Evaluation method and design of greenhouse pear pollination drones based on grounded theory and integrated theory DOI Creative Commons
Tao Wang, YanXiao Zhao,

Leah Ling Li Pang

et al.

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(10), P. e0311297 - e0311297

Published: Oct. 29, 2024

Greenhouse cultivation promotes an efficient and environmentally friendly agricultural production model, significantly enhancing resource sustainability advancing sustainable agriculture. Traditional greenhouse pollination methods are inefficient labor-intensive, limiting the economic benefits of pear cultivation. To improve efficiency achieve fully automated mechanized operations, innovative design method for drones has been developed. First, criteria were extracted using Grounded Theory (GT), Analytic Hierarchy Process (AHP) was employed to determine weight user demand evaluation indicators. Next, Quality Function Deployment (QFD) translated needs into technical requirements, resulting in final ranking element weights. The drone then designed based on these weighted rankings, yielding optimal solution. This quantifies functional requirements product, effectively identifying key proposing targeted solutions. Additionally, it provides a reference other highly machinery products.

Language: Английский

Advances in apple’s automated orchard equipment: A comprehensive research DOI
Mustafa Mhamed, Zhao Zhang, Jiangfan Yu

et al.

Computers and Electronics in Agriculture, Journal Year: 2024, Volume and Issue: 221, P. 108926 - 108926

Published: April 23, 2024

Language: Английский

Citations

21

Drones in Precision Agriculture: A Comprehensive Review of Applications, Technologies, and Challenges DOI Creative Commons

Ridha Guebsi,

Sonia Mami,

Karem Chokmani

et al.

Drones, Journal Year: 2024, Volume and Issue: 8(11), P. 686 - 686

Published: Nov. 19, 2024

In the face of growing challenges in modern agriculture, such as climate change, sustainable resource management, and food security, drones are emerging essential tools for transforming precision agriculture. This systematic review, based on an in-depth analysis recent scientific literature (2020–2024), provides a comprehensive synthesis current drone applications agricultural sector, primarily focusing studies from this period while including few notable exceptions particular interest. Our study examines detail technological advancements systems, innovative aerial platforms, cutting-edge multispectral hyperspectral sensors, advanced navigation communication systems. We analyze diagnostic applications, crop monitoring mapping, well interventional like spraying drone-assisted seeding. The integration artificial intelligence IoTs analyzing drone-collected data is highlighted, demonstrating significant improvements early disease detection, yield estimation, irrigation management. Specific case illustrate effectiveness various crops, viticulture to cereal cultivation. Despite these advancements, we identify several obstacles widespread adoption, regulatory, technological, socio-economic challenges. particularly emphasizes need harmonize regulations beyond visual line sight (BVLOS) flights improve economic accessibility small-scale farmers. review also identifies key opportunities future research, use swarms, improved energy autonomy, development more sophisticated decision-support systems integrating data. conclusion, underscore transformative potential technology sustainable, productive, resilient agriculture global 21st century, highlighting integrated approach combining innovation, adapted policies, farmer training.

Language: Английский

Citations

16

Advancements in artificial pollination of crops: from manual to autonomous DOI

Leilei He,

Xiaojuan Liu, Yezhang Ding

et al.

Computers and Electronics in Agriculture, Journal Year: 2025, Volume and Issue: 231, P. 110067 - 110067

Published: Feb. 5, 2025

Language: Английский

Citations

1

Genetic Diversity and Breeding of Cactus (Opuntia spp.) DOI
Abdelghani Tahiri, Naïma Ait Aabd, Redouan Qessaoui

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

1

Pollinators enhance the production of a superior strawberry – A global review and meta-analysis DOI Creative Commons
Agnieszka Gudowska, Aleksandra Cwajna,

Emilia Marjańska

et al.

Agriculture Ecosystems & Environment, Journal Year: 2023, Volume and Issue: 362, P. 108815 - 108815

Published: Dec. 6, 2023

Strawberry (Fragaria x ananasa Duch.) is the most economically important soft fruit worldwide. While self- and wind-pollination possible for strawberry, without biotic pollination (animal pollinators, including artificial by humans) rate of strawberry flowers rarely exceeds 60% thus production decreased. At a time widely recognized decline pollinators increasing global demand balanced food, we need comprehensive understanding worldwide valuation these ecosystem services. In this paper, use transparent systematic review process to detect gaps in available literature. By applying multilevel meta-analytic models, quantified contribution different pollinator types fruits. Our showed that research on clearly concentrated European countries, with limited information Asia – largest producer. Additionally, detected disproportions across topics, stressing further preferences between cultivars occurrence managed wild bee communities. The overall estimate benefit crops average 25% reduction weight plants not receiving treatment. This similar regardless pollinating species. mean amount globally (2011–2020) receivable producers from purchasers due $5.36 billion per year. Moreover, demonstrated are dependent or set 43% fewer seeds (fertilized achenes) than biotically pollinated plants. Such huge seed can cause deformation reduce commercial value strawberries. Together, findings indicate critical role quality. To ensure services farms produce best-quality fruits, growers should take action sustain healthy communities utilize them optimal cultivar.

Language: Английский

Citations

11

Accurate and robust pollinations for watermelons using intelligence guided visual servoing DOI
Khubaib Ahmad, Ji Eun Park, Talha Ilyas

et al.

Computers and Electronics in Agriculture, Journal Year: 2024, Volume and Issue: 219, P. 108753 - 108753

Published: Feb. 24, 2024

Language: Английский

Citations

4

Leveraging imitation learning in agricultural robotics: a comprehensive survey and comparative analysis DOI Creative Commons

Siavash Mahmoudi,

Amirreza Davar,

Pouya Sohrabipour

et al.

Frontiers in Robotics and AI, Journal Year: 2024, Volume and Issue: 11

Published: Oct. 17, 2024

Imitation learning (IL), a burgeoning frontier in machine learning, holds immense promise across diverse domains. In recent years, its integration into robotics has sparked significant interest, offering substantial advancements autonomous control processes. This paper presents an exhaustive insight focusing on the implementation of imitation techniques agricultural robotics. The survey rigorously examines varied research endeavors utilizing to address pivotal challenges. Methodologically, this comprehensively investigates multifaceted aspects applications encompasses identification tasks that can potentially be addressed through detailed analysis specific models and frameworks, thorough assessment performance metrics employed surveyed studies. Additionally, it includes comparative between conventional methodologies realm findings derived from unveil profound insights These methods are highlighted for their potential significantly improve task execution dynamic high-dimensional action spaces prevalent settings, such as precision farming. Despite promising advancements, discusses considerable challenges data quality, environmental variability, computational constraints IL must overcome. also addresses ethical social implications implementing technologies, emphasizing need robust policy frameworks manage societal impacts automation. hold implications, showcasing revolutionize processes contributes envisioning innovative tools within domain, heightened productivity efficiency robotic systems. It underscores remarkable enhancements various processes, signaling transformative trajectory sector, particularly

Language: Английский

Citations

4

Detection of Power Poles in Orchards Based on Improved Yolov5s Model DOI Creative Commons
Yali Zhang,

Xiaoyang Lu,

Wanjian Li

et al.

Agronomy, Journal Year: 2023, Volume and Issue: 13(7), P. 1705 - 1705

Published: June 26, 2023

During the operation of agricultural unmanned aerial vehicles (UAVs) in orchards, presence power poles and wires pose a serious threat to flight safety, can even lead crashes. Due difficulty directly detecting wires, this research aimed quickly accurately detect wire poles, proposed an improved Yolov5s deep learning object detection algorithm named Yolov5s-Pole. The enhances model’s generalization ability robustness by applying Mixup data augmentation technique, replaces C3 module with GhostBottleneck reduce parameters computational complexity, incorporates Shuffle Attention (SA) improve its focus on small targets. results show that when Yolov5s-Pole model was used for accuracy, recall, mAP@50 were 0.803, 0.831, 0.838 respectively, which increased 0.5%, 10%, 9.2% compared original model. Additionally, weights, parameters, GFLOPs 7.86 MB, 3,974,310, 9, respectively. Compared model, these represent compression rates 42.2%, 43.4%, 43.3%, time single image using 4.2 ms, good under different lighting conditions (dark, normal, bright) demonstrated. is suitable deployment UAVs’ onboard equipment, great practical significance ensuring efficiency safety UAVs.

Language: Английский

Citations

11

Harnessing the full potential of drones for fieldwork DOI
Thilina D. Surasinghe, Kunwar K. Singh, Amy E. Frazier

et al.

BioScience, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 25, 2025

Abstract Field-based research in the biological sciences encounters several challenges, including cost, accessibility, safety, and spatial coverage. Drones have emerged as a transformative technology to address these challenges while providing less intrusive alternative field surveys. Although drones mainly been used for high-resolution image collection, their capabilities extend beyond mapping production. They can be tailored track wildlife, measure environmental parameters, collect physical samples, versatility enables researchers tackle variety of biodiversity conservation challenges. In this article, we advocate integrated more comprehensively into field-based research, from site reconnaissance sampling, interventions, monitoring. We discuss future innovations needed harness full potential, customized instrumentation, fit-for-purpose software apps, better integration with existing online databases. also support leveraging community scientists empowering citizens contribute scientific endeavors promoting stewardship via drones.

Language: Английский

Citations

0

Vapor pressure deficit control and mechanical vibration techniques to induce self-pollination in strawberry flowers DOI Creative Commons
Hyein Lee, Meiyan Cui, Byungkwan Lee

et al.

Plant Methods, Journal Year: 2025, Volume and Issue: 21(1)

Published: Feb. 25, 2025

Abstract Background Pollination strategies to supplement or replace insect pollinators are needed produce marketable strawberry fruits in indoor vertical farms. To ensure the self-pollination of flowers, anther dehiscence, and pollen attachment were investigated under different vapor pressure deficit (VPD) conditions external mechanical wave vibrations. Results The proportion dehisced anthers was examined VPDs 2.06, 1.58, 0.33 kPa, projected area clumps assessed 2.06 kPa. After exposing flowers a VPD vibrations with various frequency (Hz) root mean square acceleration (m s −2 ) combinations used evaluate pollination effectiveness. underwent complete dehiscence at clump ejection index highest Pollen detachment effective 800 Hz 40 m , while stigma most 100 30 . Conclusions These findings demonstrate that high promotes timing facilitates formation, specific vibration frequencies optimize attachment, offering an strategy for controlled farming.

Language: Английский

Citations

0