and future prospects DOI Creative Commons

By Noëmi Elmiger,

Robert Finger, Jaboury Ghazoul

и другие.

Agricultural Systems, Год журнала: 2022, Номер 204, С. 103538 - 103538

Опубликована: Окт. 29, 2022

We systematically review proposed biodiversity indicators for result-based agri-environmental schemes.• Additionally, we synthesize currently used in Most studies and schemes focus on grasslands plant species diversity using vascular plants as indicators.• Policymakers can draw upon various options to design their Technological advances could improve the monitoring of indicators.

Язык: Английский

Процитировано

47

Cyber-agricultural systems for crop breeding and sustainable production DOI Creative Commons
Soumik Sarkar, Baskar Ganapathysubramanian, Arti Singh

и другие.

Trends in Plant Science, Год журнала: 2023, Номер 29(2), С. 130 - 149

Опубликована: Авг. 28, 2023

The cyber-agricultural system (CAS) represents an overarching framework of agriculture that leverages recent advances in ubiquitous sensing, artificial intelligence, smart actuators, and scalable cyberinfrastructure (CI) both breeding production agriculture. We discuss the progress perspective three fundamental components CAS - modeling, actuation emerging concept agricultural digital twins (DTs). also how CI is becoming a key enabler In this review we shed light on significance revolutionizing crop by enhancing efficiency, productivity, sustainability, resilience to changing climate. Finally, identify underexplored promising future directions for research development.

Язык: Английский

Процитировано

29

Mapping soil available copper content in the mine tailings pond with combined simulated annealing deep neural network and UAV hyperspectral images DOI
Yangxi Zhang, Lifei Wei, Qikai Lu

и другие.

Environmental Pollution, Год журнала: 2023, Номер 320, С. 120962 - 120962

Опубликована: Янв. 5, 2023

Язык: Английский

Процитировано

28

Dos and Don'ts of using drone technology in the crop fields DOI
Jamileh Aliloo, Enayat Abbasi, Esmail Karamidehkordi

и другие.

Technology in Society, Год журнала: 2024, Номер 76, С. 102456 - 102456

Опубликована: Янв. 2, 2024

Язык: Английский

Процитировано

14

Review on the contribution of farming practices and technologies towards climate-smart agricultural outcomes in a European context DOI Creative Commons
Kassa Tarekegn, Søren Marcus Pedersen, Tove Christensen

и другие.

Smart Agricultural Technology, Год журнала: 2024, Номер 7, С. 100413 - 100413

Опубликована: Фев. 15, 2024

The aim of this review was to provide an overview existing farming practices and technologies in Europe by assessing their contribution climate-smart agricultural (CSA) outcomes. Following the PRISMA protocol, 110 final selected studies were scrutinized. Altogether 74 different identified. Using inductive approach, identified categorized, potential towards contextualized CSA outcomes—productivity, resilience, GHG mitigation, biodiversity improvement, animal welfare support, water energy use efficiency—was assessed. Among practices, highlighted legume-based cover crops, crop rotation, intercropping, diversification as having promising achieve technologies, precision fertilization, protection, irrigation showed potential. Moreover, pasture grazing, feed additives, improved forage production holistic husbandry management with contributors emphasizes that utilization smart livestock systems could positively contribute achieving one or more Overall, mitigation farm productivity improvement outcomes relatively well covered reviewed literature. Improvements biodiversity, efficiency, are not demonstrated within studies.

Язык: Английский

Процитировано

14

UAV image acquisition and processing for high‐throughput phenotyping in agricultural research and breeding programs DOI Creative Commons
Ocident Bongomin, Jimmy Lamo,

Joshua Mugeziaubwa Guina

и другие.

The Plant Phenome Journal, Год журнала: 2024, Номер 7(1)

Опубликована: Фев. 19, 2024

Abstract We are in a race against time to combat climate change and increase food production by 70% feed the ever‐growing world population, which is expected double 2050. Agricultural research plays vital role improving crops livestock through breeding programs good agricultural practices, enabling sustainable agriculture systems. While advanced molecular technologies have been widely adopted, phenotyping as an essential aspect of has seen little development most African institutions remains traditional method. However, concept high‐throughput (HTP) gaining momentum, particularly context unmanned aerial vehicle (UAV)‐based phenotyping. Although into UAV‐based still limited, this paper aimed provide comprehensive overview understanding use UAV platforms image analytics for HTP identify key challenges opportunities area. The discusses field concepts, classification specifications, cases phenotyping, imaging systems processing methods. more required optimize UAVs’ performance data acquisition, limited studies focused on effect operational parameters acquisition.

Язык: Английский

Процитировано

12

Applications of unoccupied aerial systems (UAS) in landscape ecology: a review of recent research, challenges and emerging opportunities DOI Creative Commons
Miguel L. Villarreal, Tara B. B. Bishop, Temuulen Tsagaan Sankey

и другие.

Landscape Ecology, Год журнала: 2025, Номер 40(2)

Опубликована: Фев. 8, 2025

Язык: Английский

Процитировано

2

A Bibliometric Network Analysis of Recent Publications on Digital Agriculture to Depict Strategic Themes and Evolution Structure DOI Creative Commons
Michele Kremer Sott, Leandro da Silva Nascimento, Cristian Rogério Foguesatto

и другие.

Sensors, Год журнала: 2021, Номер 21(23), С. 7889 - 7889

Опубликована: Ноя. 26, 2021

The agriculture sector is one of the backbones many countries' economies. Its processes have been changing to enable technology adoption increase productivity, quality, and sustainable development. In this research, we present a scientific mapping precision techniques breakthrough technologies in agriculture, so-called Digital Agriculture. To do this, used 4694 documents from Web Science database perform Bibliometric Performance Network Analysis literature using SciMAT software with support PICOC protocol. Our findings presented 22 strategic themes related Agriculture, such as Internet Things (IoT), Unmanned Aerial Vehicles (UAV) Climate-smart Agriculture (CSA), among others. thematic network structure nine most important clusters (motor themes) was an in-depth discussion performed. evolution map provides broad perspective how field has evolved over time 1994 2020. addition, our results discuss main challenges opportunities for research practice study. provide comprehensive overview These show subjects analyzed on topic basis insights future research.

Язык: Английский

Процитировано

50