Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.7
3.4
Journals
Agronomy
Special Issues
Precision Operation Technology and Intelligent Equipment in Farmland—3rd Edition
share announcement

Precision Operation Technology and Intelligent Equipment in Farmland—3rd Edition

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Precision and Digital Agriculture".

Deadline for manuscript submissions: closed (15 October 2025) | Viewed by 1309

Special Issue Editors

Prof. Dr. Jun Ni

E-Mail Website
Guest Editor
College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China
Interests: agricultural smart sensor; agricultural intelligent equipment
Special Issues, Collections and Topics in MDPI journals
Dr. Lei Feng

E-Mail Website
Guest Editor
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
Interests: agricultural systems engineering; agricultural electrification and automation
Special Issues, Collections and Topics in MDPI journals
Dr. Lvhua Han

E-Mail Website
Guest Editor
Department of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Interests: agricultural equipment; precision agriculture
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The use of precision operation and intelligent equipment in fields is at the frontier of modern agricultural technology development. Key areas include adjusting measures to local conditions, the intelligent management of crop production, maximizing the production potential of farmland, and realizing the efficient utilization of key factors in agricultural production and ecological environment protection. In recent years, experts have conducted much research on the interaction mechanism of crops, soil, and other environmental factors; the rapid acquisition of information; and the employment of precise control models of crop production and intelligent equipment, using modern information and intelligent control technology. These remarkable achievements have played an important role in updating traditional agriculture and developing modern agriculture practices with high yield, quality, efficiency, ecological sustainability, and safety.

This Special Issue welcome papers involved in research on precision operation and intelligent equipment in fields. Specific topics include, but are not limited to, the following:

  1. Agricultural sensing mechanisms and new sensors;
  2. Machine–soil–crop interaction mechanisms;
  3. Crop production control models;
  4. New agricultural machinery and field robots;
  5. Intelligent control of agricultural machinery;
  6. Unmanned operations.

Prof. Dr. Jun Ni
Dr. Lei Feng
Dr. Lvhua Han
Guest Editors

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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Agronomy is an international peer-reviewed open access monthly 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

  • precision operation
  • agricultural sensor
  • agricultural machinery
  • field robots
  • machine–soil–crop interaction
  • interaction mechanism
  • intelligent control
  • unmanned and automatic operations

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.

Related Special Issue

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

18 pages, 6804 KB  
Article
Three-Dimensional Spectral Index-Driven Nondestructive Quantification of Chlorophyll in Winter Wheat: Cross-Phenology Extrapolation and Independent Validation
by Zhijun Li, Wei Zhang, Zijun Tang, Youzhen Xiang and Fucang Zhang
Agronomy 2025, 15(10), 2376; https://doi.org/10.3390/agronomy15102376 - 11 Oct 2025
Viewed by 382
Abstract
As a staple cereal worldwide, winter wheat plays a pivotal role in food security. Leaf chlorophyll serves as a direct indicator of photosynthetic performance and nitrogen nutrition, making it critical for precision management and yield gains. Consequently, rapid, nondestructive, and high-accuracy remote-sensing retrievals [...] Read more.
As a staple cereal worldwide, winter wheat plays a pivotal role in food security. Leaf chlorophyll serves as a direct indicator of photosynthetic performance and nitrogen nutrition, making it critical for precision management and yield gains. Consequently, rapid, nondestructive, and high-accuracy remote-sensing retrievals are urgently needed to underpin field operations and precision fertilization. In this study, canopy hyperspectral reflectance together with destructive chlorophyll assays were systematically acquired from Yangling field trials conducted during 2018–2020. Three families of spectral indices were devised: classical empirical indices; two-dimensional optimal spectral indices (2D OSI) selected by correlation-matrix screening; and novel three-dimensional optimal spectral indices (3D OSI). The main contribution lies in devising novel 3D OSIs that combine three spectral bands and demonstrating how their fusion with classic two-band indices can improve chlorophyll quantification. Correlation analysis showed that most empirical vegetation indices were significantly associated with chlorophyll (p < 0.05), with the new double difference index (NDDI) giving the strongest relationship (R = 0.637). Within the optimal-index sets, the difference three-dimensional spectral index (DTSI; 680, 807, and 1822 nm) achieved a correlation coefficient of 0.703 (p < 0.05). Among all multi-input fusion schemes, fusing empirical indices with 3D OSI and training with RF delivered the best validation performance (R2 = 0.816, RMSE = 0.307 mg g−1, MRE = 11.472%), and external data further corroborated its feasibility. Altogether, integrating 3D spectral indices with classical vegetation indices and deploying RF enabled accurate, nondestructive estimation of winter wheat chlorophyll, offering a new hyperspectral pathway for monitoring crop physiological status and advancing precision agricultural management and fertilization, can guide in-season fertilization to optimize nitrogen use, thereby advancing precision agriculture. Full article
(This article belongs to the Special Issue Precision Operation Technology and Intelligent Equipment in Farmland—3rd Edition)
►▼ Show Figures

Figure 1

16 pages, 2833 KB  
Article
Design and Tests of a Large-Opening Flexible Seedling Pick-Up Gripper with Multiple Grasping Pins
by Luhua Han, Meijia Zhang, Yan Wang, Guoxin Ma, Qizhi Yang and Yang Liu
Agronomy 2025, 15(7), 1634; https://doi.org/10.3390/agronomy15071634 - 4 Jul 2025
Viewed by 566
Abstract
The pick-up gripper, as a core component of automatic transplanting systems, presents challenges in reliably grasping seedlings. In this study, a large-opening flexible seedling pick-up gripper was designed based on standard trays and seedling characteristics. Structural design and force analysis of the grasping [...] Read more.
The pick-up gripper, as a core component of automatic transplanting systems, presents challenges in reliably grasping seedlings. In this study, a large-opening flexible seedling pick-up gripper was designed based on standard trays and seedling characteristics. Structural design and force analysis of the grasping mechanism were conducted to develop a functional prototype. As this represented the first prototype of this new gripper, multi-factor orthogonal tests and performance tests under local conditions were performed to evaluate its grasping effectiveness. It was found that the end diameter of the pick-up pin and the extraction speed for lifting plug seedlings vertically had the most significant effects, followed by the penetration depth and grasping force. The optimum grasping effectiveness was achieved when the end diameter of the pick-up pin was 1.2 mm, the penetration depth in the top straight line of the pick-up pin was 40 mm, the grasping force for squeezing root lumps was 0.4 MPa, and the extraction speed for lifting plug seedlings in a vertical direction was 900 mm/s. For typical vegetable seedlings, the average success rate in transplanting was up to 95%. Under the combined actions of penetrating, squeezing, and extracting operations, plug seedlings could be efficiently picked out for efficient transplanting. Full article
(This article belongs to the Special Issue Precision Operation Technology and Intelligent Equipment in Farmland—3rd Edition)
►▼ 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