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4 pages, 201 KiB

Open AccessEditorial

Special Issue on the Engineering of Smart Agriculture

by Paweł Kiełbasa, Tadeusz Juliszewski and Sławomir Kurpaska

Appl. Sci. 2023, 13(14), 8523; https://doi.org/10.3390/app13148523 - 24 Jul 2023

Cited by 1 | Viewed by 1261

Abstract

The monograph presents an extract from the reality of smart agriculture, where the combination of modern technologies, innovative solutions, and sustainable approaches to food production classifies this part of science as highly interdisciplinary, multifaceted, and technologically advanced [...] Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

Research

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19 pages, 39161 KiB

Open AccessArticle

An Image Processing Method for Measuring the Surface Area of Rapeseed Pods

by Fangyi Li, Xumeng Li, Huang Huang, Hao Xiang, Chunyun Guan and Mei Guan

Appl. Sci. 2023, 13(8), 5129; https://doi.org/10.3390/app13085129 - 20 Apr 2023

Cited by 2 | Viewed by 2007

Abstract

An image processing method that considers pods to be irregular cylinders composed of several oblique cylinder slices with different diameters was proposed to achieve the “highly accurate, highly efficient and large-scale” target of measuring the surface area of rapeseed pods. The total side [...] Read more.

An image processing method that considers pods to be irregular cylinders composed of several oblique cylinder slices with different diameters was proposed to achieve the “highly accurate, highly efficient and large-scale” target of measuring the surface area of rapeseed pods. The total side area of all the oblique cylinder slices, specifically the pod surface area, was calculated. A high-precision 3-dimensional method was used to measure and correct the actual area of the silique for the first time. The results of the measurement accuracy analysis showed that the image processing method could accurately measure the surface area of rapeseed pods. The average measurement error was 2.46%, and the root-mean-square error (RMSE) was 0.92 cm². To prove the superiority of this method, we measured the same test samples using four other methods: the Clark formula, the Leng formula, flattening scanning, and quasi-cylinder side area methods. The accuracy and efficiency of the image processing method were much higher than the other four measurement methods. The surface area of multiple pods from 83 rape plants was measured using the image processing method; the results were consistent with the expectations of the experimental design. The 3D measurement and image processing technology were compared and analyzed, and the latter was preliminarily designed for future rape pod seed testing. Thus, this method can provide technical support to measure the surface area of numerous rapeseed pods. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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19 pages, 6751 KiB

Open AccessArticle

Design of an Adaptive Algorithm for Feeding Volume–Traveling Speed Coupling Systems of Rice Harvesters in Southern China

by Lexing Deng, Tianyu Liu, Ping Jiang, Fangping Xie, Junchi Zhou, Wenhan Yang and Aolin Qi

Appl. Sci. 2023, 13(8), 4876; https://doi.org/10.3390/app13084876 - 13 Apr 2023

Cited by 6 | Viewed by 1983

Abstract

We developed an adaptive algorithm to reduce rice loss in harvesting, promote threshing and improve the quality and efficiency of small- and medium-sized rice harvesters operating in southern China’s hilly and mountainous areas. Using a fuzzy PID control algorithm, the harvester adapts to [...] Read more.

We developed an adaptive algorithm to reduce rice loss in harvesting, promote threshing and improve the quality and efficiency of small- and medium-sized rice harvesters operating in southern China’s hilly and mountainous areas. Using a fuzzy PID control algorithm, the harvester adapts to the rice harvesting conditions in southern China, and monitors rice feed volume changes and instantly adjust the traveling speed to optimize feed volume levels and threshing quality. We compared and analyzed the algorithm and the traditional PID control regulation effect in the simulation experiment. The algorithm had a quicker response speed and stable accuracy. In the field trial, the average error rate was 3.4%, and the maximum error rate was 5.1%, with most data points centered around the ideal feeding rate of 3.2 kg/s. Our results showed that the algorithm’s stability, accuracy, and real-time performance met the threshing loss reduction requirements of southern China’s rice harvesting operations. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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16 pages, 2993 KiB

Open AccessFeature PaperArticle

Generation of Typical Meteorological Sequences to Simulate Growth and Production of Biological Systems

by Ousmane Wane, Luis F. Zarzalejo, Francisco Ferrera-Cobos, Ana A. Navarro, Alberto Rodríguez-López and Rita X. Valenzuela

Appl. Sci. 2023, 13(8), 4826; https://doi.org/10.3390/app13084826 - 12 Apr 2023

Cited by 2 | Viewed by 1743

Abstract

Numerical simulation applied to agriculture or wastewater treatment (WWT) is a complementary tool to understand, a priori, the impact of meteorological parameters on productivity under limiting environmental conditions or even to guide investments towards other more relevant circular economic objectives. This work proposes [...] Read more.

Numerical simulation applied to agriculture or wastewater treatment (WWT) is a complementary tool to understand, a priori, the impact of meteorological parameters on productivity under limiting environmental conditions or even to guide investments towards other more relevant circular economic objectives. This work proposes a new methodology to calculate Typical Meteorological Sequences (TMS) that could be used as input data to simulate the growth and productivity of photosynthetic organisms in different biological systems, such as a High-Rate Algae Pond (HRAP) for WWT or in agriculture for crops. The TMS was established by applying Finkelstein-Schafer statistics and represents the most likely meteorological sequence in the long term for each meteorological season. In our case study, 18 locations in the Madrid (Spain) region are estimated depending on climate conditions represented by solar irradiance and temperature. The parameters selected for generating TMS were photosynthetically active radiation, solar day length, maximum, minimum, mean, and temperature range. The selection of potential sequences according to the growth period of the organism is performed by resampling the available meteorological data, which, in this case study, increases the number of candidate sequences by 700%. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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11 pages, 3341 KiB

Open AccessArticle

Analytical Method for Assessing Stability of a Counterbalanced Forklift Truck Assembled with Interchangeable Equipment

by Leonardo Vita and Davide Gattamelata

Appl. Sci. 2023, 13(2), 1206; https://doi.org/10.3390/app13021206 - 16 Jan 2023

Cited by 2 | Viewed by 2119

Abstract

Counterbalanced forklift trucks (FLT) are frequently used in combination with interchangeable equipment in order to handle loads in different manners. The main risks which may arise after assembling interchangeable equipment to a FLT are related to the loss of stability of the assembly. [...] Read more.

Counterbalanced forklift trucks (FLT) are frequently used in combination with interchangeable equipment in order to handle loads in different manners. The main risks which may arise after assembling interchangeable equipment to a FLT are related to the loss of stability of the assembly. Actually, the presence of interchangeable equipment and the associated payload may change in a significant way the overall centre of gravity with respect to the FLT in its basic configuration with forks. Therefore, the stability limits of the assembly, based on the same footprints on the ground of the FLT alone, are affected by the position of the overall centre of gravity. Thus, the presence of interchangeable equipment could reduce the functionality (e.g., lifting capability, lifting height, etc.) of the FLT in order to continue its stability during use. Often, interchangeable equipment is placed on the market by manufacturers other than the FLT manufacturer. In these cases, the correct and safe coupling of the interchangeable equipment with the FLT is the responsibility of the manufacturers of interchangeable equipment, including the stability risk assessment. Thus, the interchangeable equipment manufacturer should have access to the relevant information of the FLT concerning operative and structural features and its configuration as a procedure for assessing the correct and safe coupling. Otherwise, he should perform experimental stability tests for each model of FLT so that its interchangeable equipment can be fitted. Specific research activity is developed in order to define an analytical procedure to assess the stability of FLT when assembled with interchangeable equipment. Specific typologies of FLTs and interchangeable equipment have been selected in order to better characterise the case study. The analytical equations mimic the static stability tests. The results achieved have been compared to experimental data in order to optimise the procedure. The results attained by the application of the analytical procedure to all the combinations of main typologies of FLTs and the interchangeable equipment selected showed good agreement with experimental tests. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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16 pages, 5948 KiB

Open AccessArticle

Modified Barnacles Mating Optimization with Deep Learning Based Weed Detection Model for Smart Agriculture

by Amani Abdulrahman Albraikan, Mohammed Aljebreen, Jaber S. Alzahrani, Mahmoud Othman, Gouse Pasha Mohammed and Mohamed Ibrahim Alsaid

Appl. Sci. 2022, 12(24), 12828; https://doi.org/10.3390/app122412828 - 14 Dec 2022

Cited by 9 | Viewed by 2328

Abstract

Weed control is a significant means to enhance crop production. Weeds are accountable for 45% of the agriculture sector’s crop losses, which primarily occur because of competition with crops. Accurate and rapid weed detection in agricultural fields was a difficult task because of [...] Read more.

Weed control is a significant means to enhance crop production. Weeds are accountable for 45% of the agriculture sector’s crop losses, which primarily occur because of competition with crops. Accurate and rapid weed detection in agricultural fields was a difficult task because of the presence of a wide range of weed species at various densities and growth phases. Presently, several smart agriculture tasks, such as weed detection, plant disease detection, species identification, water and soil conservation, and crop yield prediction, can be realized by using technology. In this article, we propose a Modified Barnacles Mating Optimization with Deep Learning based weed detection (MBMODL-WD) technique. The MBMODL-WD technique aims to automatically identify the weeds in the agricultural field. Primarily, the presented MBMODL-WD technique uses the Gabor filtering (GF) technique for the noise removal process. For automated weed detection, the presented MBMODL-WD technique uses the DenseNet-121 model as feature extraction with the MBMO algorithm as hyperparameter optimization. The design of the MBMO algorithm involves the integration of self-population-based initialization with the standard BMO algorithm. At last, the Elman Neural Network (ENN) method was applied for the weed classification process. To demonstrate the enhanced performance of the MBMODL-WD approach, a series of simulation analyses were performed. A comprehensive set of simulations highlighted the enhanced performance of the presented MBMODL-WD methodology over other DL models with a maximum accuracy of 98.99%. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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18 pages, 3846 KiB

Open AccessArticle

Effect of Commercial Microbial Preparations Containing Paenibacillus azotofixans, Bacillus megaterium and Bacillus subtilis on the Yield and Photosynthesis of Winter Wheat and the Nitrogen and Phosphorus Content in the Soil

by Arkadiusz Stępień, Katarzyna Wojtkowiak and Ewelina Kolankowska

Appl. Sci. 2022, 12(24), 12541; https://doi.org/10.3390/app122412541 - 7 Dec 2022

Cited by 7 | Viewed by 2471

Abstract

The present state of knowledge and biotechnological advances have allowed the potential of microorganisms to be used effectively in crop cultivation. A field study on the use of commercial bacterial preparations in the cultivation of winter wheat (Triticum aestivum L.) was carried [...] Read more.

The present state of knowledge and biotechnological advances have allowed the potential of microorganisms to be used effectively in crop cultivation. A field study on the use of commercial bacterial preparations in the cultivation of winter wheat (Triticum aestivum L.) was carried out in the years 2017–2019 at the Educational and Experimental Station in Tomaszkowo (53°71′ N, 20°43′ E), Poland. This study analysed the effect of commercial microbial preparations containing Paenibacillus azotofixans, Bacillus megaterium and Bacillus subtilis, applied during the winter wheat growing season, on the grain yield, protein content, leaf greenness index (SPAD), the course of photosynthesis and the N-NO₃, N-NH₄ and P contents in the soil. The highest grain yield was noted following the application of mineral fertilisation and the three microbial preparations in combination (Paenibacillus azotofixans, Bacillus megaterium and Bacillus subtilis), as well as NPK with Paenibacillus azotofixans, in relation to mineral fertilisation alone (by 19.6% and 18.4%, respectively). The microbial preparations had a significant effect on the leaf greenness index (SPAD) at both test dates. No interaction was recorded between the years of study and the preparations applied on the SPAD values. The highest leaf photosynthetic index at both observation dates was noted for the application of NPK + P. azotofixans, as well as for NPK and all the preparations combined (P. azotofixans, B. megaterium, B. subtilis). The highest N-NO₃, N-NH₄ and P contents in the soil were obtained using NPK and all microbial preparations combined. Strong correlations were found between the SPAD index and the photosynthetic index value and the protein content in wheat grains and between the N-NO₃, N-NH₄ and P contents in the soil and the wheat grain yield. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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11 pages, 1633 KiB

Open AccessArticle

Life Cycle Assessment for Environmental Impact Reduction and Evaluation of the Energy Indices in Lettuce Production

by Ali Mousavi, Ebrahim Asadi Aghbolaghi, Ali Khorramifar, Marek Gancarz, Yousef Darvishi, Mateusz Stasiak, Anna Miernik and Hamed Karami

Appl. Sci. 2022, 12(20), 10348; https://doi.org/10.3390/app122010348 - 14 Oct 2022

Cited by 2 | Viewed by 2186

Abstract

Since the supply of basic needs, especially food, is among the strategic priorities of each country and conventional food production methods no longer suffice, food production methods are now transforming into industrial approaches. Industrialization, however, requires higher energy usage. Greater energy demand brings [...] Read more.

Since the supply of basic needs, especially food, is among the strategic priorities of each country and conventional food production methods no longer suffice, food production methods are now transforming into industrial approaches. Industrialization, however, requires higher energy usage. Greater energy demand brings about the issue of energy sustainability. In particular, the depletion of fossil fuels results in serious challenges in food production processes. On the other hand, the utilization of energy carriers is accompanied by environmental contamination. In this regard, evaluating energy consumption and environmental pollution in the production systems can be a proper approach to finding the energy consumption and pollution centers for presenting applicable solutions to decrease pollution. In this study, energy indices of ER, EP, SE, and NEG were assessed to evaluate the energy consumption of lettuce production. The results showed values of 0.4, 17.28 kg/MJ, 0.06 MJ/kg, and 29,922 MG/ha for ER, EP, SE, and NEG, respectively. Among the consumption inputs, diesel fuel and nitrogen fertilizer had the highest consumption rate. Pollutants were also explored by the life cycle assessment method. Accordingly, chemicals and agricultural machinery led to the highest contaminating emissions. To reduce environmental contaminants, lowering the application of chemical pesticides, using biological approaches to combat pests, determining the proper amount of chemical fertilizers, using animal fertilizers, and using the proper agricultural machines should be considered. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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20 pages, 3539 KiB

Open AccessArticle

Influence of Self-Compaction on the Airflow Resistance of Aerated Wheat Bulks (Triticum aestivum L., cv. ‘Pionier’)

by Iris Ramaj, Steffen Schock, Shkelqim Karaj and Joachim Müller

Appl. Sci. 2022, 12(17), 8909; https://doi.org/10.3390/app12178909 - 5 Sep 2022

Cited by 6 | Viewed by 1965

Abstract

Aeration is a key post-harvest grain processing operation that forces air through the pore volume of the grain bulk to establish favorable conditions to maintain grain quality and improve its storability. However, during storage, grain bulk experiences self-compaction due to its dead weight, [...] Read more.

Aeration is a key post-harvest grain processing operation that forces air through the pore volume of the grain bulk to establish favorable conditions to maintain grain quality and improve its storability. However, during storage, grain bulk experiences self-compaction due to its dead weight, which alters the bulk properties and impedes the uniform flow of air during aeration. Thus, this study focused on investigating the effect of self-compaction on the pressure drop ΔP of wheat bulk (Triticum aestivum L., cv. ‘Pionier’, X = 0.123 kg·kg⁻¹ d.b.) accommodated in a laboratory-scale bin (V_b = 0.62 m³) at a coherent set of airflow velocities v_a. Pressure drop ΔP was measured at bulk depths H_b of 1.0, 2.0, 3.0 and 3.4 m and storage times t of 1, 65, 164 and 236 h. For the semi-empirical characterization of the relationship between ΔP and v_a, the model of Matthies and Petersen was used, which was proficient in describing the experimental data with decent accuracy (R² = 0.990, RMSE = 68.67 Pa, MAPE = 12.50%). A tailored product factor k was employed for the specific grain bulk conditions. Results revealed a reduction of in-situ pore volume ε from 0.413 to 0.391 at bulk depths H_b of 1.0 to 3.4 m after 1 h storage time t and from 0.391 to 0.370 after 236 h storage time t, respectively. A disproportional increase of the pressure drop ΔP with bulk depth H_b and storage time t was observed, which was ascribed to the irreversible spatio-temporal behavior of self-compaction. The variation of pore volume ε was modeled and facilitated the development of a generalized model for predicting the relationship between ΔP and v_a. The relative importance of modeling parameters was evaluated by a sensitivity analysis. In conclusion, self-compaction has proven to have a significant effect on airflow resistance, therefore it should be considered in the analysis and modeling of cooling, aeration and low-temperature drying of in-store grain bulks. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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18 pages, 6987 KiB

Open AccessArticle

Real-Time Strawberry Plant Classification and Efficiency Increase with Hybrid System Deep Learning: Microcontroller and Mobile Application

by Selami Kesler, Abdil Karakan and Yüksel Oğuz

Appl. Sci. 2022, 12(17), 8860; https://doi.org/10.3390/app12178860 - 3 Sep 2022

Cited by 3 | Viewed by 2065

Abstract

The strawberry plant has three life stages: seedling, blooming, and crop. It needs different acclimatization conditions in these life stages. A dataset consisting of 10,000 photographs of the strawberry plant was prepared. Using this dataset, classification in convolutional neural networks was performed in [...] Read more.

The strawberry plant has three life stages: seedling, blooming, and crop. It needs different acclimatization conditions in these life stages. A dataset consisting of 10,000 photographs of the strawberry plant was prepared. Using this dataset, classification in convolutional neural networks was performed in Matrix Laboratory (MATLAB). Nine different algorithms were used in this process. They were realized in ResNet101 architecture, and the highest accuracy rate was 99.8%. A low-resolution camera was used while growing strawberry plants in the application greenhouse. Every day at 10:00, a picture of the strawberry plant was taken. The captured image was processed in ResNet101 architecture. The result of the detection process appeared on the computer screen and was sent to the microcontroller via a USB connection. The microcontroller adjusted air-conditioning in the greenhouse according to the state of the strawberry plant. For this, it decided based on the data received from the temperature, humidity, wind direction, and wind speed sensors outside the greenhouse and the temperature, humidity, and soil moisture sensors inside the greenhouse. In addition, all data from the sensors and the life stage of the plant were displayed with a mobile application. The mobile application also provided the possibility for manual control. In the study, the greenhouse was divided into two. Strawberries were grown with the hybrid system on one side of the greenhouse and a normal system on the other side of the greenhouse. This study achieved 9.75% more crop, had a 4.75% earlier crop yield, and required 8.59% less irrigation in strawberry plants grown using the hybrid system. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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20 pages, 4488 KiB

Open AccessArticle

Design and Application of Liquid Fertilizer pH Regulation Controller Based on BP-PID-Smith Predictive Compensation Algorithm

by Zihao Meng, Lixin Zhang, He Li, Runmeng Zhou, Haoran Bu, Yongchao Shan, Xiao Ma and Ruihao Ma

Appl. Sci. 2022, 12(12), 6162; https://doi.org/10.3390/app12126162 - 17 Jun 2022

Cited by 6 | Viewed by 2217

Abstract

The pH value of liquid fertilizer is a key factor affecting crop growth, so it is necessary to regulate its pH value. However, the pH regulation system has the characteristics of nonlinearity and time lag, which makes it difficult for the conventional controller [...] Read more.

The pH value of liquid fertilizer is a key factor affecting crop growth, so it is necessary to regulate its pH value. However, the pH regulation system has the characteristics of nonlinearity and time lag, which makes it difficult for the conventional controller to achieve accurate pH control. By analyzing the regulation process, this paper designs a BP-PID-Smith prediction compensator, which compensates for the error between the actual model and the theoretical model and improves the control accuracy. The pH regulation system with STM32F103ZET6 as the control core was also developed, and the performance tests were carried out under different flow rates to compare with the regulation system of PID-Smith and Smith algorithms. The experimental results showed that the maximum overshoot of the BP-PID-Smith prediction compensator was 0.27% on average, and the average adjustment time for pH value reduction from 7.5 to 6.8 was 71.39 s, which had good practicality and robustness to meet the actual control demand. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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16 pages, 29659 KiB

Open AccessArticle

CFD Analysis and Validation of a Foreign Material Winnowing Machine for Pepper Harvester

by Seo-Yong Shin, Myoung-Ho Kim, Yongjin Cho and Dae-Cheol Kim

Appl. Sci. 2022, 12(12), 6134; https://doi.org/10.3390/app12126134 - 16 Jun 2022

Cited by 2 | Viewed by 2334

Abstract

The winnowing machine of chili pepper harvesters was developed to reduce the potential problem of low pepper stem and fruit separation. The developed winnowing machine was combined with two impellers and a center bearing to prevent a strain on the drive shaft and [...] Read more.

The winnowing machine of chili pepper harvesters was developed to reduce the potential problem of low pepper stem and fruit separation. The developed winnowing machine was combined with two impellers and a center bearing to prevent a strain on the drive shaft and to ensure durability. The terminal velocity of chili pepper was measured, and an aerodynamic analysis was conducted based on this winnowing machine. A CFD (Computational Fluid Dynamics, Ansys Fluent 2020 R1) analysis was conducted for three levels of discharge port guide form (0, 3, and 5 guides) and three levels of rotating speed (1600, 1800, and 2000 RPM) of a winnowing machine designed utilizing aerodynamic analysis results. A validation test was conducted by fabricating a winnower test device. As for aerodynamic analysis conducted using measured values of terminal velocity, chili pepper fruits were collected at an outlet wind speed lower than 17.5 m/s and chili pepper branches were separated at a speed higher than 12.5 m/s. As a result of CFD analysis, the wind speed deviation at outlets of the 0-, 3-, and 5-guide depending on the rotating speed appeared to be 15.8, 1.4, and 1.0 m/s on average, respectively. The result of the CFD analysis showed values higher than wind speeds of the actual winnower test device by a minimum of 0 and a maximum of 2.4 m/s. Through the CFD analysis and the wind speed validation test of the winnower test device, optimal conditions to separate foreign materials were found to be a winnowing machine at a rotating speed of 1800 RPM with a discharge port having three guides or a winnowing machine at a rotating speed of 2000 RPM with a discharge port having five guides. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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13 pages, 2095 KiB

Open AccessArticle

Influence of Broadleaved Wood Conditioning by Pulsed Electric Field on Its Combustion Heat Characteristics

by Ernest Popardowski and Paweł Kiełbasa

Appl. Sci. 2022, 12(10), 5048; https://doi.org/10.3390/app12105048 - 17 May 2022

Cited by 2 | Viewed by 1419

Abstract

This publication presents changes in sawdust of selected deciduous trees as a consequence of impulse electric field (PEF) stimulation. The analyzed changes concerned the time–temperature characteristics created during the measurement of the heat of combustion of the audited material. Based on experience from [...] Read more.

This publication presents changes in sawdust of selected deciduous trees as a consequence of impulse electric field (PEF) stimulation. The analyzed changes concerned the time–temperature characteristics created during the measurement of the heat of combustion of the audited material. Based on experience from previous studies, two alternatives of electric field strength and one variant of capacitor discharges (pulses) were adopted. The results were compared with the sample not treated with PEF. The selected parameters were the result of previous studies, in which the applied variants seemed to be the most promising, i.e., they gave the most diverse results. The research presented in this work has shown that the pulsed electric field affects the time and temperature characteristics of biological material. The changes are most pronounced for the last period of the combustion process, from the moment the maximum temperature was reached to the end of the process. The obtained results indicate that birch and ash react to PEF conditioning in a similar manner. The second group, due to the similarity of the obtained results, is oak and linden. It seems that, apart from the electric field strength, the obtained results are also influenced by the cellulose content in the tested wood. The described process has a very low energy-efficiency, but the reduction of the energy needed to generate the impulse could lead to the possibility of applying the obtained results in industry. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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12 pages, 2356 KiB

Open AccessArticle

Detection and Factors That Induce Stenocarpella spp. Survival in Maize Stubble and Soil Suppressiveness under Tropical Conditions

by Felipe Augusto Moretti Ferreira Pinto, Victor Biazzotto Correia Porto, Rafaela Araújo Guimarães, Carolina da Silva Siqueira, Mirian Rabelo de Faria, José da Cruz Machado, Henrique Novaes Medeiros, Dagma Dionísia da Silva, Helon Santos Neto, Edson Ampelio Pozza and Flávio Henrique Vasconcelos de Medeiros

Appl. Sci. 2022, 12(10), 4974; https://doi.org/10.3390/app12104974 - 14 May 2022

Cited by 4 | Viewed by 1928

Abstract

Stenocarpella spp. causes stalk and ear rot in maize and overwinters in stubble during the off-season. Understanding the factors that guide saprophytic colonization is a crucial strategy for management. In this study, we analyzed the abiotic factors and crop management practices in relation [...] Read more.

Stenocarpella spp. causes stalk and ear rot in maize and overwinters in stubble during the off-season. Understanding the factors that guide saprophytic colonization is a crucial strategy for management. In this study, we analyzed the abiotic factors and crop management practices in relation to the inoculum of Stenocarpella spp. in stubble by qPCR. Soil samples were used for suppressiveness tests against Fusarium verticillioides, Fusarium graminearum, and Stenocarpella maydis. In the 29 fields, different levels of Stenocarpella spp. were detected. Only three fields were considered suppressive for the three pathogens. Heat maps showed that soil suppressiveness was inversely related to the pathogen concentration, and the suppressiveness of one pathogen was correlated with the suppressiveness of other pathogens. Under no-tillage systems in which rotation with soybeans was adopted, Stenocarpella spp. were detected at lower concentrations than in areas that adopted no-tillage systems with maize monocultures. While in tillage systems, the maize–maize monocropping increases the inoculum level of Stenocarpella spp. Crop rotation is a factor related to the observed reduction in the pathogen concentration and increases in the broad-spectrum antagonistic microbial communities. These communities guide the suppressiveness of soil-borne diseases in maize fields cultivated under tropical conditions. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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20 pages, 1908 KiB

Open AccessArticle

Mobile Internet Technology Adoption for Sustainable Agriculture: Evidence from Wheat Farmers

by Nawab Khan, Ram L. Ray, Hazem S. Kassem and Shemei Zhang

Appl. Sci. 2022, 12(10), 4902; https://doi.org/10.3390/app12104902 - 12 May 2022

Cited by 43 | Viewed by 5353

Abstract

Mobile internet technology (MIT) is considered a significant advancement in information and communication technology (ICT), due to its crucial impact on the financial system and social life. In addition, it is an essential technology to overcome the digital divide between urban and rural [...] Read more.

Mobile internet technology (MIT) is considered a significant advancement in information and communication technology (ICT), due to its crucial impact on the financial system and social life. In addition, it is an essential technology to overcome the digital divide between urban and rural areas. In terms of agricultural advancement, MIT can play a key role in data collection and the implementation of smart agricultural technologies. The main objectives of this study were to (i) investigate MIT adoption and use in sustainable agriculture development among selected wheat farmers of Pakistan and (ii) examine the crucial factors influencing MIT adoption. This study selected 628 wheat farmers from four districts of Khyber Pakhtunkhwa Province (KPK), Pakistan, for sampling. This study used a bivariate probit method for sampling wheat farmers. The analysis of wheat farmer’s data showed farmer’s age, farm size, farm location, and knowledge about Internet technology (IT) are strongly correlated with MIT adoption in sustainable agriculture development. Results showed on average, 65% of wheat farmers have mobile devices supporting these Internet technologies, and 55% use MIT in agricultural environments. Since the extant research on MIT adoption for agriculture production in Pakistan is sparse, this study helps advance MIT adoption-based studies. These outcomes may draw the attention of decision-makers dealing with IT infrastructure and agricultural equipment who can support farmers adopting MIT. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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13 pages, 3254 KiB

Open AccessArticle

Compression and Fungal Heat Production in Maize Bulk Considering Kernel Breakage

by Chaosai Liu, Yang Zhou, Guixiang Chen, Deqian Zheng and Longfei Yue

Appl. Sci. 2022, 12(10), 4870; https://doi.org/10.3390/app12104870 - 11 May 2022

Cited by 4 | Viewed by 1633

Abstract

Breakage in maize kernels and vertical pressure in grains lead to the uneven distribution of grain bulk density, which easily causes undesired problems in terms of grain storage. The objective of this study was, therefore, to determine the compression and heat production of [...] Read more.

Breakage in maize kernels and vertical pressure in grains lead to the uneven distribution of grain bulk density, which easily causes undesired problems in terms of grain storage. The objective of this study was, therefore, to determine the compression and heat production of the whole kernel (WK) and half kernel (HK) under two different loadings, i.e., 50 and 150 kPa, in maize bulk. An easy-to-use element testing system was developed by modification of an oedometer, and an empirical–analytical–numerical method was established to evaluate fungal heat production, considering kernel breakage and vertical pressure. Based on the experimental results, it was found that breakage induced larger compression; the compression of HK was 62% and 58% higher than that of WK at 50 kPa and 150 kPa, respectively. The creep model of the Hooke spring–Kelvin model in series can be used to accurately describe the creep behavior of maize bulk. Fungi and aerobic plate counting (APC) were affected significantly by the breakage and vertical pressure. APC in HK was 19 and 15 times that of WK under 150 and 50 kPa, respectively. The heat released by the development of fungi was found to be directly related to the APC results. The average temperatures of WK and HK under 150 and 50 kPa were 11.1%, 9.7%, 7.9%, and 7.6% higher than the room temperature, respectively. A numerical method was established to simulate the temperature increase due to fungi development. Based on the numerical results, heat production (Q) by fungi was estimated, and the results showed that the Q in HK was 1.29 and 1.32 times that of WK on average under 150 and 50 kPa. Additionally, the heat production results agreed very well with the APC results. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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18 pages, 4337 KiB

Open AccessArticle

Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC)

by Wilmer Quimbita, Edison Toapaxi and Jacqueline Llanos

Appl. Sci. 2022, 12(9), 4235; https://doi.org/10.3390/app12094235 - 22 Apr 2022

Cited by 9 | Viewed by 2748

Abstract

Traditional irrigation techniques usually cause the wasting of water resources. In addition, crops that are located in rural areas require water pumps that are powered by environmentally unfriendly fossil fuels. This research proposes a smart irrigation system energized by a microgrid. The proposal [...] Read more.

Traditional irrigation techniques usually cause the wasting of water resources. In addition, crops that are located in rural areas require water pumps that are powered by environmentally unfriendly fossil fuels. This research proposes a smart irrigation system energized by a microgrid. The proposal includes two stages: the first generates the daily irrigation profile based on an expert system for the adequate use of the water. Then, considering the irrigation profile, the power required for the water pump is measured—the optimal daily profile of electricity demand is determined in the second stage. The energy system is a microgrid composed of solar energy, a battery energy storage system (BESS) and a diesel generator. The microgrid is managed by an energy management system (EMS) that is based on model predictive control (MPC). The system selects the optimal start-up time of the water pump considering the technical aspects of irrigation and of the microgrid. The proposed methodology is validated by a simulation with real data from an alfalfa crop in an area of Ecuador. The results show that the smart irrigation proposed considers technical aspects that benefit the growth of the crops being studied and also avoids the waste of water. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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16 pages, 4455 KiB

Open AccessArticle

Method for Prolonging the Shelf Life of Apples after Storage

by Bogdan Saletnik, Grzegorz Zaguła, Aneta Saletnik, Marcin Bajcar, Ewelina Słysz and Czesław Puchalski

Appl. Sci. 2022, 12(8), 3975; https://doi.org/10.3390/app12083975 - 14 Apr 2022

Cited by 17 | Viewed by 3822

Abstract

This study investigated the effects of the use of low magnetic fields as a potential method for improving the quality of apples after storage. The fruit were exposed to 100 μT magnetic fields for 8 h per day and kept for a period [...] Read more.

This study investigated the effects of the use of low magnetic fields as a potential method for improving the quality of apples after storage. The fruit were exposed to 100 μT magnetic fields for 8 h per day and kept for a period of two weeks in room conditions. The results showed that the samples that were treated with a magnetic field generally had a higher value ratio of total soluble solid and titratable acidity compared to the untreated samples, which indicated their higher quality. Continuous treatment with a magnetic field influenced the mechanical properties of apples, as demonstrated by the greater firmness, lower weight loss and suppressed CO₂ production of the apples that were stored in room conditions. After the treatment of the apples, a new product was produced with greater firmness, higher quality potential (the ratio of total soluble solid and titratable acidity) and an extended shelf life/lower respiration rate. Therefore, treatment with a magnetic field can be used to extend the shelf life of apples and needs to be demonstrated by further investigations. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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13 pages, 2816 KiB

Open AccessArticle

Theory of Movement of Machine-Tractor Unit with Trailer Haulm Harvester Machine

by Volodymyr Bulgakov, Aivars Aboltins, Semjons Ivanovs, Hristo Beloev, Volodymyr Nadykto, Yevhen Ihnatiev and Jüri Olt

Appl. Sci. 2022, 12(8), 3901; https://doi.org/10.3390/app12083901 - 12 Apr 2022

Cited by 3 | Viewed by 2140

Abstract

Harvesting sugar and fodder beet tops is a complex technological process that requires the use of special harvesting machines. Trailed harvesters of different rows, which together with aggregate tractors form symmetric or asymmetric machine-tractor units, the movement of which in the horizontal plane [...] Read more.

Harvesting sugar and fodder beet tops is a complex technological process that requires the use of special harvesting machines. Trailed harvesters of different rows, which together with aggregate tractors form symmetric or asymmetric machine-tractor units, the movement of which in the horizontal plane is not always stable, are widely used. The purpose of this study is to determine the parameters of stable plane-parallel motion of asymmetric harvester machine-tractor unit based on numerical computer simulation of the obtained analytical dependencies. According to the results of the analytical study, the values of the amplitude and phase-frequency characteristics of the turning angle tractor’s oscillations were obtained. They reflect the reproduction by the angle rotation fluctuations of the haulm harvester machine in the horizontal plane. Calculations have shown that reducing the value of the input resistance coefficient of pneumatic tires of the driving wheels of the aggregating tractor increases its sensitivity to the action of disturbing influences. The greater the sensitivity, the closer the wheels of the power tool are to the attachment point of the trailed haulm harvester. In qualitative terms, increasing the speed of the machine-tractor unit from 1.5 to 2.5 m∙s⁻¹ leads to an undesirable increase in the amplitude-frequency response and desired increase in the phase-frequency response when reproducing its external disturbing effects in the form of oscillations of the angle of rotation of the harvester. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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15 pages, 2786 KiB

Open AccessArticle

Efficacy of Four In Vitro Fungicides for Control of Wilting of Strawberry Crops in Puebla-Mexico

by Alba Cruz Coronel, Conrado Parraguirre Lezama, Yesenia Pacheco Hernández, Olga Santiago Trinidad, Antonio Rivera Tapia and Omar Romero-Arenas

Appl. Sci. 2022, 12(7), 3213; https://doi.org/10.3390/app12073213 - 22 Mar 2022

Cited by 4 | Viewed by 3897

Abstract

Strawberry wilt is an established disease of strawberry crops caused by fungus Fusarium solani. In Mexico, strawberry cultivation represents an important productive activity for several rural areas; however, wilt disease affects producers economically. The objectives of this research were: (a) to identify [...] Read more.

Strawberry wilt is an established disease of strawberry crops caused by fungus Fusarium solani. In Mexico, strawberry cultivation represents an important productive activity for several rural areas; however, wilt disease affects producers economically. The objectives of this research were: (a) to identify and morphologically characterize strain “MA-FC120” associated with root rot and wilting of strawberry crops in Santa Cruz Analco, municipality of San Salvador el Verde, Puebla-Mexico; (b) to evaluate the potential of single and multiple applications of four broad-spectrum fungicides used against F. solani in vitro. Plant tissue samples were collected from strawberry crops in Puebla-Mexico with presence of symptoms of desiccation and root rot. Strain “MA-FC120” was identified as F. solani, being the causal agent of wilt and root rot in strawberry plants from Santa Cruz Analco. Fungicide Benomyl 50^® showed the highest percentage of inhibition on F. solani (100%) under in vitro conditions. The fungicide Mancosol 80^® and Talonil 75^® at low concentration (600 and 450 mg L⁻¹) showed no toxicity, being harmless to strain MA-FC120. However, fungicide Talonil 75^® showed slight toxicity at the dose recommended by the manufacturer and moderate toxicity in high concentration (1350 mg L⁻¹). Likewise, Captan 50^® in its three concentrations evaluated showed slight toxicity, obtaining around 50% on the classification scale established by International Organization for Biological Control (IOBC). Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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15 pages, 5920 KiB

Open AccessArticle

Autonomous Detection of Spodoptera frugiperda by Feeding Symptoms Directly from UAV RGB Imagery

by Jiedong Feng, Yaqin Sun, Kefei Zhang, Yindi Zhao, Yi Ren, Yu Chen, Huifu Zhuang and Shuo Chen

Appl. Sci. 2022, 12(5), 2592; https://doi.org/10.3390/app12052592 - 2 Mar 2022

Cited by 11 | Viewed by 3759

Abstract

The use of digital technologies to detect, position, and quantify pests quickly and accurately is very important in precision agriculture. Imagery acquisition using air-borne drones in combination with the deep learning technique is a new and viable solution to replace human labor such [...] Read more.

The use of digital technologies to detect, position, and quantify pests quickly and accurately is very important in precision agriculture. Imagery acquisition using air-borne drones in combination with the deep learning technique is a new and viable solution to replace human labor such as visual interpretation, which consumes a lot of time and effort. In this study, we developed a method for automatic detecting an important maize pest—Spodoptera frugiperda—by its gnawing holes on maize leaves based on convolution neural network. We validated the split-attention mechanism in the classical network structure ResNet50, which improves the accuracy and robustness, and verified the feasibility of two kinds of gnawing holes as the identification features of Spodoptera frugiperda invasion and the degree. In order to verify the robustness of this detection method against plant morphological changes, images at the jointing stage and heading stage were used for training and testing, respectively. The performance of the models trained with the jointing stage images has been achieved the validation accuracy of ResNeSt50, ResNet50, EfficientNet, and RegNet at 98.77%, 97.59%, 97.89%, and 98.07%, with a heading stage test accuracy of 89.39%, 81.88%, 86.21%, and 84.21%. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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16 pages, 6865 KiB

Open AccessArticle

Analysis of RGB Plant Images to Identify Root Rot Disease in Korean Ginseng Plants Using Deep Learning

by Praveen Kumar Jayapal, Eunsoo Park, Mohammad Akbar Faqeerzada, Yun-Soo Kim, Hanki Kim, Insuck Baek, Moon S. Kim, Domnic Sandanam and Byoung-Kwan Cho

Appl. Sci. 2022, 12(5), 2489; https://doi.org/10.3390/app12052489 - 27 Feb 2022

Cited by 15 | Viewed by 3045

Abstract

Ginseng is an important medicinal plant in Korea. The roots of the ginseng plant have medicinal properties; thus, it is very important to maintain the quality of ginseng roots. Root rot disease is a major disease that affects the quality of ginseng roots. [...] Read more.

Ginseng is an important medicinal plant in Korea. The roots of the ginseng plant have medicinal properties; thus, it is very important to maintain the quality of ginseng roots. Root rot disease is a major disease that affects the quality of ginseng roots. It is important to predict this disease before it causes severe damage to the plants. Hence, there is a need for a non-destructive method to identify root rot disease in ginseng plants. In this paper, a method to identify the root rot disease by analyzing the RGB plant images using image processing and deep learning is proposed. Initially, plant segmentation is performed, and then the noise regions are removed in the plant images. These images are given as input to the proposed linear deep learning model to identify root rot disease in ginseng plants. Transfer learning models are also applied to these images. The performance of the proposed method is promising in identifying root rot disease. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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14 pages, 3617 KiB

Open AccessArticle

A Low-Cost Global Navigation Satellite System Positioning Accuracy Assessment Method for Agricultural Machinery

by Dorijan Radočaj, Ivan Plaščak, Goran Heffer and Mladen Jurišić

Appl. Sci. 2022, 12(2), 693; https://doi.org/10.3390/app12020693 - 11 Jan 2022

Cited by 12 | Viewed by 3059

Abstract

The high-precision positioning and navigation of agricultural machinery represent a backbone for precision agriculture, while its worldwide implementation is in rapid growth. Previous studies improved low-cost global navigation satellite system (GNSS) hardware solutions and fused GNSS data with complementary sources, but there is [...] Read more.

The high-precision positioning and navigation of agricultural machinery represent a backbone for precision agriculture, while its worldwide implementation is in rapid growth. Previous studies improved low-cost global navigation satellite system (GNSS) hardware solutions and fused GNSS data with complementary sources, but there is still no affordable and flexible framework for positioning accuracy assessment of agricultural machinery. Such a low-cost method was proposed in this study, simulating the actual movement of the agricultural machinery during agrotechnical operations. Four of the most commonly used GNSS corrections in Croatia were evaluated in two repetitions: Croatian Positioning System (CROPOS), individual base station, Satellite-based Augmentation Systems (SBASs), and an absolute positioning method using a smartphone. CROPOS and base station produced the highest mean GNSS positioning accuracy of 2.4 and 2.9 cm, respectively, but both of these corrections produced lower accuracy than declared. All evaluated corrections produced significantly different median values in two repetitions, representing inconsistency of the positioning accuracy regarding field conditions. While the proposed method allowed flexible and effective application in the field, future studies will be directed towards the reduction of the operator’s subjective impact, mainly by implementing autosteering solutions in agricultural machinery. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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13 pages, 275 KiB

Open AccessArticle

Effect of Poultry and Goat Manures on the Nutrient Content of Sesamum alatum Leafy Vegetables

by Khulekani Cyprian Mbatha, Charmaine Ntokozo Mchunu, Sydney Mavengahama and Nontuthuko Rosemary Ntuli

Appl. Sci. 2021, 11(24), 11933; https://doi.org/10.3390/app112411933 - 15 Dec 2021

Cited by 11 | Viewed by 4538

Abstract

Sesamum alatum Thonn. is one of the less-popular but nutritious leafy vegetables that is still collected from the wild or as weeds among crops in South Africa. The plant is also used in medicines and cosmetics in Africa and elsewhere. Despite its importance, [...] Read more.

Sesamum alatum Thonn. is one of the less-popular but nutritious leafy vegetables that is still collected from the wild or as weeds among crops in South Africa. The plant is also used in medicines and cosmetics in Africa and elsewhere. Despite its importance, the cultivation of S. alatum under different agronomic systems for improved harvestable yield and nutrient content is still lacking. The study aimed to determine the response of S. alatum nutrient content to the application of poultry and goat manures. Plants were grown in pots under rain-fed shade cloth conditions, with poultry and goat manures applied at 0, 1, 2, and 3 t ha^–1 each, and they were laid in a completely randomized design. Shoot tips were harvested at 60 days after planting and analyzed for nutrient content. Shoots contained better nutrients in S. alatum plants grown during the first than the second season, with minor exceptions. Poultry and goat manure application led to an increase in Ca, Mg, K, P, and micro-nutrients. Goat manure had potential to increase the nutrient content in S. alatum than poultry manure, although differences were not substantial. Therefore, both manures could be equally used to improve nutrient content of S. alatum. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

17 pages, 8060 KiB

Open AccessArticle

Measuring System Design and Experiment for Ground Pressure on Seeding Skateboard of Rice Direct Seeding Machine

by Yuan Gao, Guozhong Zhang, Hongchang Wang, Abouelnadar Salem, Jianwei Fu and Yong Zhou

Appl. Sci. 2021, 11(21), 10024; https://doi.org/10.3390/app112110024 - 26 Oct 2021

Cited by 2 | Viewed by 1867

Abstract

Acquiring real-time ground pressure measurements from the surface of the soil in working parts of paddy fields is a challenging task. The real-time data can be used to monitor the changing state of the ground pressure of the working parts in a paddy [...] Read more.

Acquiring real-time ground pressure measurements from the surface of the soil in working parts of paddy fields is a challenging task. The real-time data can be used to monitor the changing state of the ground pressure of the working parts in a paddy field. To effectively reduce the accumulation of choked mud at the front end of the seeding skateboard and the contact adhesion between the skateboard and the paddy soil, a ground pressure measuring device suitable for paddy fields was designed. The device uses an Arduino controller, combined with Internet of things technology and wireless measurement technology. It can measure the pressure from 16 measuring points at the same time and transmit the measurement data to the computer remotely through the Internet of things technology, which greatly reduces the labor intensity of measuring personnel in the muddy paddy field. Analysis of the data showed that the forward tilt angle, ground pressure, and forward resistance of the seeding skateboard also increased with the increase of forward speed and vertical load. In addition, the distribution law of the ground pressure between the skateboard and the paddy soil was obtained. The conclusions show that the ground pressure measurement system can work stably in the paddy field and the measured data can be wirelessly transmitted to the computer and mobile phone. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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14 pages, 2986 KiB

Open AccessArticle

Preliminary Research on the Influence of a Pulsed Magnetic Field on the Cationic Profile of Sunflower, Cress, and Radish Sprouts and on Their Germination Rate

by Grzegorz Zaguła, Bogdan Saletnik, Marcin Bajcar, Aneta Saletnik and Czesław Puchalski

Appl. Sci. 2021, 11(20), 9678; https://doi.org/10.3390/app11209678 - 17 Oct 2021

Cited by 2 | Viewed by 1998

Abstract

Magnetic stimulation of seeds before sowing can have a significant impact on the speed of their germination. Sprouts are sought after by consumers for their high nutrient content. The purpose of the study was to investigate the influence of a pulsed magnetic field [...] Read more.

Magnetic stimulation of seeds before sowing can have a significant impact on the speed of their germination. Sprouts are sought after by consumers for their high nutrient content. The purpose of the study was to investigate the influence of a pulsed magnetic field on the dynamics of seed germination and on the content of ions in sunflower, cress, and radish sprouts. The research material in the experiment was provided by seeds of sunflower (Helianthus annuus L.), garden cress (Lepidium sativum L.), and garden radish (Raphanus sativus L.) intended for sprouting, which were supplied by PNOS Ożarów Mazowiecki. The research methods involved germinating seeds under strictly defined conditions for 14 days. Then, the mineral composition of the previously mineralised sprout material was determined using emission spectrometry on a ICP-OES iCAP Duo 6500 Termo spectrometer. Greater dynamics of germination were noted in the first half of the growth period in seeds stimulated with a pulsed magnetic field with the parameters 100 µT and 100 Hz. However, the application of the magnetic field produced no increase in the capacity of the seeds to germinate. The research showed an increase in the content of macronutrients in sprouts, such as calcium, magnesium, phosphorus, and sulphur. In the case of the field with parameters of 100 µT and 200 Hz, the effect was similar for both the germination percentage and the accumulation of macronutrients. However, in the case of both frequencies of magnetic field applied, the effect on individual plant seed species was different. Pre-sowing stimulation of seeds with a pulsed magnetic field may affect the rate of seed germination and the content of ions in the sprouts; however, these effects vary in individual plant matrices. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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20 pages, 11751 KiB

Open AccessFeature PaperArticle

Comparing Performances of CNN, BP, and SVM Algorithms for Differentiating Sweet Pepper Parts for Harvest Automation

by Bongki Lee, Donghwan Kam, Yongjin Cho, Dae-Cheol Kim and Dong-Hoon Lee

Appl. Sci. 2021, 11(20), 9583; https://doi.org/10.3390/app11209583 - 14 Oct 2021

Cited by 5 | Viewed by 1847

Abstract

For harvest automation of sweet pepper, image recognition algorithms for differentiating each part of a sweet pepper plant were developed and performances of these algorithms were compared. An imaging system consisting of two cameras and six halogen lamps was built for sweet pepper [...] Read more.

For harvest automation of sweet pepper, image recognition algorithms for differentiating each part of a sweet pepper plant were developed and performances of these algorithms were compared. An imaging system consisting of two cameras and six halogen lamps was built for sweet pepper image acquisition. For image analysis using the normalized difference vegetation index (NDVI), a band-pass filter in the range of 435 to 950 nm with a broad spectrum from visible light to infrared was used. K-means clustering and morphological skeletonization were used to classify sweet pepper parts to which the NDVI was applied. Scale-invariant feature transform (SIFT) and speeded-up robust features (SURFs) were used to figure out local features. Classification performances of a support vector machine (SVM) using the radial basis function kernel and backpropagation (BP) algorithm were compared to classify local SURFs of fruits, nodes, leaves, and suckers. Accuracies of the BP algorithm and the SVM for classifying local features were 95.96 and 63.75%, respectively. When the BP algorithm was used for classification of plant parts, the recognition success rate was 94.44% for fruits, 84.73% for nodes, 69.97% for leaves, and 84.34% for suckers. When CNN was used for classifying plant parts, the recognition success rate was 99.50% for fruits, 87.75% for nodes, 90.50% for leaves, and 87.25% for suckers. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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11 pages, 8913 KiB

Open AccessArticle

A Digital Twin Architecture to Optimize Productivity within Controlled Environment Agriculture

by Jesus David Chaux, David Sanchez-Londono and Giacomo Barbieri

Appl. Sci. 2021, 11(19), 8875; https://doi.org/10.3390/app11198875 - 24 Sep 2021

Cited by 54 | Viewed by 6050

Abstract

To ensure food security, agricultural production systems should innovate in the direction of increasing production while reducing utilized resources. Due to the higher level of automation with respect to traditional agricultural systems, Controlled Environment Agriculture (CEA) applications generally achieve better yields and quality [...] Read more.

To ensure food security, agricultural production systems should innovate in the direction of increasing production while reducing utilized resources. Due to the higher level of automation with respect to traditional agricultural systems, Controlled Environment Agriculture (CEA) applications generally achieve better yields and quality crops at the expenses of higher energy consumption. In this context, Digital Twin (DT) may constitute a fundamental tool to reach the optimization of the productivity, intended as the ratio between production and resource consumption. For this reason, a DT Architecture for CEA systems is introduced within this work and applied to a case study for its validation. The proposed architecture is potentially able to optimize productivity since it utilizes simulation software that enables the optimization of: (i) Climate control strategies related to the control of the crop microclimate; (ii) treatments related to crop management. Due to the importance of food security in the worldwide landscape, the authors hope that this work may impulse the investigation of strategies for improving the productivity of CEA systems. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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15 pages, 5141 KiB

Open AccessArticle

Design of an Intelligent Variable-Flow Recirculating Aquaculture System Based on Machine Learning Methods

by Fudi Chen, Yishuai Du, Tianlong Qiu, Zhe Xu, Li Zhou, Jianping Xu, Ming Sun, Ye Li and Jianming Sun

Appl. Sci. 2021, 11(14), 6546; https://doi.org/10.3390/app11146546 - 16 Jul 2021

Cited by 11 | Viewed by 4187

Abstract

A recirculating aquaculture system (RAS) can reduce water and land requirements for intensive aquaculture production. However, a traditional RAS uses a fixed circulation flow rate for water treatment. In general, the water in an RAS is highly turbid only when the animals are [...] Read more.

A recirculating aquaculture system (RAS) can reduce water and land requirements for intensive aquaculture production. However, a traditional RAS uses a fixed circulation flow rate for water treatment. In general, the water in an RAS is highly turbid only when the animals are fed and when they excrete. Therefore, RAS water quality regulation technology based on process control is proposed in this paper. The intelligent variable-flow RAS was designed based on the circulating pump-drum filter linkage working model. Machine learning methods were introduced to develop the intelligent regulation model to maintain a clean and stable water environment. Results showed that the long short-term memory network performed with the highest accuracy (training set 100%, test set 96.84%) and F1-score (training 100%, test 93.83%) among artificial neural networks. Optimization methods including grid search, cuckoo search, linear squares, and gene algorithm were proposed to improve the classification ability of support vector machine models. Results showed that all support vector machine models passed cross-validation and could meet accuracy standards. In summary, the gene algorithm support vector machine model (accuracy: training 100%, test 98.95%; F1-score: training 100%, test 99.17%) is suitable as an optimal variable-flow regulation model for an intelligent variable-flow RAS. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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19 pages, 1073 KiB

Open AccessReview

The Effect of UV-C Irradiation on the Mechanical and Physiological Properties of Potato Tuber and Different Products

by Addis Lemessa, Ernest Popardowski, Tomasz Hebda and Tomasz Jakubowski

Appl. Sci. 2022, 12(12), 5907; https://doi.org/10.3390/app12125907 - 10 Jun 2022

Cited by 10 | Viewed by 3158

Abstract

Amongst the surface treatment technologies to emerge in the last few decades, UV-C radiation surface treatment is widely used in food process industries for the purpose of shelf life elongation, bacterial inactivation, and stimulation. However, the short wave application is highly dose-dependent and [...] Read more.

Amongst the surface treatment technologies to emerge in the last few decades, UV-C radiation surface treatment is widely used in food process industries for the purpose of shelf life elongation, bacterial inactivation, and stimulation. However, the short wave application is highly dose-dependent and induces different properties of the product during exposure. Mechanical properties of the agricultural products and their derivatives represent the key indicator of acceptability by the end-user. This paper surveys the recent findings of the influence of UV-C on the stress response and physiological change concerning the mechanical and textural properties of miscellaneous agricultural products with a specific focus on a potato tuber. This paper also reviewed the hormetic effect of UV-C triggered at a different classification of doses studied so far on the amount of phenolic content, antioxidants, and other chemicals responsible for the stimulation process. The combined technologies with UV-C for product quality improvement are also highlighted. The review work draws the current challenges as well as future perspectives. Moreover, a way forward in the key areas of improvement of UV-C treatment technologies is suggested that can induce a favorable stress, enabling the product to achieve self-defense mechanisms against wound, impact, and mechanical damage. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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22 pages, 870 KiB

Open AccessReview

Effect of Magnetic and Electrical Fields on Yield, Shelf Life and Quality of Fruits

by Bogdan Saletnik, Grzegorz Zaguła, Aneta Saletnik, Marcin Bajcar, Ewelina Słysz and Czesław Puchalski

Appl. Sci. 2022, 12(6), 3183; https://doi.org/10.3390/app12063183 - 21 Mar 2022

Cited by 17 | Viewed by 7613

Abstract

The presented article is a review of the literature reports on the influence of magnetic and electric fields on the growth, yield, ripening, and durability of fruits and their quality. The article shows the potential application of MF and EF in agricultural production. [...] Read more.

The presented article is a review of the literature reports on the influence of magnetic and electric fields on the growth, yield, ripening, and durability of fruits and their quality. The article shows the potential application of MF and EF in agricultural production. Magnetic and electrical fields increase the shelf life of the fruit and improve its quality. Alternating magnetic fields (AMF) with a value of 0.1–200 mT and a power frequency of 50 Hz or 60 Hz improve plant growth parameters. MF cause an increase in firmness, the rate of maturation, the content of beta-carotene, lycopene, and fructose, sugar concentration, and a reduction in acidity and respiration. The most common is a high-voltage electric field (HVEF) of 2–3.61 kV/cm. These fields extend the shelf life and improve the quality of fruit by decreasing respiration rate and ethylene production. The presented methods seem to be a promising way to increase the quantity and quality of crops in agricultural and fruit production. They are suitable for extending the shelf life of fruit and vegetables during their storage. Further research is needed to develop an accessible and uncomplicated way of applying MF and AEF in agricultural and fruit production. Full article

(This article belongs to the Special Issue Engineering of Smart Agriculture)

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