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Applied Sciences
Special Issues
Innovative Machinery and Technologies Applied in Agriculture Engineering
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Innovative Machinery and Technologies Applied in Agriculture Engineering

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Agricultural Science and Technology".

Deadline for manuscript submissions: 20 July 2024 | Viewed by 1989

Special Issue Editor

Prof. Dr. Górnicki Krzysztof

E-Mail Website
Guest Editor
Institute of Mechanical Engineering, Warsaw University of Life Sciences, Nowoursynowska 164 St., 02-787 Warsaw, Poland
Interests: heat and mass transfer; drying; rehydration; modelling; ANN; optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue will focus on the innovative machinery and technologies applied in agriculture engineering. Agricultural engineering is the branch of engineering that attends to the design and exploitation of farm machinery and devices, the location and planning of farm structures, farm drainage, soil management and erosion control, water supply and irrigation, rural electrification, farm product processing and the challenge of deriving renewable energy from agricultural products. Innovative machines or novel technologies enable the solution of many of the problems that arise in agricultural engineering. Therefore, we invite the submission of papers that attend to the following areas of interest:

  • Device and machine design;
  • Device and machine exploitation;
  • Technical diagnostics;
  • System and process modeling;
  • Processes optimization;
  • Innovative technologies in agricultural engineering.

Prof. Dr. Górnicki Krzysztof
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. Applied Sciences 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 2400 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 engineering
  • agricultural machinery
  • computer simulation
  • drying
  • process modeling
  • optimization
  • technical diagnostics
  • renewable energy sources

Published Papers (2 papers)

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Research

18 pages, 935 KiB  
Article
Some Aspects of the Modelling of Dried Red Beets Rehydration Process
by Agnieszka Kaleta, Krzysztof Górnicki, Marko Obranović and Krzysztof Kosiorek
Appl. Sci. 2024, 14(3), 1016; https://doi.org/10.3390/app14031016 - 25 Jan 2024
Viewed by 698
Abstract
Some dehydrated products must be rehydrated before consumption or further industry processing. Optimization of the rehydration process needs mathematical models of the process. Despite the widespread use of computers and their associated software, empirical equations are still widely used in view of their [...] Read more.
Some dehydrated products must be rehydrated before consumption or further industry processing. Optimization of the rehydration process needs mathematical models of the process. Despite the widespread use of computers and their associated software, empirical equations are still widely used in view of their simplicity and ease of computation. The mathematical description of the kinetics of mass gain, volume increase, dry matter loss, and moisture content increase and changes of rehydration indices during the rehydration of dried red beets was investigated. The effects of drying air temperature (Td), drying air velocity (vd), characteristic dimension (L), and rehydration temperature (Tr) on model constants were also examined. Red beets cubes (10 mm) and slices (5 and 10 mm) were dried in natural convection (vd = 0.01 m/s), forced convection (vd = 2 m/s), and fluidization (vd = 6 m/s) at Td = 50, 60, and 70 °C. The rehydration was conducted in distilled water at Tr = 20, 45, and 70 °C. The kinetics of rehydrating dried red beets was modelled applying five empirical models: Peleg, Lewis (Newton), Henderson–Pabis, Page, and modified Page. Equations were developed to make the model constants dependent on Td, vd, L, and Tr. Artificial neural networks (ANNs) (feedforward multilayer perceptron) were adopted to condition the rehydration indices on Td, vd, L, and Tr. The following models can be recommended as the most acceptable: (1) the modified Page model for mass gain (RMSE = 0.0236–0.0897) and for volume increase (RMSE = 0.0213–0.0972), (2) the Peleg model for dry mass loss (RMSE = 0.0161–0.610), and (3) the Henderson–Pabis model for moisture content increase (RMSE = 0.0350–0.1062). The ANNs performed the rehydration indices in an acceptable way (RMSE = 0.0528–0.2285). Both the rehydration indices and model constants depended (but to a different degree) on the investigated drying and rehydration conditions. Full article
(This article belongs to the Special Issue Innovative Machinery and Technologies Applied in Agriculture Engineering)
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18 pages, 18910 KiB  
Article
Structural Strength Analysis of a Rotary Drum Mower in Transportation Position
by H. Kursat Celik, Ibrahim Akinci, Nuri Caglayan and Allan E. W. Rennie
Appl. Sci. 2023, 13(20), 11338; https://doi.org/10.3390/app132011338 - 16 Oct 2023
Viewed by 931
Abstract
A rotary drum mower is a tractor-mounted harvester used for harvesting green fodder plants in agricultural fields. During transportation, it experiences significant dynamic road reaction forces that can cause deformation and functional failures. This study focuses on analysing the deformation behaviour of the [...] Read more.
A rotary drum mower is a tractor-mounted harvester used for harvesting green fodder plants in agricultural fields. During transportation, it experiences significant dynamic road reaction forces that can cause deformation and functional failures. This study focuses on analysing the deformation behaviour of the machine during transportation to test the machine’s failure condition. To conduct the strength analysis, a total work cycle scenario reflecting actual load conditions and design challenges was created. Experimental strain-gauge-based stress analysis and advanced computer-aided engineering (CAE) simulation methods were employed. The study successfully conducted experimental stress analysis, 3D solid modelling, and validated finite element analysis (FEA). A comparison between experimental and simulation results showed an average relative difference of 24.25% with a maximum absolute difference of approximately 5 MPa. No functional failure issues were observed during physical experiments. The study also revealed that the mean dynamic loading value, when compared to the static linkage position, was calculated as 3.65 ± 0.40. Overall, this research provides a valuable approach for future studies on complex stress and deformation evaluations of agricultural machinery and equipment. Full article
(This article belongs to the Special Issue Innovative Machinery and Technologies Applied in Agriculture Engineering)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Design and Experimentation of a Machine Vision-Based Fresh Cucumber Mass Grader
Author: Liu
Highlights: Novel Grading Mechanism: Introduces a fixed tray-type mechanism for grading North China-type cucumbers, ensuring no damage during the process. Innovative CNN Structure: Proposes MassNet, a convolutional neural network, for efficient feature extraction and mass prediction from a single RGB view. High-Performance Machine: Validates the cucumber grading system with a maximum capacity of 2.3t/hr, achieving 93% grading efficiency in online experiments.

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