Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.3
3.4
Journals
Sensors
Special Issues
Sensors Integration in Agricultural Farm Mechanization and Food Processing Operations
sensors-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Sensors Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Sensors Integration in Agricultural Farm Mechanization and Food Processing Operations

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Smart Agriculture".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 7869

Special Issue Editor

Dr. Ravi Pandiselvam

E-Mail Website
Guest Editor
Central Plantation Crops Research Institute, Kasaragod, India
Interests: non-destructive methods; spectroscopy; online monitoring; food quality; food safety

Special Issue Information

Dear Colleagues,

Traditional agricultural techniques and practices may not be enough to meet the future global demands of food production due to the growing population. Advanced agricultural production and processing technologies are going to play a vital role in the development of sustainable crop and livestock farming. These modern techniques will be helpful in the agriculture production and food processing sector to maximizing the profit of farmers, entrepreneurs and industries by optimizing farmers’ productivity and efficiency to save time at lower input costs and maximize the food industries’ production. Production from farming has to be increased with environmentally friendly farming practices by reducing the application of agriculture inputs expenses such as seed, fuel, agrochemicals and time. Modern techniques are promising for the farming sector with the implementation and integration of sensors using the embedded system, AL, and ML techniques in agriculture production and food processing. At present, many sensors are available in agriculture practices for direct sensing and remote sensing to collect informative data for digitalization. The digitalization of collected data can be analyzed to take  wiser decisions by providing a better overview of their farm and agriculture input on demand. The applications of sensors are expanded in the area of food science and technology, such as food-quality monitoring, spoilage detection, adulteration detection, biochemical profiling of the products, food safety monitoring, etc.

This Special Issue intends to cover the recent progress in different aspects related to the real implementation and integration of novel sensors and their applications in agriculture and post-harvest processing operations. Sensors in agriculture are based on the requirements of farming operations and food processing operations, which need to be addressed with reduced cost and increased efficiency. All types of manuscripts (original research and reviews) providing new insights in the application and benefits of sensors in the areas of agriculture and post-harvest processing are invited. Articles may include, but are not limited to, the following topics.

Dr. Ravi Pandiselvam
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. Sensors 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

  • precision agriculture
  • non-destructive food quality testing
  • sensors’ applications in food packaging
  • detection and identification of crops
  • food adulteration detection
  • sensors for spoilage detection in fruits
  • sensors for food quality determination
  • online monitoring of food quality
  • sensor for agriculture robotics
  • crop and soil sensors
  • drones
  • variable-rate application machinery
  • artificial intelligence
  • machine learning
  • optical sensors
  • sensors for crop health status/pest management
  • sensors for crop phenotyping, germination, emergence and determination of the different growth stages of crops
  • remote sensing
  • non-destructive soil sensing
  • sensors for weed control
  • sensors for positioning, navigation and obstacle detection
  • sensor networks in agriculture

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.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (3 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

19 pages, 14059 KiB  
Article
A Monoblock Light-Scattering Milk Fat Percentage and Somatic Cell Count Sensor for Use in Milking Systems
by Alexey V. Shkirin, Maxim E. Astashev, Dmitry N. Ignatenko, Nikolai V. Suyazov, Sergey N. Chirikov, Vladimir V. Kirsanov, Dmitriy Y. Pavkin, Yakov P. Lobachevsky and Sergey V. Gudkov
Sensors 2023, 23(20), 8618; https://doi.org/10.3390/s23208618 - 21 Oct 2023
Viewed by 1596
Abstract
A monoblock light-scattering sensor, which is capable of measuring the fat content of milk and indicating the excess by which the somatic cell count (SCC) is over the permissible level, has been developed for installation in dairy systems. In order for the sensor [...] Read more.
A monoblock light-scattering sensor, which is capable of measuring the fat content of milk and indicating the excess by which the somatic cell count (SCC) is over the permissible level, has been developed for installation in dairy systems. In order for the sensor to perform measurements when the milking machine is working in the “milk plug” mode, a flow-through unit is designed in the form of a pipe with a lateral cylindrical branch, in which milk accumulates so as to eliminate large bubbles and achieve continuity of the milk flow. The operation of the sensor is based on the registration of the angular intensity distribution of light scattered in the transparent cylindrical segment of the tube branch. A semiconductor laser with a wavelength of 650 nm is used as a light source for determining scattering in milk. The angular distribution of the scattered light intensity (scattering indicatrix) is recorded using an axial photodiode array. The fat content is determined by the average slope of the measured scattering indicatrix in the range of scattering angles 72–162°. The SCC level is estimated from the relative deviation of the forward scatter intensity normalized to the backscatter intensity with respect to uninfected milk. The sensor has been tested on a Yolochka-type milking machine. Full article
(This article belongs to the Special Issue Sensors Integration in Agricultural Farm Mechanization and Food Processing Operations)
►▼ Show Figures

Figure 1

16 pages, 3254 KiB  
Article
Development of an Embedded Software and Control Kit to Be Used in Soilless Agriculture Production Systems
by Uğur Yegül
Sensors 2023, 23(7), 3706; https://doi.org/10.3390/s23073706 - 3 Apr 2023
Cited by 5 | Viewed by 2284
Abstract
Traditional agricultural methods, which are still adopted today, depend on many factors. Food production processes face serious risks, such as limited clean water resources and supplements such as phosphorus, in addition to weather conditions due to climate change, the distribution of pests and [...] Read more.
Traditional agricultural methods, which are still adopted today, depend on many factors. Food production processes face serious risks, such as limited clean water resources and supplements such as phosphorus, in addition to weather conditions due to climate change, the distribution of pests and soil-borne diseases, and increasing demand due to population growth, which can lead to famine. In particular, there may be cases where the soil nutrient content is insufficient and the soil structure is not suitable for cultivation. Therefore, soilless farming techniques have become popular, where the producer is entirely in control of the process. Additionally, many factors affect conventional farming techniques, including restrictions on land suitable for agriculture, climate-increased transportation costs from production areas to central regions, and environmental sanctions. Therefore, soilless farming techniques and the use of technology have rapidly gained importance. The use of technology has two crucial parameters: hardware and software. Today, no device can simultaneously control the electrical conductivity, pH, dissolved oxygen, and temperature of the solution in systems cultivated with soilless farming techniques. The present study was conducted to find a solution to the needs in this area. An automatic control system was developed and tested, employing a microcontroller, various sensors, appropriate open-source codes, and original software. Electrical conductivity (EC), power of hydrogen (pH), dissolved oxygen (DO), and temperature (T) values were determined successfully by the developed control system. The area where the experiment was conducted is a fully controlled and closed area established within Ankara University. The ambient temperature was 22 °C and the humidity was 39%. The coordinates of the experimental area are 39.962013 and 32.867491. Three different artificial lighting intensities (165.6 µmol m−2 s−1, 248.4 µmol m−2 s−1, and 331.2 µmol m−2 s−1) and a desired photoperiod duration can be applied to the site. Full article
(This article belongs to the Special Issue Sensors Integration in Agricultural Farm Mechanization and Food Processing Operations)
►▼ Show Figures

Figure 1

25 pages, 5164 KiB  
Article
Development of Smart Irrigation Equipment for Soilless Crops Based on the Current Most Representative Water-Demand Sensors
by Francisco Sánchez Millán, Francisco J. Ortiz, Teresa C. Mestre Ortuño, Antonio Frutos and Vicente Martínez
Sensors 2023, 23(6), 3177; https://doi.org/10.3390/s23063177 - 16 Mar 2023
Cited by 3 | Viewed by 3062
Abstract
Due to the edaphoclimatic conditions in southeast Spain, which are expected to worsen due to climate change, more efficient ways of using water must be found to maintain sustainable agriculture. Due to the current high price of irrigation control systems in southern Europe, [...] Read more.
Due to the edaphoclimatic conditions in southeast Spain, which are expected to worsen due to climate change, more efficient ways of using water must be found to maintain sustainable agriculture. Due to the current high price of irrigation control systems in southern Europe, 60–80% of soilless crops are still irrigated, based on the experience of the grower or advisor. The hypothesis of this work is that the development of a low-cost, high-performance control system will allow small farmers to improve the efficiency of water use by obtaining better control of soilless crops. The objective of the present study was to design and develop a cost-effective control system for the optimization of soilless crop irrigation after evaluating the three most commonly used irrigation control systems to determine the most efficient. Based on the agronomic results comparing these methods, a prototype of a commercial smart gravimetric tray was developed. The device records the irrigation and drainage volumes and drainage pH and EC. It also offers the possibility of determining the temperature, EC, and humidity of the substrate. This new design is scalable thanks to the use of an implemented data acquisition system called SDB and the development of software in the Codesys programming environment based on function blocks and variable structures. The reduced wiring achieved by the Modbus-RTU communication protocols means the system is cost-effective even with multiple control zones. It is also compatible with any type of fertigation controller through external activation. Its design and features solve the problems in similar systems available on the market at an affordable cost. The idea is to allow farmers to increase their productivity without having to make a large outlay. The impact of this work will make it possible for small-scale farmers to have access to affordable, state-of-the-art technology for soilless irrigation management leading to a considerable improvement in productivity. Full article
(This article belongs to the Special Issue Sensors Integration in Agricultural Farm Mechanization and Food Processing Operations)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop