Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.3
3.6
Journals
Agriculture
Special Issues
Intelligent Agricultural Seeding Equipment
share announcement

Intelligent Agricultural Seeding Equipment

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Agricultural Technology".

Deadline for manuscript submissions: 10 September 2026 | Viewed by 1387

Special Issue Editor

Prof. Dr. Ying Zang

E-Mail Website
Guest Editor
College of Engineering, South China Agricultural University, Guangzhou 510642, China
Interests: agricultural machinery; seed metering device; smart agricultural seeding devices; precision seeding; intelligent technologies; modern agriculture; seeding data collection
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Amid modern agriculture’s key challenges—such as labor shortages and the urgent need for optimized resource utilization—meeting the growing demands for efficient, precise, and sustainable sowing stands as a critical task. Traditional sowing methods often lack essential accuracy, uniform distribution, and adaptability to varied field conditions, which directly harm crop emergence rates, potential yields, and overall farm productivity. Thus, exploring intelligent technologies to innovate seeding equipment is vital for boosting sowing efficiency, cutting resource waste, and laying a solid foundation for high-quality crop production.​ Smart agricultural seeding devices integrate advanced tools like precision sensors, IoT connectivity, AI algorithms, and automated control systems. They adjust seeding depth and spacing in real time based on soil conditions and crop types to ensure uniform germination; minimize seed and fertilizer waste by matching input quantities to field needs, reducing both production costs and environmental impact; support data-driven farm management by collecting and analyzing sowing-related data (e.g., seeding rate, equipment performance) for informed decisions; and enhance operational efficiency by cutting down manual intervention.​

This Special Issue focuses on smart seeding aims to showcase its latest innovations, development progress, and role in precision agriculture. It involves interdisciplinary cooperation, combining agricultural science with mechanical engineering, computer science, etc., covering both field crop seeding and specialty crop seeding. All types of articles, such as original research, opinions, and reviews, are welcome.

Prof. Dr. Ying Zang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • agricultural machinery
  • seed metering device
  • smart agricultural seeding devices
  • precision seeding
  • intelligent technologies
  • modern agriculture
  • seeding data collection

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

31 pages, 21197 KB  
Article
Research on Road Slope Estimation and the Passable Area Modelling Method in Hilly and Mountainous Areas Based on Multi-Sensor Fusion
by Hequan Miao, Chunjiang Bao, Jian Wu and Peisong Diao
Agriculture 2026, 16(7), 776; https://doi.org/10.3390/agriculture16070776 - 31 Mar 2026
Viewed by 422
Abstract
Autonomous tractors have been shown to possess the capability to ensure a high degree of operational precision during seeding activities on flat terrain. However, in topographically challenging environments characterised by significant elevations and pronounced variations in slope, factors such as road gradients have [...] Read more.
Autonomous tractors have been shown to possess the capability to ensure a high degree of operational precision during seeding activities on flat terrain. However, in topographically challenging environments characterised by significant elevations and pronounced variations in slope, factors such as road gradients have been shown to compromise the precision of satellite-based positioning systems. This, in turn, can lead to alterations in vehicle posture and the generation of disparate longitudinal driving forces between the left and right tyres. It is important to note that this deviation from the predefined path has the potential to result in rollover accidents. Evidence has been presented that indicates a correlation between road gradient and vehicle roll motion. The proposed methodology is an algorithmic approach to the estimation of lateral slope, integrating inertial measurement unit (IMU) sensors and ground-based ultrasonic radars. This algorithmic approach is proposed as a means to achieve more accurate estimations of lateral slope. The initial development of the vehicle dynamics model was based on slope operation requirements, and the model was endowed with eight degrees of freedom. The utilisation of an unscented Kalman filter (UKF) facilitates the integration of inertial measurement unit (IMU) and ground-based ultrasonic radar measurements, thereby enabling real-time estimation of key motion states, such as lateral slope. The validity of the proposed algorithm was established through a combination of hardware-in-the-loop testing and field trials involving real tractors. The findings indicate that the implementation of this algorithm leads to a substantial enhancement in the trajectory tracking accuracy of tractors during slope operations. This enhancement is characterised by a substantial reduction in lateral deviation and an effective augmentation in the operational pass rate. In the course of empirical trials conducted in a mountainous environment, the lateral positioning deviation during straight-line driving was diminished from 10 cm to within 5 cm. Concurrently, the precision of lateral slope estimation was enhanced to 0.04 degrees. Full article
(This article belongs to the Special Issue Intelligent Agricultural Seeding Equipment)
►▼ Show Figures

Figure 1

23 pages, 3399 KB  
Article
Design and Experimental Research of a CFD-DEM Coupled Pelleted Rice Seeds UAV Hole-Sowing Seed Feeding Device
by Qingqing Wang, Donghan Xu, Bin Zhu, Chunxia Jiang, Yinhu Qiao, Hualong Li and Ru Yang
Agriculture 2026, 16(5), 561; https://doi.org/10.3390/agriculture16050561 - 28 Feb 2026
Viewed by 454
Abstract
To achieve high-speed quantitative hole sowing of rice using an unmanned aerial vehicle (UAV), this study proposes an agricultural UAV pneumatic hole sowing system suitable for high-speed quantitative hole sowing. This system is based on pelletizing rice seeds. A pneumatic seed distribution system [...] Read more.
To achieve high-speed quantitative hole sowing of rice using an unmanned aerial vehicle (UAV), this study proposes an agricultural UAV pneumatic hole sowing system suitable for high-speed quantitative hole sowing. This system is based on pelletizing rice seeds. A pneumatic seed distribution system based on the Venturi effect was designed, with a seed feeding device that employs a computational fluid dynamics–discrete element method (CFD-DEM) coupled simulation method to construct a gas–solid two-phase flow simulation model that simulates actual field sowing conditions and analyzes seed transport characteristics. Using the seed feeding device blending chamber height, expansion section cone angle, and inlet airflow velocity as experimental factors, and evaluating seed distribution statistics based on the hole formation ratio(HFR) and hole spacing coefficient of variation (HSCV), the study achieved a comprehensive statistical analysis of seed distribution patterns. The Box–Behnken orthogonal experiment optimized the structural parameters of the seed feeding device, determining the optimal airflow velocity during seeding. The optimized parameter combination yielded a blending chamber height of 15.59 mm, an expansion section cone angle of 22.20°, and an inlet airflow velocity of 19.67 m/s, corresponding to an HFR of 84.66% and an HSCV of 6.95%. Field trials validated an HFR of 86.25% and an HSCV of 6.83%. This study provides theoretical and technical support for the design of high-speed hole -sowing equipment for rice using a UAV. Full article
(This article belongs to the Special Issue Intelligent Agricultural Seeding Equipment)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop