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Agriculture
Special Issues
Knowledge and Techniques Application in Agriculture
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Knowledge and Techniques Application in Agriculture

A special issue of Agriculture (ISSN 2077-0472).

Deadline for manuscript submissions: closed (1 June 2018) | Viewed by 13294

Special Issue Editor

Dr. Ritaban Dutta

E-Mail Website
Guest Editor
CSIRO Data61, Hobart, Tasmania 7001, Australia
Interests: big data analytics; remote sensing; machine learning; precision agriculture; digital agronomy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Research in agricultural information and knowledge management will be the key pathway to handle the world’s food crisis in the decades to come. In the last decade, digital disruptions and digitization of information in a form of Big Data has given birth of a new era of Digital Agriculture, where satellites and drones could be used to monitor and measure what we grow and feed. However, ultimately, challenge remains in the extraction of knowledge from the data, developing techniques of handling data to manage knowledge and develop decision application for a better and sustainable agriculture. In today’s world, demand of suitable agricultural applications is dominating the agricultural research space, where researcher are continuously innovating novel techniques to make agriculture more productive and profitable. It is appropriate and timely to publish a Special Issue in Agriculture, which highlights the progress made in developing strategies for the successful adoption of knowledge and techniques application in agriculture. I invite those working in this area to submit manuscripts summarizing results of this research for this Special Issue.

Dr. Ritaban Dutta
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 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. Agriculture 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

  • Knowledge management and IoT
  • Platform technology in agriculture
  • Data Driven Techniques in Agriculture
  • Feature Engineering for Knowledge
  • Agricultural Data
  • Climate and Agriculture
  • Decision Making Using Knowledge
  • Digital Agriculture Future Trends

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Published Papers (2 papers)

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Research

22 pages, 5355 KiB  
Article
The O3-Farm Project: First Evaluation of a Business Process Management (BPM) Approach through the Development of an Experimental Farm Management System for Milk Traceability
by Mauro Zaninelli and Matías Reyes Pace
Agriculture 2018, 8(9), 139; https://doi.org/10.3390/agriculture8090139 - 8 Sep 2018
Cited by 4 | Viewed by 7309
Abstract
The modeling of farm workflows, and the use of a business process management (BPM) paradigm, could enable improvement in the development of farm management information systems (FMIS). A rapid design of software applications could be possible and quick development, intrinsically service oriented, could [...] Read more.
The modeling of farm workflows, and the use of a business process management (BPM) paradigm, could enable improvement in the development of farm management information systems (FMIS). A rapid design of software applications could be possible and quick development, intrinsically service oriented, could be achieved through the use of a software suite for the implementation of BPM diagrams. As the first evaluation of this paradigm, an experimental FMIS was developed considering a “use-case” whose target was to develop a hardware and software solution for the traceability of milk. The outcomes of this activity have shown that the software application developed (O3-Farm) was able to provide all features of the database application previously used for the traceability of milk. At the same time, it was able to provide some new features such as increased usability, portability and efficiency. Also, the chance to integrate it with other possible software applications was increased as a result of a better sharing of agricultural data. This seems to suggest that a design, and a software suite, based on the BPM paradigm, could be a valid way for the development of FMIS also in line with the farm software environment models if its abilities to describe, use and deploy, workflows and software services are taken into consideration. Full article
(This article belongs to the Special Issue Knowledge and Techniques Application in Agriculture)
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11 pages, 2541 KiB  
Article
Modelling the Collection and Delivery of Sheep Milk: A Tool to Optimise the Logistics Costs of Cheese Factories
by Maria Caria, Giuseppe Todde and Antonio Pazzona
Agriculture 2018, 8(1), 5; https://doi.org/10.3390/agriculture8010005 - 1 Jan 2018
Cited by 11 | Viewed by 5165
Abstract
The milk transformation process, in the last thirty years, moved from on-farm to centralised cheese factories, affecting the management of transport logistics. In Sardinia, the presence of about 12,000 dairy sheep farms, located in rural areas with poor condition of road network, makes [...] Read more.
The milk transformation process, in the last thirty years, moved from on-farm to centralised cheese factories, affecting the management of transport logistics. In Sardinia, the presence of about 12,000 dairy sheep farms, located in rural areas with poor condition of road network, makes collecting milk a significant impact on profit, affecting the costs of milk transportation. Moreover, dairy sheep farming is characterized by seasonal production, this means that the amount of milk that is produced by each farm differs significantly over the year. The objective of this work was to develop a decision support tool that, while optimising milk collection routes, reduced the costs of milk transport, thus improving the density of collection. The tool developed ad hoc in this study used GPS map location and milk volumes of farms to calculate the cost per litre of milk for the regular routing, and to recalculate the same cost for the optimised collecting route. Results showed that this tool improved the efficiency of milk collection, reducing the number of routes and the driving distances. Furthermore, optimising the density of collection, the new routes improved the environmental impact and the transportation costs that are associated with logistic and traceability of raw sheep milk. Full article
(This article belongs to the Special Issue Knowledge and Techniques Application in Agriculture)
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