Special Issue "Smart Decision-Making Systems for Precision Agriculture"

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Farming Sustainability".

Deadline for manuscript submissions: 31 December 2020.

Special Issue Editors

Dr. Jaume Arnó
Website
Guest Editor
Research Group in AgroICT & Precision Agriculture, University of Lleida, 25198, Lleida (Spain)
Interests: precision agriculture; decision support systems; data analysis; geostatistics; sensors and monitoring; sampling in agriculture
Special Issues and Collections in MDPI journals
Prof. Dr. José A. Martínez-Casasnovas
Website
Guest Editor
Research Group in AgroICT & Precision Agriculture, University of Lleida, 25198, Lleida (Spain)
Interests: precision agriculture; digital soil mapping; spatial data analysis; remote sensing; site-specific crop management
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Precision Agriculture (PA) is, conceptually, an agricultural management strategy that aims to improve resource efficiency, productivity, and quality based on a better understanding of the spatial and temporal variability that is usually inherent in many farms. Acquisition of spatial and temporal data on soils and crops is the starting point of the process. For that, farmers usually have a wide variety of proximal and remote sensors, in addition to global navigation satellite systems to georeference all these data. However, moving from sensor data to piece of information, intermediate stages must be addressed in order to make the best agronomic decision, which is still a bottleneck in the real implementation of PA. Thus, data processing, mapping, data analysis, delineation of management zones or prescription map creation are steps to be solved before using variable-rate devices installed on agricultural equipment. Making the right decision at the right time to apply the right amount of inputs is an important issue on which the economy and sustainability of agricultural production ultimately depends. In this respect, the digital revolution in agriculture will only be feasible through the development of smart, compact and easy-to-use systems that, adapted to the needs of farmers, help in decision-making and to run management tools despite the complexity of these new technologies.

This Special Issue aims to contribute to the dissemination of new research findings related to (i) data processing and data analysis in the spatial and temporal domains, (ii) decision support, (iii) delineation of potential management zones, (iv) agricultural internet of things (IoT), (v) Agro Big Data, and (vi) efficient sampling methods in forecasting tasks.

Dr. Jaume Arnó
Prof. José A. Martínez-Casasnovas
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 papers will be 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 1600 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 agriculture
  • post-process data analysis
  • real-time data processing
  • smart sampling
  • Internet of Things (IoT)
  • decision making
  • smart farming

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessArticle
A Joint Decision-Making Approach for Tomato Picking and Distribution Considering Postharvest Maturity
Agronomy 2020, 10(9), 1330; https://doi.org/10.3390/agronomy10091330 - 04 Sep 2020
Abstract
Fruit maturity is an essential factor for fresh retailers to make economical distribution scheduling and scientific market strategies. In the context of farm-to-door mode, the fresh retailers could incorporate the postharvest maturity time, picking time and distribution time to deliver high-quality fruits to [...] Read more.
Fruit maturity is an essential factor for fresh retailers to make economical distribution scheduling and scientific market strategies. In the context of farm-to-door mode, the fresh retailers could incorporate the postharvest maturity time, picking time and distribution time to deliver high-quality fruits to consumers. This study selects climacteric tomato fruits and formulates a postharvest maturity model by capturing the firmness and soluble solid content (SSC) data during maturing. A joint picking and distribution model is proposed to ensure tomatoes could arrive at consumers within expected maturity time windows. To improve the feasibility of proposed model, an improved genetic algorithm (IGA) is designed to obtain solutions. The results demonstrate that the joint model could optimize the distribution routing to improve consumer satisfaction and reduce the order fulfillment costs. The proposed method provides precise guidance for tomato online retailers by taking advantage of postharvest maturity data, which is conducive to sustainable development of fresh e-ecommerce. Full article
(This article belongs to the Special Issue Smart Decision-Making Systems for Precision Agriculture)
Show Figures

Figure 1

Open AccessArticle
Fruit Morphological Measurement Based on Three-Dimensional Reconstruction
Agronomy 2020, 10(4), 455; https://doi.org/10.3390/agronomy10040455 - 25 Mar 2020
Cited by 3
Abstract
Three-dimensional (3D) shape information is valuable for fruit quality evaluation. Grading of the fruits is one of the important postharvest tasks that the fruit processing agro-industries do. Although the internal quality of the fruit is important, the external quality of the fruit influences [...] Read more.
Three-dimensional (3D) shape information is valuable for fruit quality evaluation. Grading of the fruits is one of the important postharvest tasks that the fruit processing agro-industries do. Although the internal quality of the fruit is important, the external quality of the fruit influences the consumers and the market price significantly. To solve the problem of feature size extraction in 3D fruit scanning, this paper proposes an automatic fruit measurement scheme based on a 2.5-dimensional point cloud with a Kinect depth camera. For getting a complete fruit model, not only the surface point cloud is obtained, but also the bottom point cloud is rotated to the same coordinate system, and the whole fruit model is obtained by iterative closest point algorithm. According to the centroid and principal direction of the fruit, the cut plane of the fruit is made in the x-axis, y-axis, and z-axis respectively to obtain the contour line of the fruit. The experiment is divided into two groups, the first group is various sizes of pears to get the morphological parameters; the second group is the various colors, shapes, and textures of many fruits to get the morphological parameters. Comparing the predicted value with the actual value shows that the automatic extraction scheme of the size information is effective and the methods are universal and provide a reference for the development of the related application. Full article
(This article belongs to the Special Issue Smart Decision-Making Systems for Precision Agriculture)
Show Figures

Figure 1

Back to TopTop