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Agronomy
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Agricultural Automation and Innovative Agricultural Systems
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Agricultural Automation and Innovative Agricultural Systems

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

Deadline for manuscript submissions: closed (10 June 2023) | Viewed by 40046

Special Issue Editors

Prof. Dr. Egidijus Šarauskis

E-Mail Website
Guest Editor
Agriculture Academy, Faculty of Agricultural Engineering, Institute of Agricultural Engineering and Safety, Vytautas Magnus University, Studentu Str. 15A, LT-53362 Akademija, Kaunas Distr., Lithuania
Interests: agricultural engineering; environment engineering; reduced tillage technologies; sowing machinery; precision agriculture; sowing and weed control robots; technological, energetic, and environmental assessment of the impact of agricultural technological operations on soil and environmental pollution
Special Issues, Collections and Topics in MDPI journals
Dr. Vilma Naujokienė

E-Mail Website
Guest Editor
Agriculture Academy, Faculty of Agricultural Engineering, Institute of Agricultural Engineering and Safety, Vytautas Magnus University, Studentu Str. 15A, LT-53362 Akademija, Kaunas Distr., Lithuania
Interests: environmental engineering; agricultural technologies; sustainable animal husbandry; energy cost reduction and environmental sustainability in various agricultural systems; multicriteria bioimpact effectiveness for environmental improvement
Special Issues, Collections and Topics in MDPI journals
Dr. Zita Kriauciuniene

E-Mail Website
Guest Editor
Department of Agroecosystems and Soil Sciences, Faculty of Agronomy, Agriculture Academy, Vytautas Magnus University, Studentu Str. 11, LT-53361 Akademija, Lithuania
Interests: soil, crop and residues management improvement; soil health; soil organic matter; soil biological activity; soil agrochemical and agrophysical parameters; use of bioactivators; meat and bone meal fertilisers in crop growing technologies; crop and weed allelopathy; sustainable agrotechnologies; precision agriculture; ICT in agriculture
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Delivering the European Green Deal and UN Sustainable Development Goals (SDGs) has highlighted the importance of agricultural transition employing and realizing innovative agricultural systems, digitalization and automation. Present technological development is very fast, but still not implemented enough in the agricultural sector. Innovations and automation are the way to assure healthy food production, sustainable use of resources, climate change mitigation and adaptation aiming to save the planet for future generations. Researchers play a very important role in answering questions and helping to implement innovation adaptations in practice. In this Special Issue, we invite you to share the results of your high-quality research of innovative agrotechnologies, using novel preparations and equipment, automation, robotization, digitalization, ICT, sensors in agricultural systems, application precision agriculture, smart agricultural engineering in conventional, sustainable and organic crop production, horticulture, animal husbandry, and primary processing.

Prof. Dr. Egidijus Šarauskis
Dr. Vilma Naujokienė
Dr. Zita Kriauciuniene
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

  • agricultural machinery
  • automation and robotization
  • digital agriculture
  • precision agriculture
  • organic agriculture
  • innovation in animal husbandry
  • soil management
  • sowing, fertilization, spraying operations
  • plant care
  • harvesting
  • application of innovative bio-products
  • primary processing
  • energy, economic and environmental assessment

Related Special Issue

Published Papers (16 papers)

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Research

17 pages, 15370 KiB  
Article
Mobile Robot System for Selective Asparagus Harvesting
by Sebastjan Šlajpah, Marko Munih and Matjaž Mihelj
Agronomy 2023, 13(7), 1766; https://doi.org/10.3390/agronomy13071766 - 29 Jun 2023
Cited by 2 | Viewed by 1632
Abstract
Asparagus harvesting presents unique challenges, due to the variability in spear growth, which makes large-scale automated harvesting difficult. This paper describes the development of an asparagus harvesting robot system. The system consists of a delta robot mounted on a mobile track-based platform. It [...] Read more.
Asparagus harvesting presents unique challenges, due to the variability in spear growth, which makes large-scale automated harvesting difficult. This paper describes the development of an asparagus harvesting robot system. The system consists of a delta robot mounted on a mobile track-based platform. It employs a real-time asparagus detection algorithm and a sensory system to determine optimal harvesting points. Low-level control and high-level control are separated in the robot control. The performance of the system was evaluated in a laboratory field mock-up and in the open field, using asparagus spears of various shapes. The results demonstrate that the system detected and harvested 88% of the ready-to-harvest spears, with an average harvesting cycle cost of 3.44s±0.14s. In addition, outdoor testing in an open field demonstrated a 77% success rate in identifying and harvesting asparagus spears. Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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16 pages, 2394 KiB  
Article
Ammonia Emissions from Cattle Manure under Variable Moisture Exchange between the Manure and the Environment
by Rolandas Bleizgys and Vilma Naujokienė
Agronomy 2023, 13(6), 1555; https://doi.org/10.3390/agronomy13061555 - 05 Jun 2023
Viewed by 2059
Abstract
When reducing ammonia emissions from cowsheds, it is recommended to reduce the ventilation intensity, air temperature in the barn, manure moisture by using bedding and manure-contaminated surfaces, and to prevent urine from accumulating in the airways. Using the mass flow method in the [...] Read more.
When reducing ammonia emissions from cowsheds, it is recommended to reduce the ventilation intensity, air temperature in the barn, manure moisture by using bedding and manure-contaminated surfaces, and to prevent urine from accumulating in the airways. Using the mass flow method in the wind tunnel, after research on seven types of cattle manure with different moisture contents, it was found that ammonia evaporates up to 3.9 times more intensively from liquid manure than from solid manure. There is a strong correlation between ammonia and water evaporation from manure. Ammonia emission from liquid manure decrease by 2.0–2.3 times, emissions from solid manure decrease by 1.9–2.1 times. Different cowsheds have different opportunities to reduce air pollution and conditions for manure to dry and crusts to form on the surface. The best results will be achieved by applying complex measures to reduce air pollution. Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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31 pages, 10310 KiB  
Article
Toward Sustainable Farming: Implementing Artificial Intelligence to Predict Optimum Water and Energy Requirements for Sensor-Based Micro Irrigation Systems Powered by Solar PV
by Maged Mohammed, Hala Hamdoun and Alaa Sagheer
Agronomy 2023, 13(4), 1081; https://doi.org/10.3390/agronomy13041081 - 08 Apr 2023
Cited by 9 | Viewed by 6000
Abstract
Future trends in climate change, water scarcity, and energy costs will motivate agriculturists to develop innovative agricultural systems. In order to achieve sustainable farming in arid regions, there is an urgent need to use artificial intelligence (AI) to predict and estimate the optimum [...] Read more.
Future trends in climate change, water scarcity, and energy costs will motivate agriculturists to develop innovative agricultural systems. In order to achieve sustainable farming in arid regions, there is an urgent need to use artificial intelligence (AI) to predict and estimate the optimum water and energy requirements for the irrigation of date palms. Therefore, this study aimed to predict the optimum water and energy requirements for date palm irrigation depending on the optimum water use efficiency (WUE) and yield in arid conditions. To achieve this aim, four solar-powered micro irrigation systems were developed and evaluated under six irrigation levels for date palm irrigation. Soil moisture sensor-based controllers were used to automate irrigation scheduling for the micro irrigation systems. The water pumping in these systems was powered using a solar photovoltaic (PV) system. In addition, four machine-learning (ML) algorithms, including linear regression (LR), support vector regression (SVR), long short-term memory (LSTM) neural network, and extreme gradient boosting (XGBoost), were developed and validated for prediction purposes. These models were developed in Python programing language using the Keras library. The results indicated that the optimum WUS was achieved when the maximum setpoints of irrigation control were adjusted at the field capacity and by adjusting the minimum setpoints at 40, 50, 70, and 80% of the available water (AW). The optimum yield was achieved by adjusting the minimum setpoints at 60, 70, 80, and 90% of AW for subsurface irrigation, subsurface drip irrigation, drip irrigation, and bubbler irrigation, respectively. Therefore, the dataset was prepared at these levels for four years to train and test the models, and a fifth year was used to validate the performance of the best model. The evaluation of the models showed that the LSTM followed by XGBoost models were more accurate than the SVR and LR models for predicting the optimum irrigation water and energy requirements. The validation result showed that the LSTM was able to predict the water and energy requirements for all irrigation systems with R2 ranging from 0.90 to 0.92 based on limited meteorological variables and date palm age. The findings of the current study demonstrated that the developed LSTM model can be a powerful tool in irrigation water and energy management as a fast and easy-to-use approach. Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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16 pages, 4964 KiB  
Article
The Influence of Different Irrigation Scenarios on the Yield and Sustainability of Wheat Fodder under Hydroponic Conditions
by Andrius Grigas, Dainius Savickas, Dainius Steponavičius, Žygimantas Niekis and Jonas Balčiūnas
Agronomy 2023, 13(3), 860; https://doi.org/10.3390/agronomy13030860 - 15 Mar 2023
Viewed by 1813
Abstract
Agriculture uses more water than any other resource to produce animal feed and wastes much of it through inefficiency. One possible alternative to solve this problem is hydroponically grown animal fodder, which under hydroponic conditions can achieve optimal results and, most importantly, use [...] Read more.
Agriculture uses more water than any other resource to produce animal feed and wastes much of it through inefficiency. One possible alternative to solve this problem is hydroponically grown animal fodder, which under hydroponic conditions can achieve optimal results and, most importantly, use expensive resources, such as water, more efficiently. In the conducted research, different irrigation scenarios (IR1–IR6) were investigated when the water flow rate, irrigation frequency, and duration (IR1—1 l min−1, 4 times day−1, 120 s; IR2—2 l min−1, 4 times day−1, 120 s; IR3—3 l min−1, 4 times day−1, 120 s; IR4—1 l min−1, 8 times day−1, 60 s; IR5—2 l min−1, 8 times day−1, 60 s; and IR6—3 l min−1, 8 times day−1, 60 s) were changed during the hydroponic wheat fodder cultivation using a 7-day growth cycle. The results showed that the highest yield from the used seed was obtained in scenarios IR5 (5.95 ± 0.14 kg kg−1) and IR6 (5.91 ± 0.19 kg kg−1). In terms of frequency and irrigation duration, in IR1, IR2, and IR3, the average yield reached 4.7 ± 1.85 kg kg−1, and in scenarios IR4, IR5, and IR6, the average yield was 15.4% higher—5.55 ± 1.63 kg kg−1. The results obtained showed that by increasing the flow rate (from 1 l min−1 to 3 l min−1) and the frequency of irrigation (from 4 times day−1 to 8 times day−1), the yield increased by 32.5%, but the mass of the grown fodder per liter of water used simultaneously decreased by 50.6%. The life cycle assessment showed that although irrigation scenario IR4 had the most efficient use of water, the CO2 footprint per functional unit (FU) was the highest due to the lowest yield compared to the other five irrigation scenarios. The lowest environmental impacts per FU were obtained in scenarios IR5 and IR6 (100.5 ± 3.3 and 100.6 ± 2.4 kg CO2eq t−1, respectively). Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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21 pages, 17440 KiB  
Article
Tomato Disease Monitoring System Using Modular Extendable Mobile Robot for Greenhouses: Automatically Reporting Locations of Diseased Tomatoes
by Chen Ouyang, Emiko Hatsugai and Ikuko Shimizu
Agronomy 2022, 12(12), 3160; https://doi.org/10.3390/agronomy12123160 - 13 Dec 2022
Cited by 5 | Viewed by 2351
Abstract
Based on the appearance of tomatoes, it is possible to determine whether they are diseased. Detecting diseases early can help the yield losses of tomatoes through timely treatment. However, human visual inspection is expensive in terms of the time and labor required. This [...] Read more.
Based on the appearance of tomatoes, it is possible to determine whether they are diseased. Detecting diseases early can help the yield losses of tomatoes through timely treatment. However, human visual inspection is expensive in terms of the time and labor required. This paper presents an automatic tomato disease monitoring system using modular and extendable mobile robot we developed in a greenhouse. Our system automatically monitors whether tomatoes are diseased and conveys the specific locations of diseased tomatoes to users based on the location information of the image data collected by the robot, such that users can adopt timely treatment. This system consists of two main parts: a modular, extendable mobile robot that we developed and a server that runs a tomato disease detection program. Our robot is designed to be configured and extended according to the actual height of the tomato vines, thus ensuring that the monitoring range covers most tomatoes. It runs autonomously between two rows of tomato plants and collects the image data. In addition to storing the image data of tomatoes, the data server runs a program for detecting diseases. This program contains a two-level disease detection model: a detection network for detecting diseased tomatoes and a validation network for verifying the detection results. The validation network verifies the results of the detection network by classifying the outputs of the detection network, thus reducing the false positive rate of the proposed system. Experimentally, this work focuses on the blossom-end rot of tomatoes. In this paper, YOLOv5, YOLOv7, Faster R-CNN, and RetinaNet are trained and compared on datasets divided by different conditions. YOLOv5l showed the best results on the randomly divided dataset: the mAP@0.5 reached 90.4%, and the recall reached 85.2%. Through the trained YOLOv5l, a dataset was created for training the classification networks: ResNet, MobileNet, and DenseNet. MobileNetv2 achieved the best overall performance with a 96.7% accuracy and a size of 8.8 MB. The final deployment to the system included YOLOv5l and MobileNetv2. When the confidence threshold of YOLOv5l was set to 0.1, the two-level model’s false positive and false negative rates were 13.3% and 15.2%, respectively. Compared to using YOLOv5l alone, the false positive rate decreased by 5.7% and the false negative rate increased by only 2.3%. The results of the actual operation of the proposed system reveal that the system can inform the user of the locations of diseased tomatoes with a low rate of false positives and false negatives, and that it is an effective and promotable approach. Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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30 pages, 10382 KiB  
Article
Design and Validation of Automated Sensor-Based Artificial Ripening System Combined with Ultrasound Pretreatment for Date Fruits
by Maged Mohammed and Nashi K. Alqahtani
Agronomy 2022, 12(11), 2805; https://doi.org/10.3390/agronomy12112805 - 10 Nov 2022
Cited by 5 | Viewed by 1830
Abstract
Climate change affects fruit crops’ growth and development by delaying fruit ripening, reducing color development, and lowering fruit quality and yield. The irregular date palm fruit ripening in the past few years is assumed to be related to climatic change. The current study [...] Read more.
Climate change affects fruit crops’ growth and development by delaying fruit ripening, reducing color development, and lowering fruit quality and yield. The irregular date palm fruit ripening in the past few years is assumed to be related to climatic change. The current study aimed to design and validate an automated sensor-based artificial ripening system (S-BARS) combined with ultrasound pretreatment for artificial ripening date fruits cv. Khalas. A sensor-based control system was constructed to allow continuous real-time recording and control over the process variables. The impact of processing variables, i.e., the artificial ripening temperature (ART-temp) and relative humidity (ART-RH) using the designed S-BARS combined with ultrasound pretreatment variables, i.e., time (USP-Time) and temperature (USP-Temp) on the required time for fruit ripening (RT), the percentage of ripened fruits (PORF), the percentage of damaged fruits (PODF), and the electrical energy consumption (EEC) were investigated. The quadratic predictive models were developed using the Box–Behnken Design (B-BD) to predict the RT, PORF, PODF, and EEC experimentally via Response Surface Methodology(RSM). Design Expert software (Version 13) was used for modeling and graphically analyzing the acquired data. The artificial ripening parameter values were determined by solving the regression equations and analyzing the 3D response surface plots. All parameters were simultaneously optimized by RSM using the desirability function. The Mean Absolute Percentage Error (MAPE) and the Root Mean Square Error (RMSE) between the predicted and actual experimental values were used to evaluate the developed models. The physicochemical properties of the ripened fruit were assessed under the optimization criteria. The results indicated that the pretreated unripe date fruits with 40 kHz ultrasound frequency, 110 W power, and USP-Temp of 32.49 °C for 32.03 min USP-Time under 60 °C ART-Temp and 59.98% ART-RH achieved the best results. The designed S-BARS precisely controlled the temperature and relative humidity at the target setpoints. The ultrasound pretreatment improved the color and density of the artificially ripened date fruits, decreased the RT and EEC, and increased the PORF without negatively affecting the studied fruit quality attributes. The developed models could effectively predict the RT, PORF, PODF, and EEC. The designed S-BARS combined with ultrasound pretreatment is an efficient approach for high-quality ripening date fruits. Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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16 pages, 2700 KiB  
Article
Effect of Tillage and Sowing Technologies Nexus on Winter Wheat Production in Terms of Yield, Energy, and Environment Impact
by Lina Saldukaitė-Sribikė, Egidijus Šarauskis, Sidona Buragienė, Aida Adamavičienė, Rimantas Velička, Zita Kriaučiūnienė and Dainius Savickas
Agronomy 2022, 12(11), 2713; https://doi.org/10.3390/agronomy12112713 - 01 Nov 2022
Cited by 3 | Viewed by 1394
Abstract
Crop production is considered one of the most important agricultural areas in the world, supplying humanity with raw food materials. However, intensive farming very often has a detrimental effect on the environment. The aim of this study was to investigate and assess the [...] Read more.
Crop production is considered one of the most important agricultural areas in the world, supplying humanity with raw food materials. However, intensive farming very often has a detrimental effect on the environment. The aim of this study was to investigate and assess the efficiency of strip tillage and a sowing machine as well as a direct sowing machine in differently prepared soils in terms of yield, energy, and environmental impact. The experiments were performed with winter wheat (Triticum aestivum L.) grown using three different tillage techniques and two sowing machines. The results show that the inputs of diesel fuel, energy, and time are directly affected by the number and complexity of technological operations throughout the production chain. The highest inputs of diesel fuel, working time, and energy consumption were needed using conventional tillage technology with strip tillage and a sowing machine (CT–STS), amounting to 130.2 l ha−1, 6.65 h ha−1, and 18,349 MJ ha−1, respectively. The best yields were obtained using no tillage–direct sowing technology (NT–DS), where were reached 7.54 t ha−1. The lowest environmental impact was achieved in the winter wheat production system using NT–DS, where the CO2 emissions were as high as 15%, lower than those under conventional tillage–direct sowing (CT–DS) and CT–STS. The costs of winter wheat production can be reduced by up to 23.6%. The main conclusion regarding the use of strip tillage and sowing and direct sowing machines in traditional tillage technology is that energy and environmental indicators have deteriorated compared to no tillage, but no significant difference in winter wheat yields has been identified. Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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19 pages, 326 KiB  
Article
The Effect of Combining N-Fertilization with Urease Inhibitors and Biological Preparations on Maize Biological Productivity
by Povilas Drulis, Zita Kriaučiūnienė and Vytautas Liakas
Agronomy 2022, 12(10), 2264; https://doi.org/10.3390/agronomy12102264 - 21 Sep 2022
Cited by 2 | Viewed by 1405
Abstract
After evaluating the ecological and economic aspects, it is predicted that the use of urease inhibitors and biological preparations should reduce the risk of nutrient leaching by using fertilizers containing amide, ammonium, and nitrate forms of nitrogen and would increase nitrogen use efficiency. [...] Read more.
After evaluating the ecological and economic aspects, it is predicted that the use of urease inhibitors and biological preparations should reduce the risk of nutrient leaching by using fertilizers containing amide, ammonium, and nitrate forms of nitrogen and would increase nitrogen use efficiency. Moreover, with lower nitrogen fertilizer rates, it would be possible to achieve or even increase planned maize biomass yield. The field experiment was performed in 2019–2021 at the Experimental Station of Vytautas Magnus University Agriculture Academy. The soil of the experimental field was Endohipogleyic-Eutric Planasol. The aim of this study was to investigate the effect of urease inhibitors and biological preparations in combination with nitrogen fertilizers on the productivity of aboveground maize (Zea mays L.) biomass. A two-factor experiment was carried out: factor A included nitrogen fertilizer rates of (1) 100 kg N ha−1, (2) 140 kg N ha−1, and (3) 180 kg N ha−1; and factor B included the use of preparations of (1) no use of urease inhibitors (UIs) and biological preparations (BPs) (control), (2) the urease inhibitor ammonium thiosulphate (UI ATS), (3) the urease inhibitor (UI URN)—N-Butyl-thiophosphorus triamide (NBPT), (4) the biological preparation of suspension of humic and fulvic acids (BP HUM); and (5) the biological preparation (BP FIT) of suspension of Ascophyllum nodosum The studies showed that the dry matter yield of maize was significantly increased not only by increasing nitrogen fertilizer rates but also by the use of UIs and BPs. The highest dry matter yield of maize (24.1 t ha−1) was obtained with N180 fertilizer and UI ATS. UI ATS significantly increased the dry matter yield of the aboveground maize in all nitrogen fertilization backgrounds. The UIs and BPs tested had a greater and significant (p < 0.05) effect on the dry matter yield of maize at lower rates of N100 and N140 nitrogen fertilizer. Increasing nitrogen fertilizer rates up to N180 had a positive significant effect on dry matter yields of the aboveground part of maize, its cobs, leaves, and stems. Positive, moderate, strong, and very strong correlations were found in most cases between the latter variables. These correlations were statistically significant (r2 = 0.62–0.98). The UIs and BPs increased the efficiency of nitrogen fertilizer; therefore, the lower rates of nitrogen fertilizer (N100 and N140) could be used to produce maize productivity the same as that obtained with a high rate of nitrogen fertilizer (N180). Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
19 pages, 4280 KiB  
Article
Influencing Factors of the Distribution Accuracy and the Optimal Parameters of a Pneumatic Fertilization Distributor in a Fertilizer Applicator
by Wensheng Yuan, Changying Ji, Zhiyuan Liu, Chengqian Jin and Yugang Feng
Agronomy 2022, 12(9), 2222; https://doi.org/10.3390/agronomy12092222 - 18 Sep 2022
Cited by 2 | Viewed by 1576
Abstract
A pneumatic fertilization distributor used for fertilizing in a fertilizer applicator is a key component of the applicator. The parameters of a pneumatic fertilization distributor affect the uniformity and accuracy of the fertilization of a fertilizer applicator. To obtain the optimal design parameters [...] Read more.
A pneumatic fertilization distributor used for fertilizing in a fertilizer applicator is a key component of the applicator. The parameters of a pneumatic fertilization distributor affect the uniformity and accuracy of the fertilization of a fertilizer applicator. To obtain the optimal design parameters of a pneumatic fertilization distributor, a fluidstructure coupling simulation test and a bench test were carried out in the Intelligent Agricultural Machinery Laboratory of the Nanjing Institute of Agricultural Mechanization from March 2021 to July 2022. The curvature–diameter ratios of the elbow, bellow length, and air velocity were selected as the experimental factors, and the variation coefficient of the fertilizer discharge at each discharge outlet within 0.5–3 s was selected as the experimental index. A five-level quadratic regression orthogonal rotation combined test was carried out. The results showed that: (1) all three factors had a significant impact on the uniformity of the fertilizer discharge. The reasonable ranges of the curvature–diameter ratio, bellow length, and air velocity were 0.5–1.5, 350–550 mm, and 25–35 m/s, respectively. (2) The order of the influence of the three factors on the uniformity of the fertilizer discharge in descending order was as follows: the curvature–diameter ratio of the elbow, the bellow length, and the air velocity. When the bellow length was 460 mm, the curvature–diameter ratio was 0.6, and the inlet air velocity was 28 m/s. The uniformity of the fertilizer discharge was optimal. A pneumatic conveying system was redesigned according to the optimal parameters, and a bench test was carried out. The results showed that at different speeds, the coefficient of variation of each row’s displacement was not greater than 5%, and the simulation test results were consistent with the bench test results. Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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18 pages, 3683 KiB  
Article
Conversion of Thermal Energy to Gas Flow Kinetic Energy in the Bionic Leaf Stomata
by Tomas Ūksas, Povilas Algimantas Sirvydas, Simona Paulikienė and Rasa Čingienė
Agronomy 2022, 12(8), 1742; https://doi.org/10.3390/agronomy12081742 - 23 Jul 2022
Viewed by 1370
Abstract
In the technical field, the potential energy of gas under pressure is converted into mechanical kinetic energy by means of special complex channels. Leaf stomata perform a similar function in plant leaves. The shape of leaf stomata channels is much more sophisticated compared [...] Read more.
In the technical field, the potential energy of gas under pressure is converted into mechanical kinetic energy by means of special complex channels. Leaf stomata perform a similar function in plant leaves. The shape of leaf stomata channels is much more sophisticated compared to gas flow transformation channels in energy production facilities. There is a biological prototype of a heat engine in the leaf, where leaf stomata convert thermal energy into mechanical kinetic energy of the flow with a change in leaf temperature. The paper presents experimental research on thermal energy conversion into mechanical kinetic energy of the flow in plant leaf stomata. The values of biological heat engine in a plant leaf and the associated processes are minute. The operation of the biological heat engine in a plant leaf was proven by indirect experimental measurements. After applying a light source flux to a plant leaf and inducing a temperature change in the tissues of the plant leaf, the rotational movements of a freely hanging plant leaf about the suspension axis were studied. When studying the dependence of plant leaf rotation movements on the area of the plant leaf, it was found that at a 150 W light source, the angle of rotation increased as the area of the plant leaf increased. For a plant leaf with an area of 52.5 ± 1.9 cm2, the angle of rotation reached 165°; 29.1 ± 1.1 cm2—143°; 16.0 ± 0.8 cm2—92°; and 9.2 ± 0.6 cm2—44°. The angular speed of plant leaf rotation was from 0.070–0.262 rad/s. The influence of light sources on the rotation angle of the plant leaf was studied; when illuminating the active leaf area of 25.0 ± 1.0 cm2 of the plant with a 40 W power light source, after 11 s, the rotation angle reached 31°, 60 W—97°, 100 W—131° and 150 W—134°. The effect of light sources (from 40 to 150 W) on the angular rotation speed of the plant leaf varies at 0.049–0.213 rad/s, respectively. Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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11 pages, 794 KiB  
Article
Estimation of Optimum Vacuum Pressure of Air-Suction Seed-Metering Device of Precision Seeders Using Artificial Neural Network Models
by Davut Karayel, Orhan Güngör and Egidijus Šarauskis
Agronomy 2022, 12(7), 1600; https://doi.org/10.3390/agronomy12071600 - 01 Jul 2022
Cited by 5 | Viewed by 1950
Abstract
The success of the seed-metering device of a seeder determines the quality seeding and final plant stand. The adjustment of the optimal vacuum pressure of air-suction-type seed-metering devices is a key factor affecting the success of seed-metering devices. The optimal value of vacuum [...] Read more.
The success of the seed-metering device of a seeder determines the quality seeding and final plant stand. The adjustment of the optimal vacuum pressure of air-suction-type seed-metering devices is a key factor affecting the success of seed-metering devices. The optimal value of vacuum of the seed-metering device should be adjusted in relation to the physical properties of the seed before seeding in the field. This research was carried out to estimate the optimal value of vacuum pressure of an air-suction seed-metering device of a precision seeder by using an artificial neural network method. Training of the network was performed by using a Levenberg–Marquardt (LM) learning algorithm. Training and testing were carried out using Matlab software. The inputs were physical properties of seeds such as surface area, thousand kernel weight, kernel density and sphericity. Optimum vacuum pressures were determined for soybean, maize, cucumber, melon, watermelon, sugarbeet and onion seeds in laboratory. Surface area, thousand kernel weight, kernel density and sphericity of seeds varied from 0.05 to 0.638 cm2, 4.4 to 322.4 g, 0.43 to 1.29 g cm−3 and 42.8 to 85.75%, respectively. The optimal vacuum pressure was determined as 1.5 kPa for onion; 2.0 kPa for sugarbeet; 2.5 kPa for melon and watermelon; 3.0 kPa for soybean; and 4.0 kPa for maize seeds. A trained program using an artificial neural network could satisfactorily estimate the optimum value of vacuum pressure of the air-suction type seed-metering device of precision seeders with a prediction success (R2) of 0.9949 for both linear and polynomial regressions. Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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15 pages, 3397 KiB  
Article
Weeding Effectiveness and Changes in Soil Physical Properties Using Inter-Row Hoeing and a Robot
by Indrė Bručienė, Sidona Buragienė and Egidijus Šarauskis
Agronomy 2022, 12(7), 1514; https://doi.org/10.3390/agronomy12071514 - 24 Jun 2022
Cited by 6 | Viewed by 2683
Abstract
Weed control is one of the most important technological operations to ensure crop yield and quality in ecological sugar beet production. However, conventional mechanical weed control is labor- and time-intensive and has adverse effects on the soil and the environment. The aim of [...] Read more.
Weed control is one of the most important technological operations to ensure crop yield and quality in ecological sugar beet production. However, conventional mechanical weed control is labor- and time-intensive and has adverse effects on the soil and the environment. The aim of this study was to experimentally investigate the influence of conventional mechanical and robotic weed control systems on soil properties and to assess the effectiveness of these different weed control methods in ecological sugar beet production. This study examines two different weed control systems: robotic weed control (RWC) and conventional weed control (CWC). Field experimental studies were carried out with a solar-powered field robot and conventional inter-row cultivation (CWC1—first cultivation, CWC2—second cultivation) to determine the effectiveness of mechanical weed control in ecological sugar beet crops. The influence of different weed control systems on the physical properties of the soil in the contact zone between the soil and the tires of weed control machines was investigated. The results showed that the average weed control effectiveness inter-row was higher in the RWC (81%) compared to that in the CWC2 (46%). The overall weed control effectiveness of the robotic weed control in the sugar beet inter-row and intra-row was around 49%. The measurements showed that the weed control process reduced the soil moisture and temperature in all treatments tested. Experimental studies have confirmed that the weed control operation, although carried out with relatively lightweight robots, also has an impact on soil bulk density. RWC weed control resulted in an average increase of 0.16 g cm–3 in soil bulk density in the topsoil layer (0–10 cm) after weeding. Both CWC1 and RWC increased soil penetration resistance (PR). For CWC1, the average increase in topsoil PR after weed control was 20%, while for RWC, the increase was marginal, only around 1%. Automated precision weed control by self-propelled solar-powered field robots is an important solution to reduce the need for tedious and time-consuming manual weeding. Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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16 pages, 5302 KiB  
Article
Humidification–Cooling System in Semi-Insulated Box-Type Cowsheds Prevent the Loss of Milk Productivity Due to Thermal Stress
by Rolandas Bleizgys, Vilma Naujokienė and Jonas Čėsna
Agronomy 2022, 12(5), 1131; https://doi.org/10.3390/agronomy12051131 - 07 May 2022
Cited by 2 | Viewed by 1548
Abstract
Heat stress is becoming an increasingly important problem in Lithuanian cowsheds. Microclimate formation systems were evaluated in the seven most popular cowsheds in Lithuania, with different wall and roof constructions, insulation, ventilation intensity controls, and one cowshed was additionally equipped with an air-cooling [...] Read more.
Heat stress is becoming an increasingly important problem in Lithuanian cowsheds. Microclimate formation systems were evaluated in the seven most popular cowsheds in Lithuania, with different wall and roof constructions, insulation, ventilation intensity controls, and one cowshed was additionally equipped with an air-cooling system—the air is cooled by spraying water droplets with a high pressure. In cowsheds equipped with fans to intensify the movement of air, the temperature does not fall below the outdoor temperature and the temperature humidity index (THI) is higher than outdoors. During the heat period, the THI rises to 82 and the cows get moderate thermal stress, which adversely affects feed intake and milk yield of dairy cows. In the cowshed, where the air humidification–cooling system is installed, the air temperature during heat is lower than the average in the field of 2.61 ± 0.74 °C. Although the relative humidity in the cowshed is on average 16.29 ± 4.12% wetter during heat than outside, the THI in the barn is lower than outside. The air temperature in this cowshed decreases by 3.17 ± 0.86 °C compared to cowsheds without an air humidification–cooling system. The air humidification–cooling system creates good conditions to reduce the conditions for cows to experience thermal stress. Further research is needed to optimize the amount of water spray and droplet size and increase the efficiency of the cooling system. Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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13 pages, 2781 KiB  
Article
Effects of New Compounds into Substrates on Seedling Qualities for Efficient Transplanting
by Luhua Han, Menghan Mo, Yansu Gao, Haorui Ma, Daqian Xiang, Guoxin Ma and Hanping Mao
Agronomy 2022, 12(5), 983; https://doi.org/10.3390/agronomy12050983 - 19 Apr 2022
Cited by 7 | Viewed by 1950
Abstract
Automating vegetable seedling transplanting has led to labor-saving opportunities and improved productivity. Some changes in seedling agronomy are necessary for efficient transplanting. In this study, the local nursery substrates were added with the herbaceous peat, the sphagnum peat, and the coir peat, respectively. [...] Read more.
Automating vegetable seedling transplanting has led to labor-saving opportunities and improved productivity. Some changes in seedling agronomy are necessary for efficient transplanting. In this study, the local nursery substrates were added with the herbaceous peat, the sphagnum peat, and the coir peat, respectively. Effects of the new compound substrates were investigated on the seedling growth qualities and the root substrate strength. In the results, we found that the addition of three compound mediums significantly affected the physiochemical properties of the original substrates. Under the same conditions of cultivating seedlings, appropriate additions of new compounds promoted the seedling growth. Moreover, deficient or excessive additions inhibited the growing development of seedlings and their roots. The corresponding additions also improved the structural characteristics of the root lumps. Compared with the two other compounds, the nursery substrates added with the sphagnum peat were optimized in contribution to the seedling qualities and the root substrate strengths. As the local substrate and the sphagnum peat were mixed at a volume ratio of 2:1, the dry matter accumulation of seedlings was 2.18 times more than the original. Their root lumps had the best consolidation strength. This new compound of substrates may be an effective application for the necessary qualities of seedlings for automatic transplanting. Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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17 pages, 3238 KiB  
Article
Environmental Impact Assessment of Sustainable Pig Farm via Management of Nutrient and Co-Product Flows in the Farm
by Kęstutis Venslauskas, Kęstutis Navickas, Mantas Rubežius, Vita Tilvikienė, Skaidrė Supronienė, Modupe Olufemi Doyeni, Karolina Barčauskaitė, Aušra Bakšinskaitė and Kristina Bunevičienė
Agronomy 2022, 12(4), 760; https://doi.org/10.3390/agronomy12040760 - 22 Mar 2022
Cited by 6 | Viewed by 4518
Abstract
This study evaluates the environmental impact assessment of sustainable pig farm via management of nutrient and co-product flows in the farm. Manure management and biogas production are among the most promising pathways towards fully utilizing organic waste within a circular bioeconomy as the [...] Read more.
This study evaluates the environmental impact assessment of sustainable pig farm via management of nutrient and co-product flows in the farm. Manure management and biogas production are among the most promising pathways towards fully utilizing organic waste within a circular bioeconomy as the most environmentally friendly solution mitigating gaseous emissions and producing bioenergy and high-quality bio-fertilizers. The concept of farm management includes rearing pig, growing all the feeds needed, and managing the nutrients and co-product flows in the farm. A consequential life cycle assessment (LCA) was performed to examine three scenarios in which all the generated manure is used as fertilizer for barley cultivation and mineral fertilizer is used where necessary (SC1); produced surplus straw is used for thermal energy generation and maize is used for sale, substituting maize biomass in the market (SC2); and all co-products are circulated in a closed system (SC3). The functional unit (FU) was defined as a “farm with 1000 fattening pigs at farm gate”. The analysis showed that heat generation from wheat, barley and legumes straw has a significantly higher positive environmental impact than the use of these cereal straw for biogas production. The partial replacement of mineral fertilizers with digestate has positive environmental effects in terms of abiotic depletion, photochemical oxidation, terrestrial ecotoxicity, freshwater aquatic ecotoxicity, human toxicity, and marine aquatic ecotoxic aspects. The amount of digestate generated on a farm is not sufficient to completely eliminate the use of mineral fertilizers for plant fertilization. The generated pig manure (SC1) and digestate (SC2) is only enough for the fertilization of 8.3% of the total cultivated land of farm applying 22.9 t/ha rate. Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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15 pages, 5591 KiB  
Article
The Influence of Different Nitrogen Fertilizer Rates, Urease Inhibitors and Biological Preparations on Maize Grain Yield and Yield Structure Elements
by Povilas Drulis, Zita Kriaučiūnienė and Vytautas Liakas
Agronomy 2022, 12(3), 741; https://doi.org/10.3390/agronomy12030741 - 19 Mar 2022
Cited by 11 | Viewed by 4150
Abstract
The field experiment was performed in 2019–2021 at the Experimental Station of Vytautas Magnus University Agriculture Academy (54°52′ N, 23°49′ E). The soil of the experimental field was Endohipogleyic-Eutric Planasol. The studied factors were: Factor A—different nitrogen fertilizer rates: (1) 100 kg N [...] Read more.
The field experiment was performed in 2019–2021 at the Experimental Station of Vytautas Magnus University Agriculture Academy (54°52′ N, 23°49′ E). The soil of the experimental field was Endohipogleyic-Eutric Planasol. The studied factors were: Factor A—different nitrogen fertilizer rates: (1) 100 kg N ha−1; (2) 140 kg N ha−1; (3) 180 kg N ha−1; Factor B—the use of urease inhibitors (UI) and biological preparations (BP): (1) urease inhibitors (UI) and biological preparations (BP) were not used; (2) Urease inhibitor (UI ATS)—ammonium thiosulfate—[(NH4)2S2O3 12-0-0-26S]; (3) Urease inhibitor (UI URN)—N-butyl-thiophosphorus triamide (NBPT) and N-propyl-thiophosphorus triamide (NPPT); (4) Biological preparation (BP HUM)—suspension of humic and fulvic acids; (5) Biological preparation (BP FIT)—Ascophyllum nodosum suspension. Our studies showed that the highest yield of maize grain (8.9–12.0 t ha−1) was obtained by fertilizing with N180 and using the urease inhibitor ammonium thiosulfate (ATS). ATS significantly increased corn grain yield in all backgrounds of nitrogen fertilization. The investigated urease inhibitors and biologics had a higher and more significant (p < 0.05) effect on maize grain yield when fertilized with N100 nitrogen. The increase in nitrogen fertilizer rates had an effect on maize grain yield, with the largest increase in yield being found in the increase in nitrogen rate from N100 to N140, and the increase in rate to N180 was less effective. The maximum mass of 1000 grains (323.5 g) was determined in 2019 by fertilization with N180 and use of the urease inhibitor UI URN. The urease inhibitor UI ATS was more effective when fertilized with lower rates of N100 and N140. Positive, moderate, strong and very strong, statistically significant correlations (r2 = 0.48–0.91) were most often found between the latter indicators and nitrogen fertilizer rates throughout the study year. The largest amount of grain (497 units) in the cob was determined in 2019, using fertilization with N140 and UI ATS, but no significant differences were found between the different fertilizer rates and the tested preparations. These results suggest that urease inhibitors and biologics can reduce dependence on nitrogen fertilizers and increase maize yield, a technology that should be practiced by maize growers. Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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