Topic Editors

Department of Agricultural Engineering, Bahauddin Zakariya University, Multan 60800, Pakistan
Department of Agricultural Engineering, College of Engineering, China Agricultural University, Beijing 100083, China
Leibniz Institute for Agricultural Engineering and Bioeconomy, 14469 Potsdam, Germany
Department of Mechanical, Biomedical and Design Engineering, College of Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UK

Emerging Agricultural Engineering Sciences, Technologies, and Applications

Abstract submission deadline
closed (30 June 2023)
Manuscript submission deadline
closed (31 August 2023)
Viewed by
160753

Topic Information

Dear Colleagues,

Modern agricultural engineering technologies and applications are directly linked with the 2030 United Nations’ Sustainable Development Goals (UN-SDGs). Technological advancement is essential to next-generation agriculture in order to ensure food security, poverty alleviation, and sustainability. Worldwide, it is directly associated with farm mechanization; automation and robotics; intelligent agriculture; high-efficiency irrigation systems; indoor farming and soilless agriculture; precision/conservation agriculture; farm energy systems; post-harvest storage/processing and value addition; tillage and cultivation; spraying and harvesting machinery; livestock and poultry sheds; safe utilization of coal and bioenergy; remote sensing and geographical studies; wastewater management; societal aspects in agriculture; and the associated bioenvironment. Consequently, this topic aims to explore the interdisciplinary nature of research on such agricultural engineering sciences, technologies, and applications from the viewpoint of the agricultural water–energy–food-security nexus. Increasing agriculture modernization mitigates conventional energy reserves, which also escalates greenhouse-gas emissions and climate change. Carbon-neutral development and clean-energy utilization are also associated with the UN-SDGs. Thus, it is important to develop energy-efficient and environmentally friendly solutions to ensure the agriculture sector achieves the UN-SDGs.

This topic invites a wide range of emerging concepts on the agricultural engineering technologies and applications by which sustainable agriculture and associated UN-SDGs can be ensured. We look forward to receiving cutting-edge original research, review, case studies, and/or recent progress/scenarios.

Dr. Muhammad Sultan
Dr. Yuguang Zhou
Dr. Redmond R. Shamshiri
Dr. Muhammad Imran
Topic Editors

Keywords

  • biomass, bioenergy, and clean fuel
  • farm mechanization and robotics
  • food science and processing
  • high-efficiency irrigation systems
  • hydroponic and aeroponic agriculture
  • irrigation systems and applications
  • modern control sheds and livestock barns
  • next-generation greenhouses
  • precision farming and food security
  • renewable energy for agriculture
  • smart and sustainable agriculture
  • solar dryers and solar pumping
  • sustainable bioenvironment
  • temperature/humidity control in agriculture
  • water and wastewater treatment

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Agriculture
agriculture
3.6 4.9 2011 17.7 Days CHF 2600
AgriEngineering
agriengineering
2.8 4.7 2019 25.8 Days CHF 1600
Energies
energies
3.2 6.2 2008 16.1 Days CHF 2600
Sustainability
sustainability
3.9 6.8 2009 18.8 Days CHF 2400
Water
water
3.4 5.8 2009 16.5 Days CHF 2600

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Published Papers (59 papers)

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33 pages, 1212 KiB  
Article
Proposal of a Model of Irrigation Operations Management for Exploring the Factors That Can Affect the Adoption of Precision Agriculture in the Context of Agriculture 4.0
by Sergio Monteleone, Edmilson Alves de Moraes, Roberto Max Protil, Brenno Tondato de Faria and Rodrigo Filev Maia
Agriculture 2024, 14(1), 134; https://doi.org/10.3390/agriculture14010134 - 16 Jan 2024
Viewed by 1205
Abstract
Agriculture is undergoing a profound change related to Agriculture 4.0 development and Precision Agriculture adoption, which is occurring at a slower pace than expected despite the abundant literature on the factors explaining this adoption. This work explores the factors related to agricultural Operations [...] Read more.
Agriculture is undergoing a profound change related to Agriculture 4.0 development and Precision Agriculture adoption, which is occurring at a slower pace than expected despite the abundant literature on the factors explaining this adoption. This work explores the factors related to agricultural Operations Management, farmer behavior, and the farmer mental model, topics little explored in the literature, by applying the Theory of Planned Behavior. Considering the exploratory nature of this work, an exploratory multi-method is applied, consisting of expert interviews, case studies, and modeling. This study’s contributions are a list of factors that can affect this adoption, which complements previous studies, theoretical propositions on the relationships between these factors and this adoption, and a model of irrigation Operations Management built based on these factors and these propositions. This model provides a theoretical framework to study the identified factors, the relationships between them, the theoretical propositions, and the adoption of Precision Agriculture. Furthermore, the results of case studies allow us to explore the relationships between adoption, educational level, and training. The identified factors and the model contribute to broadening the understanding of Precision Agriculture adoption, adding Operations Management and the farmer mental model to previous studies. A future research agenda is formulated to direct future studies. Full article
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20 pages, 6706 KiB  
Article
Post-Harvest Management of Immature (Green and Semi-Green) Soybeans: Effect of Drying and Storage Conditions (Temperature, Light, and Aeration) on Color and Oil Quality
by Ibukunoluwa Ajayi-Banji, Ewumbua Monono, Jasper Teboh, Szilvia Yuja and Kenneth Hellevang
AgriEngineering 2024, 6(1), 135-154; https://doi.org/10.3390/agriengineering6010009 - 15 Jan 2024
Viewed by 776
Abstract
Soybean downgrading due to immature (green and semi-green) color at harvest, caused by frost conditions, poses a significant loss to producers and processors. After harvest, drying and storage are important for preserving the quality of the harvested produce. This study investigated the impact [...] Read more.
Soybean downgrading due to immature (green and semi-green) color at harvest, caused by frost conditions, poses a significant loss to producers and processors. After harvest, drying and storage are important for preserving the quality of the harvested produce. This study investigated the impact of drying on color change in harvested immature soybeans and the effect of the soybean moisture content, storage environment (temperature, light, and aeration), and storage period on color change and oil quality of immature soybeans. Soybeans were harvested at three different maturity stages: R6 (green) and R7 (semi-green) in pods and R8 (fully matured) in seed. The soybeans in pods were dried, shelled, and conditioned to moisture contents of 12% and 17% (wet basis) prior to storage in 12 storage chamber (box) environments. The chambers were built to have four environments of “light” and “no light” with and without aeration and were stored at temperatures of either 4 °C or 23.5 °C for 24 weeks. Samples were taken every 2 weeks for 2 months and then bimonthly in storage. Soybean color change during drying and their chlorophyll, color, peroxide value (PV), and free fatty acid (FFA) status in storage were determined. Visual observation showed that R6 (green) soybean color faded after 48 h drying, which was supported with a colorimeter reading as the “a” value increased from −8.89 to −3.83 and −8.89 to −1.71 with 37 °C and 27 °C drying temperatures, respectively. The ANOVA analysis showed that light had the greatest contribution (~81%) to the color change compared to the other three storage environment factors of temperature (~9.1%), aeration (~8%), and moisture content (~1.5%) with <10% separate effects. During storage, the R6 green and R7 semi-green soybean color continued to fade with color a-values that exceeded the initial values of the R8 matured (control) by 353% and 350%, respectively, by the end of the storage period. Low amounts of peroxide and free fatty acids (FFA) were recorded throughout the storage period. Only the FFA of 17% M.C. soybeans stored at 23.5 °C exceeded acceptable limits at the end of the storage period. Exposing immature (green and semi-green) soybeans to light resulted in the fading of the green color. Seed producers in regions prone to frost can extend harvest time by allowing immature soybeans to field-dry. Full article
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18 pages, 866 KiB  
Article
The Influencing Factors Analysis of Aquaculture Mechanization Development in Liaoning, China
by Lixingbo Yu, Haiheng Wang, Anqi Ren, Fengfan Han, Fei Jia, Haochen Hou and Ying Liu
AgriEngineering 2024, 6(1), 34-51; https://doi.org/10.3390/agriengineering6010003 - 8 Jan 2024
Cited by 1 | Viewed by 1080
Abstract
Promoting the mechanization of aquaculture is one of the most important supporting measures to ensure the high-quality development of the aquaculture industry in China. In order to solve the problems of predominantly manual work and to decrease the costs of aquaculture, the influencing [...] Read more.
Promoting the mechanization of aquaculture is one of the most important supporting measures to ensure the high-quality development of the aquaculture industry in China. In order to solve the problems of predominantly manual work and to decrease the costs of aquaculture, the influencing factors of China’s aquaculture mechanization were systematically analyzed. The triple bottom theory was selected, and three aspects were identified, including environmental, economic, and social aspects. Through the literature review, the Delphi method, and the analytic hierarchy process, the comprehensive evaluation indicator system, including 18 influencing factors, was proposed. Moreover, the fuzzy comprehensive evaluation method was combined with the model to solve the evaluation results. A case study in Liaoning Province was offered and, according to the analysis results, the economic aspect at the first level was the most critical factor; the financial subsidy for the purchase of aquaculture machinery, the energy consumption of the machinery and equipment, and the promotion and use of aquaculture technology were the most important factors and had the greatest impact on the development of aquaculture mechanization in China. The effective implementation paths and countermeasures were proposed, such as the promotion of mechanized equipment and the enhancement of the machinery purchase subsidies, in order to provide an important decision-making basis for the improvement of the level of aquaculture mechanization. Full article
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11 pages, 4041 KiB  
Article
Modeling of Coffee Fruit: An Approach to Simulate the Effects of Compression
by Janielle Souza Pereira, Ricardo Rodrigues Magalhães, Fábio Lúcio Santos, Ednilton Tavares de Andrade and Leomar Santos Marques
AgriEngineering 2023, 5(4), 2303-2313; https://doi.org/10.3390/agriengineering5040141 - 1 Dec 2023
Viewed by 864
Abstract
The flavor, aroma, and color of coffee can be changed due to mechanical damage, reducing its quality. To measure the mechanical behavior of the fruit, compression tests can be performed at different stages of ripeness. In this study, we analyzed the deformation, strain [...] Read more.
The flavor, aroma, and color of coffee can be changed due to mechanical damage, reducing its quality. To measure the mechanical behavior of the fruit, compression tests can be performed at different stages of ripeness. In this study, we analyzed the deformation, strain energy, and von Mises stress of coffee fruits at mature, semi-mature, and immature stages under compression forces. Compression in three directions (x, y, and z) was simulated on coffee fruit models using the finite element method. A compression support was applied in the opposite direction to the force application axis. Numerical simulations of the compression process allowed us to verify that the more mature the fruit, greater the associated mean deformation (2.20 mm mm−1, 0.78 mm mm−1, and 0.88 mm mm−1), the lower the mean strain energy (0.07 mJ, 0.21 mJ, and 0.34 mJ), and the lower the mean equivalent von Mises stress (0.25 MPa, 1.03 MPa, and 1.25 MPa), corresponding to ripe, semi-ripe, and immature fruits, respectively. These analyses not only save time and professional resources but also offer insights into how strain energy and von Mises stress affect fruits at different maturation stages. This information can guide machine adjustments to reduce coffee harvesting damages. Full article
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15 pages, 1530 KiB  
Review
Bridging the Implementation Gap between Pomace Waste and Large-Scale Baker’s Yeast Production
by Josipa Lisičar Vukušić, Thomas Millenautzki and Stéphan Barbe
AgriEngineering 2023, 5(4), 2238-2252; https://doi.org/10.3390/agriengineering5040137 - 1 Dec 2023
Viewed by 1220
Abstract
The objectives set in the European Green Deal constitute the starting point of this review, which then focuses on the current implementation gap between agro-industrial wastes as resources for large-scale bioprocesses (e.g., baker’s yeast, bioethanol, citric acid, and amino acids). This review highlights [...] Read more.
The objectives set in the European Green Deal constitute the starting point of this review, which then focuses on the current implementation gap between agro-industrial wastes as resources for large-scale bioprocesses (e.g., baker’s yeast, bioethanol, citric acid, and amino acids). This review highlights the current lack of sustainability of the post-harvest processing of grapes and apples. In light of the European Green Deal, industrial biotechnology often lacks sustainability as well. We reviewed the recent progress reported in the literature to enhance the valorization of grape and apple pomace and the current failure to implement this research in technical processes. Nevertheless, selected recent papers show new perspectives to bridge this gap by establishing close collaborations between academic teams and industrial partners. As a final outcome, for the first time, we drew a circular flow diagram that connects agriculture post-harvest transformation with the industrial biotechnology and other industries through the substantial valorization of apple and grape pomace into renewable energy (solid biofuels) and sugar extracts as feedstock for large-scale bioprocesses (production of baker’s yeast industry, citric acid, bioethanol and amino acids). Finally, we discussed the requirements needed to achieve the successful bridging of the implementation gap between academic research and industrial innovation. Full article
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9 pages, 516 KiB  
Article
Calcium, Potassium, and Magnesium Affect the Nutritional Value of Tomato Grafted Fruits Grown in a Nutrient Film Technique System
by Rocío Maricela Peralta Manjarrez, Rafael Delgado Martínez, Adalberto Benavides Mendoza, Antonio Juárez Maldonado and Marcelino Cabrera De la Fuente
Agriculture 2023, 13(12), 2189; https://doi.org/10.3390/agriculture13122189 - 23 Nov 2023
Viewed by 1011
Abstract
Solanum lycopersicum is a vegetable with a high mineral, nutraceutical, and vitamin content. It is a basic ingredient in the human diet, and its use is diverse within the kitchen. Grafting and Ca, K, and Mg applications can be used to increase production [...] Read more.
Solanum lycopersicum is a vegetable with a high mineral, nutraceutical, and vitamin content. It is a basic ingredient in the human diet, and its use is diverse within the kitchen. Grafting and Ca, K, and Mg applications can be used to increase production and raise the mineral contents of tomato fruit. An experiment was established with tomato plants using the “CID F1” variety with the “FORTAMINO” rootstock, established in the NFT system, determining the influence on the agronomic yield and mineral composition of the fruit. Grafted and non-grafted plants were considered, with five concentrations (0-0-0, 9-0-0, 0-12-0, 0-0-9, and 9-12-9 mEq L−1) of Ca, K, and Mg, respectively. A highly significant difference was obtained in the grafted plants on high plants, number of leaves, number of fruits, polar diameters of fruits, equatorial diameters of fruits, and weight of fruits, with an increase in variables, FW 19% and NF 18%, and an improvement for the mineral composition in elements such as Ca 10%, P 1%, Mn 6%, Zn 7%, Cu 6%, Fe 64%, K 21%, and Mg 19%. The 9-12-9 meq formula improved Ca 6%, P 4%, Mn 12%, Zn 14%, Cu 8%, Fe 74%, and Mg 25%. The graft and the addition of calcium, potassium, and magnesium increased the mineral content in tomato fruits and improved the agronomic performance of the plants. Full article
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15 pages, 2463 KiB  
Review
Recent Progress on Catalytic of Rosin Esterification Using Different Agents of Reactant
by Mardiah Mardiah, Tjokorde Walmiki Samadhi, Winny Wulandari, Aqsha Aqsha, Yohanes Andre Situmorang and Antonius Indarto
AgriEngineering 2023, 5(4), 2155-2169; https://doi.org/10.3390/agriengineering5040132 - 9 Nov 2023
Viewed by 2187
Abstract
Gum rosin is an important agricultural commodity which is widely used as a raw material for various industries. However, gum rosin has low stability, crystallizes easily, and tends to oxidize. This is due to carboxyl groups and conjugated double bonds in gum rosin’s [...] Read more.
Gum rosin is an important agricultural commodity which is widely used as a raw material for various industries. However, gum rosin has low stability, crystallizes easily, and tends to oxidize. This is due to carboxyl groups and conjugated double bonds in gum rosin’s structure. Therefore, to reduce these weaknesses, it is necessary to modify the rosin compound to achieve better stability via the esterification process. This paper surveys esterification agents such as glycerol, pentaerythritol, methanol, ethylene glycol, polyethylene glycol (PEG), allyl group, and starch Rosin ester. The product is used in the manufacture of pressure-sensitive adhesives, drug delivery, solder flux for electronic devices, as a plasticizer, and as a coating agent in fertilizers. In general, the esterification reaction between alcohols and carboxylic acids is very slow without a catalyst. Heterogeneous catalysts have the advantage of controlling size, structure, spatial distribution, surface composition, thermal-chemical stability, and selectivity. Among the catalysts for gum rosin esterification are ZSM-5, Fe3O4, ZnO, Calcium, TiO2, Kaolin, and Al2O3, among others. Different catalysts and esterification agents can produce various physical and chemical properties of rosin ester and will result in specific rosin ester products, such as glycerol ester, pentaerythritol ester, methyl ester, glycol ester, allyl ester, and acid starch-based rosin. Full article
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11 pages, 2116 KiB  
Article
Optimization of Black Tea Drying Temperature in an Endless Chain Pressure (ECP) Dryer
by Gunaratnam Abhiram, Rasaiyah Diraj and Rasu Eeswaran
AgriEngineering 2023, 5(4), 1989-1999; https://doi.org/10.3390/agriengineering5040122 - 1 Nov 2023
Cited by 1 | Viewed by 1768
Abstract
Drying is a crucial and energy-consuming process in black tea manufacturing that is aimed at reducing moisture content and terminating enzymatic reactions in tea leaves. In Sri Lanka, an endless chain pressure (ECP) dryer is commonly used for drying, but it consumes a [...] Read more.
Drying is a crucial and energy-consuming process in black tea manufacturing that is aimed at reducing moisture content and terminating enzymatic reactions in tea leaves. In Sri Lanka, an endless chain pressure (ECP) dryer is commonly used for drying, but it consumes a significant amount of energy, necessitating the optimization of drying conditions. The current drying temperature at the Houpe tea factory in Ratnapura, Sri Lanka is 121 °C (250 °F), and it has not been optimized for a considerable period. As a result, energy consumption and wastage are high, leading to an inferior quality of black tea. To optimize factory conditions, tea leaves were dried under different temperatures: 115 (T1), 118 (T2), 121 (T3), 124 (T4), and 127 (T5) °C. Energy consumption, energy wastage, and specific energy consumption (SEC) for tea drying were calculated. Additionally, chemical and sensory analyses of samples of made tea were performed. SEC and energy wastage were significantly (p < 0.05) lower for treatments T1 and T2 than for other treatments. The theaflavin and thearubigin contents were significantly (p < 0.05) higher while total phenolic content was moderate for treatment T2. The sensory parameters of T2 outperformed other treatments. Based on these results, the optimum drying temperature for the ECP dryer was determined to be 118 °C and this temperature has been recommended for this factory. Full article
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16 pages, 4810 KiB  
Article
Evaluation of the Accuracy of the Remote Determination of the Brewster Angle When Measuring Physicochemical Parameters of Soil
by Gennadiy Ivanovich Linets, Anatoliy Vyacheslavovich Bazhenov, Sergey Vladimirovich Malygin, Natalia Vladimirovna Grivennaya, Sergey Vladimirovich Melnikov and Vladislav Dmitrievich Goncharov
AgriEngineering 2023, 5(4), 1893-1908; https://doi.org/10.3390/agriengineering5040116 - 19 Oct 2023
Viewed by 1208
Abstract
In precision farming technology, the moisture of the soil, its granulometric composition, specific conductivity and a number of other physical and chemical parameters are determined using remote radar sensing. The most important parameters are those measured in the area of the plant root [...] Read more.
In precision farming technology, the moisture of the soil, its granulometric composition, specific conductivity and a number of other physical and chemical parameters are determined using remote radar sensing. The most important parameters are those measured in the area of the plant root system located well below the “air-surface” boundary. In order to create conditions for the penetration of electromagnetic waves through the “air-surface” interface with a minimum reflection coefficient, the irradiation of the Earth’s surface is carried out obliquely with an angle of incidence close to the Brewster angle. The reflection coefficient, and, consequently, the Brewster angle, depend on the complex dielectric permittivity of the surface soil layer and are not known a priori. To determine the Brewster angle, the usual method is to search for the minimum amplitude of the vertically polarized signal reflected from the surface. Another approach is when the first derivative of the dependence of the modulus of the complex amplitude of a vertically polarized interference wave, taken with respect to the angle of incidence, is set equal to zero. In turn, in real dielectrics such as agricultural soils, the amplitude of the vertically polarized signal reflected from the surface is directly proportional to the reflection coefficient and does not have a pronounced minimum, which reduces the accuracy of the measurements. Based on the solution of the Helmholtz wave equation for a three-layered structure of the propagation medium (air, upper fertile soil layer, soil layer below the groundwater level), a model of the process of forming an interference wave under oblique irradiation of a planar layered dielectric with losses has been developed. Using the developed model, factors influencing the accuracy of determining the Brewster angle have been identified. For the first time, it is proposed to use the phase shift between the oscillations of the interference waves with vertical and horizontal polarization to measure the Brewster angle. A comparative assessment of the accuracy of determining the Brewster angle using known amplitude methods and the proposed phase method has been carried out. The adequacy of the method was experimentally confirmed. Recommendations have been developed for the practical application of the phase method of finding the Brewster angle for assessing the dielectric permittivity of soil and its moisture content. Full article
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14 pages, 5150 KiB  
Article
Performance Evaluation of a Wet Medium Made of Mangosteen Peels for a Direct Evaporative Cooling System
by Nattawut Chaomuang, Thanut Nuangjamnong and Samak Rakmae
AgriEngineering 2023, 5(4), 1865-1878; https://doi.org/10.3390/agriengineering5040114 - 12 Oct 2023
Cited by 1 | Viewed by 1187
Abstract
The present study aimed to investigate an alternative evaporative cooling pad material made from mangosteen peel (MP) waste. Mangosteen peels were used to fill a 150 mm thick mesh container with a packing density of 180 kg/m3. A wind tunnel was [...] Read more.
The present study aimed to investigate an alternative evaporative cooling pad material made from mangosteen peel (MP) waste. Mangosteen peels were used to fill a 150 mm thick mesh container with a packing density of 180 kg/m3. A wind tunnel was constructed and utilized to experimentally evaluate the cooling performance of this organic-waste-based pad under hot and humid conditions (31–34 °C and 55–70% RH). The performance parameters assessed included pressure drop, temperature drop, saturation effectiveness, cooling capacity, and coefficient of performance (COP). The influence of air velocity (0.7, 1.0, 1.4, and 1.8 m/s) on these parameters was also examined. The results revealed that the saturation effectiveness of the MP pad ranged from 53% to 77% within the considered air velocity range. The maximum temperature drop (4.6 °C), saturation effectiveness (77%), cooling capacity (0.6 kW), and COP (3.5) were achieved when the system operated at 1.4 m/s. A comparative study showed that, at this velocity, the MP pad provided performance nearly equivalent to that of the commercial cellulose paper pad, except for the pressure drop. This result affirms the potential of mangosteen peels as a suitable wet medium for evaporative cooling applications. Full article
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17 pages, 4854 KiB  
Article
Chicken Tracking and Individual Bird Activity Monitoring Using the BoT-SORT Algorithm
by Allan Lincoln Rodrigues Siriani, Isabelly Beatriz de Carvalho Miranda, Saman Abdanan Mehdizadeh and Danilo Florentino Pereira
AgriEngineering 2023, 5(4), 1677-1693; https://doi.org/10.3390/agriengineering5040104 - 29 Sep 2023
Cited by 2 | Viewed by 2067
Abstract
The analysis of chicken movement on the farm has several applications in evaluating the well-being and health of birds. Low locomotion may be associated with locomotor problems, and undesirable bird movement patterns may be related to environmental discomfort or fear. Our objective was [...] Read more.
The analysis of chicken movement on the farm has several applications in evaluating the well-being and health of birds. Low locomotion may be associated with locomotor problems, and undesirable bird movement patterns may be related to environmental discomfort or fear. Our objective was to test the BoT-SORT object tracking architecture embedded in Yolo v8 to monitor the movement of cage-free chickens and extract measures to classify running, exploring, and resting behaviors, the latter of which includes all other behaviors that do not involve displacement. We trained a new model with a dataset of 3623 images obtained with a camera installed on the ceiling (top images) from an experiment with layers raised cage-free in small-scale aviaries and housed in groups of 20 individuals. The model presented a mAP of 98.5%, being efficient in detecting and tracking the chickens in the video. From the tracking, it was possible to record the movements and directions of individual birds, and we later classified the movement. The results obtained for a group of 20 chickens demonstrated that approximately 84% of the time, the birds remained resting, 10% of the time exploring, and 6% of the time running. The BoT-SORT algorithm was efficient in maintaining the identification of the chickens, and our tracking algorithm was efficient in classifying the movement, allowing us to quantify the time of each movement class. Our algorithm and the measurements we extract to classify bird movements can be used to assess the welfare and health of chickens and contribute to establishing standards for comparisons between individuals and groups raised in different environmental conditions. Full article
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20 pages, 7368 KiB  
Article
Analyzing Extreme Temperature Patterns in Subtropical Highlands Climates: Implications for Disaster Risk Reduction Strategies
by Abdulnoor A. J. Ghanim, Muhammad Naveed Anjum, Ghulam Rasool, Saifullah, Muhammad Irfan, Mana Alyami, Saifur Rahman and Usama Muhammad Niazi
Sustainability 2023, 15(17), 12753; https://doi.org/10.3390/su151712753 - 23 Aug 2023
Viewed by 855
Abstract
This study utilized hot and cold indices to evaluate the changes in extreme temperature events that occurred in subtropical highland climates from 1991 to 2020. The modified Mann–Kendall (MMK) test and the Theil–Sen (TS) slope estimator were used to analyze the linear trends [...] Read more.
This study utilized hot and cold indices to evaluate the changes in extreme temperature events that occurred in subtropical highland climates from 1991 to 2020. The modified Mann–Kendall (MMK) test and the Theil–Sen (TS) slope estimator were used to analyze the linear trends in the time series of the extreme temperature indices. The northern highlands of Pakistan (NHP) were considered as a case study region. The results showed that the annual maximum temperature had a slightly increasing tendency (at the rate of 0.14 °C/decade), while the annual minimum temperature had a slightly decreasing tendency (at the rate of −0.02 °C/decade). However, these trends were not significant at the 5% significance level. The decadal averages of the hot indices were the highest in the second decade (2000s), while they were the lowest in the subsequent decade (2010s). In comparison, all the cold indices except the annual minimum value of the maximum temperature (TXn) showed a persistent decline in their decadal averages throughout the 2000s and 2010s. Overall, the frequency of hot days significantly increased in the NHP during the study period. This study found that the hot days and coldest days increased over the past three decades in the NHP. However, there was a decreasing trend in the cold spell duration, cold nights, and the coldest nights over the past three decades, as demonstrated by the trends of the cold spell duration index (CSDI), the temperature of cold nights (TN10p), and the annual minimum value of the minimum temperature (TNn) indices. These changes may impact the environment, human health, and agricultural operations. The findings provide useful insights into the shifting patterns of extreme temperature events in northern Pakistan and have crucial implications for the climate-change-adaptation and resilience-building initiatives being undertaken in the region. It is suggested that the continuous monitoring of extreme temperature events is necessary to comprehend their effects on the region and devise strategies for sustainable development. Full article
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17 pages, 4565 KiB  
Article
Ventilation Operating Standard for Improving Internal Environment in Pig House Grafting Working Conditions Using CFD
by Byung-Wook Oh, Hyo-Jae Seo and Il-Hwan Seo
AgriEngineering 2023, 5(3), 1378-1394; https://doi.org/10.3390/agriengineering5030086 - 14 Aug 2023
Viewed by 1607
Abstract
Many farms utilize closed-type livestock systems to enhance productivity and facilitate effective environmental management. However, the confined nature of these closed spaces poses an increased risk of exposure to harmful gases and organic dust for both workers and livestock. Additionally, the introduction of [...] Read more.
Many farms utilize closed-type livestock systems to enhance productivity and facilitate effective environmental management. However, the confined nature of these closed spaces poses an increased risk of exposure to harmful gases and organic dust for both workers and livestock. Additionally, the introduction of outside air through ventilation systems can lead to temperature fluctuations within the breeding environment, resulting in potential productivity issues. This research paper employs computational fluid dynamics (CFD) to develop ventilation operation management plans that address both the working environment and the breeding environment simultaneously. The proposed plans are designed to be easily implemented in practical farm settings. The findings of this study, based on the simulation analysis, indicate that while ventilation is effective in reducing harmful gases and improving the working environment, its efficiency decreases after the initial 3 min of operation. Furthermore, uncontrolled ventilation can cause sudden temperature changes, which may adversely affect the well-being of the livestock. However, when upgraded ventilation structures are implemented, significant improvements in the working environment (an average of 27.3% improvement) can be achieved while maintaining temperature stability for the livestock. These results highlight the importance of referring to the provided ventilation operation management table before commencing work, as it enables workers to improve the working environment while minimizing the potential impact of ventilation on the breeding environment. Full article
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15 pages, 3658 KiB  
Article
Identifying the Role of Biostimulants in Turnip (Brassica rapa L.) Production Compared with Chemical Fertilization
by Qurat-Ul-Ain Raza, Muhammad Amjad Bashir, Abdur Rehim, Yucong Geng, Hafiz Muhammad Ali Raza, Sajjad Hussain, Ijaz Ahmad and Muhammad Wasif
Sustainability 2023, 15(15), 11851; https://doi.org/10.3390/su151511851 - 1 Aug 2023
Cited by 1 | Viewed by 1100
Abstract
Chemical fertilizers play an integral role in advancing food production to combat the increasing food challenges and ensure food security. Unfortunately, the overuse of these fertilizers has negatively influenced the soil and the environment. Considering this aspect, two pot experiments were performed to [...] Read more.
Chemical fertilizers play an integral role in advancing food production to combat the increasing food challenges and ensure food security. Unfortunately, the overuse of these fertilizers has negatively influenced the soil and the environment. Considering this aspect, two pot experiments were performed to evaluate the efficacy of biostimulants in vegetable production systems. The first experiment compared the effects of chemical fertilizers (CF) with glycine (GL), aspartic acid (AA), lysine (LY), and vitamin B complex (VB). The plant’s physiological and morphological attributes and yield were studied. The results confirmed that VB has the potential to improve the rate of transpiration (26%), total chlorophyll content (27%), root diameter (213%), and dry matter (289%) compared with CF. In the second experiment, the effects of chemical fertilizers (CF) were compared with Isabion® (I), 25% CF + GL + LY (B1), 25% CF + GL + AA (B2), and 25% CF + AA + LY (B3). Similar attributes were analyzed to identify the influence of the applied treatments on turnip production. The results demonstrated that B2 enhanced the rate of photosynthesis (963%), transpiration (254%), and stomatal conductance (76%). Moreover, B1 improved the plant’s fresh weight (6%) and moisture contents (4%) compared to CF. In conclusion, biostimulants (LY, VB, and B1) are capable of improving turnip performance and production compared to CF. Future studies must focus on the efficiency of biostimulants against the long-term application effects on soils, nutrient-use efficiency, and crop production. Furthermore, the mechanism of action needs to be addressed in the future. Full article
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13 pages, 1417 KiB  
Technical Note
Milking Machine Settings and Liner Design Are Important to Improve Milking Efficiency and Lactating Animal Welfare—Technical Note
by Shehadeh Kaskous and Michael W. Pfaffl
AgriEngineering 2023, 5(3), 1314-1326; https://doi.org/10.3390/agriengineering5030083 - 28 Jul 2023
Cited by 2 | Viewed by 2898
Abstract
The purpose of milking machines is to harvest milk at optimal quality and speed, while maintaining animal comfort and teat defense mechanisms against invading mastitis pathogens. Therefore, the milking machine is a very important piece of equipment on dairy farms to maintain a [...] Read more.
The purpose of milking machines is to harvest milk at optimal quality and speed, while maintaining animal comfort and teat defense mechanisms against invading mastitis pathogens. Therefore, the milking machine is a very important piece of equipment on dairy farms to maintain a long healthy lactation by following the physiological conditions of the udder. The mechanical forces during long-term machine milking processes lead to changes in the teat tissue. This effect is related to the degree of adaptation of the milking machines to the physiological requirements of the individual udder anatomy and the physiological conditions of the lactating animals. If both, milking machine settings and liner design are not suitable for all teats and animals on the farm, some animals will not be fully milked, the teat condition will deteriorate over time and in the end, they may suffer from mastitis. Therefore, maintaining healthy udders and teats during milking is a central key component of an effective milking machine to produce good milk yield with higher quality by preventing mastitis and maintaining animal health and welfare. On large and thick teats, conventional liners often fit too tight, causing a massive mechanical stress load on the tissue. On small teats, however, they often do not adhere sufficiently close to the teat which can cause a considerable air admission and hence liner slips. The new liners, “Stimulor® StressLess” (Siliconform, Türkheim, Germany), have a wave-like lip construction and adapt well to the different teat sizes in a herd, thus ensuring consistent milking of lactating animals. A proper milking machine accommodates all teat sizes and forms, has a low vacuum to effectively open the teat and to stimulate physiological milk release and letdown. In addition, the right pulsation rate will maintain a stable vacuum on the teat area during milking. In conclusion, an ideal milking machine adapts to the morphological, anatomical, and physiological characteristics of the udder and teats of the lactating animals and it should achieve a physiologically ideal milking process that meets high animal welfare standards and increases milk production with a high quality standard. Full article
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18 pages, 2821 KiB  
Review
Analysis of Hotspots in Subsurface Drip Irrigation Research Using CiteSpace
by Yatao Xiao, Chaoxiang Sun, Dezhe Wang, Huiqin Li and Wei Guo
Agriculture 2023, 13(7), 1463; https://doi.org/10.3390/agriculture13071463 - 24 Jul 2023
Cited by 1 | Viewed by 2091
Abstract
To investigate the research hotspots and development trends of subsurface drip irrigation (SDI) over the past 20 years, this study analyzed relevant literature from the Web of Science Core Collection spanning from 2002 to 2022. The data were visualized using CiteSpace, showcasing the [...] Read more.
To investigate the research hotspots and development trends of subsurface drip irrigation (SDI) over the past 20 years, this study analyzed relevant literature from the Web of Science Core Collection spanning from 2002 to 2022. The data were visualized using CiteSpace, showcasing the publication volume trends, countries, keywords, cited references, authors, and affiliated institutions. Based on 1079 articles, the annual publication volume showed an overall upward trend. The United States had the most extensive research coverage and highest publication volume, whereas China had the fastest growing publication rate in recent years. However, relatively little cooperation occurred among research teams and institutions. Over time, research topics became increasingly diverse, with water conservation and yield increases being the primary research objectives. In addition to improving irrigation and fertilizer use efficiency, SDI has also been applied in research on the safe utilization of unconventional water resources (wastewater and salt water) and the optimization of soil conditions. Among these, aerated irrigation technology—aimed at improving root growth in the rhizosphere—may become a new branch of SDI research. Currently, the main research focus in the field of SDI is the diffusion and distribution of water in the crop root zone, for which Hydrus model simulation is a particularly important method. Full article
(This article belongs to the Topic Emerging Agricultural Engineering Sciences, Technologies, and Applications)
(This article belongs to the Section Agricultural Water Management)
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17 pages, 2606 KiB  
Article
Opportunities of Digital Transformation in Post-Harvest Activities: A Single Case Study of an Engineering Solutions Provider
by Daniel Schmidt, Maria Angela Butturi and Miguel Afonso Sellitto
AgriEngineering 2023, 5(3), 1226-1242; https://doi.org/10.3390/agriengineering5030078 - 12 Jul 2023
Cited by 1 | Viewed by 2788
Abstract
The purpose of this article is to identify opportunities that digital transformation in post-harvest activities offers to an engineering solution provider. The research method is a simple case study. The object is a company based in southern Brazil that provides engineering-integrated digital solutions [...] Read more.
The purpose of this article is to identify opportunities that digital transformation in post-harvest activities offers to an engineering solution provider. The research method is a simple case study. The object is a company based in southern Brazil that provides engineering-integrated digital solutions to grain producers, including products and services. The specific objectives are to describe the company’s digital products and services, identify opportunities and players, and discuss how players can take advantage of opportunities owing to business process digitalization. The main results include separating products into three technological layers and identifying five types of opportunities (financing, commercialization, operation, logistics, traceability, and insurance), eight types of players, and the main opportunities for each player. The most significant opportunities are risk reduction in insurance contracts, improvement in grain quality, increments in food safety, and accurate information on grain movements. The main implication of the study is that grain producers and other players can explore opportunities, and solution providers can evolve toward complete digitalization by integrating service into the current offerings of post-harvest engineering solutions. Full article
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19 pages, 18436 KiB  
Article
Spatiotemporal Estimation of Reference Evapotranspiration for Agricultural Applications in Punjab, Pakistan
by Hadeed Ashraf, Saliha Qamar, Nadia Riaz, Redmond R. Shamshiri, Muhammad Sultan, Bareerah Khalid, Sobhy M. Ibrahim, Muhammad Imran and Muhammad Usman Khan
Agriculture 2023, 13(7), 1388; https://doi.org/10.3390/agriculture13071388 - 12 Jul 2023
Cited by 1 | Viewed by 1675
Abstract
Estimation of reference evapotranspiration (ETo) is a key element in water resources management and crop water requirement which, in turn, affects irrigation scheduling. ETo is subject to the influence of various climatic parameters including minimum temperature (Tmin), maximum [...] Read more.
Estimation of reference evapotranspiration (ETo) is a key element in water resources management and crop water requirement which, in turn, affects irrigation scheduling. ETo is subject to the influence of various climatic parameters including minimum temperature (Tmin), maximum temperature (Tmax), relative humidity (RH), windspeed (WS), and sunshine hours (SH). Usually, the influence of the climatic parameters and a dominating climatic factor influencing ETo is estimated on yearly basis. However, in diverse climatic regions, ETo varies with the varying climate. Therefore, this study aims to estimate the spatiotemporal variation in the influence of the climatic parameters on ETo in Punjab, Pakistan, for the period 1950–2021, specifically focusing on decennial, annual, and monthly patterns. The study area was divided into five agroclimatic zones. The Penman–Monteith model was used to estimate ETo. The influence was assessed using geographic weighted regression (GWR) and multiscale geographic weighted regression (MGWR) as the primary methods. As per results from MGWR, ETo in Punjab was highly influenced by the Tmin, Tmax, and WS. Additionally, annual ETo exhibited a higher value in southern Punjab in comparison to northern Punjab, with a range of 2975 mm/year in the cotton–wheat zone to 1596 mm/year in the rain-fed zone. Over the course of the past seventy years, Punjab experienced an average increasing slope of 5.18 mm/year in ETo. Tmin was the highest monthly dominant factor throughout the year, whereas WS and SH were recorded to be the dominant factor in the winters, specifically. All in all, accurate estimation of ETo, which serves as an essential component for crop water requirement, could potentially help improve the irrigation scheduling of crops in the agroclimatic zones. Full article
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14 pages, 3551 KiB  
Article
Evaluation of Body Surface Temperature in Pigs Using Geostatistics
by Maria de Fátima Araújo Alves, Héliton Pandorfi, Abelardo Antônio de Assunção Montenegro, Rodes Angelo Batista da Silva, Nicoly Farias Gomes, Taize Calvacante Santana, Gledson Luiz Pontes de Almeida, Gabriel Thales Barboza Marinho, Marcos Vinícius da Silva and Weslley Amaro da Silva
AgriEngineering 2023, 5(2), 1090-1103; https://doi.org/10.3390/agriengineering5020069 - 19 Jun 2023
Viewed by 2152
Abstract
This paper explores the potential of infrared thermography and geostatistics in animal production and presents the results of the application of the combination of these techniques, contributing significantly to efforts to obtain animals’ responses to the environments in which they are located and [...] Read more.
This paper explores the potential of infrared thermography and geostatistics in animal production and presents the results of the application of the combination of these techniques, contributing significantly to efforts to obtain animals’ responses to the environments in which they are located and thereby ensuring improvements in productivity and animal welfare. The objective was to verify the variability in surface temperature in pigs submitted to different climate control systems using geostatistics. Three growing animals per stall were selected. Dry bulb temperature (Tbd, °C), relative humidity (RH, %) and thermal images were recorded at 08:00 and 12:00 h. To analyze the data, semivariograms were made, the theoretical model was validated and kriging maps were constructed. The mean temperature of the pigs in the pen with adiabatic evaporative cooling (AEC) ranged from 32.40 to 36.25 °C; for the pigs in the forced ventilation (FV) pen, the range of variation was from 32.51 to 36.81 °C. In the control group (Con), with natural ventilation, the average temperature was 37.51 to 38.45 °C. The geostatistical analysis provided a mathematical model capable of illustrating the variation in temperature in the caudal–dorsal regions of the pigs according to the environments to which the animals were subjected. Full article
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18 pages, 1566 KiB  
Article
Wheat Straw Biochar Produced at a Low Temperature Enhanced Maize Growth and Yield by Influencing Soil Properties of Typic calciargid
by Muhammad Aon, Zeshan Aslam, Shahid Hussain, Muhammad Amjad Bashir, Muhammad Shaaban, Sajid Masood, Sidra Iqbal, Muhammad Khalid, Abdur Rehim, Walid F. A. Mosa, Lidia Sas-Paszt, Samy A. Marey and Ashraf Atef Hatamleh
Sustainability 2023, 15(12), 9488; https://doi.org/10.3390/su15129488 - 13 Jun 2023
Cited by 7 | Viewed by 1456
Abstract
Arid and semi-arid soils are low in organic matter and have poor fertility, making them a serious threat to crop production. Most organic amendments, such as crop residues and farmyard manure, are short lived because of rapid decomposition. Incubation and pot studies were [...] Read more.
Arid and semi-arid soils are low in organic matter and have poor fertility, making them a serious threat to crop production. Most organic amendments, such as crop residues and farmyard manure, are short lived because of rapid decomposition. Incubation and pot studies were conducted to assess the impact of wheat straw biochar (produced at 350 °C) on temporal changes in soil microbial biomass and fertility status and to evaluate the efficacy of biochar for maize production in the top layer of Typic calciargid. The incubation study compared four levels of biochar (control, 0.5, 1.0 and 2.0% on a w/w basis of soil) and two fertilizer rates, i.e., unfertilized (no NPK fertilizer) and fertilized (nitrogen, P2O5 and K2O with rates of 125, 80 and 52.5 mg kg−1 soil, respectively). After incubation, the 2.0% biochar significantly improved the soil cation exchange capacity, organic carbon and microbial biomass carbon by up to 35, 59 and 26%, respectively, while decreasing the soil pH by up to 1.5% compared to that of the control treatment. When fertilized, the 2.0% biochar improved the soil’s available phosphorous, extractable potassium and total nitrogen by up to 59, 39 and 28%, respectively, compared to those of the control. The results from the pot experiment showed that using the 1% biochar with fertilizer significantly increased the maize dry biomass and grain yield by up to 57 and 72%, respectively, compared to those of the control. Additionally, the nitrogen and phosphorus recoveries from the mineral fertilizers improved significantly (up to 26 and 38%, respectively) when using the 1.0% biochar compared to those of the control. Conclusively, the addition of 1.0% biochar significantly improved maize growth and yield by enhancing nutrient recovery from mineral fertilizer and improving soil properties. Full article
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27 pages, 2068 KiB  
Review
Mitigating the Impacts of the COVID-19 Pandemic on Crop Farming: A Nanotechnological Approach
by Fadekemi O. Akinhanmi, Opeyemi I. Ayanda, Eze F. Ahuekwe and Gabriel A. Dedeke
Agriculture 2023, 13(6), 1144; https://doi.org/10.3390/agriculture13061144 - 29 May 2023
Cited by 2 | Viewed by 2289
Abstract
COVID-19 is a highly infectious respiratory disease that resulted in a global pandemic that has affected every stage and sector of life. Although it is mainly seen as a health issue, its impacts and ripple effects also resonated in the education, technology, agriculture, [...] Read more.
COVID-19 is a highly infectious respiratory disease that resulted in a global pandemic that has affected every stage and sector of life. Although it is mainly seen as a health issue, its impacts and ripple effects also resonated in the education, technology, agriculture, and research fields, creating socio-economic disruptions across the globe. In a bid to curb the wide spread of the disease, diverse sudden restriction measures were adopted, which had implications on food security and food availability via supply shortages and agricultural disruptions. Scientific studies such as those regarding nanotechnological developments, which had been underway for improving food quality and crop improvement, were also slowed down due to the complexities of the pandemic and global restrictions. Nanotechnology is a developing and promising field for further development of crop productivity by enhancing the proficiency of agricultural resources, thereby increasing food yield and food security. The application of nanotechnology crop farming involves the use of nano-scale materials that can be formulated into nano-emulsion, nano-capsule, nano-fertilizer, nano-pesticide, and nano-biosensor applications for improved agricultural productivity. In as much as the challenges of nanotoxicity could raise health and environmental concerns, advances in the biosynthesis of nanomaterials potentially allay such fears and concerns. Furthermore, these ideas will help in bridging the gap created by the pandemic on food availability, food security, and agriculture. This review focuses on the implications of the COVID-19 pandemic on nanotechnological applications for improved crop productivity and nanotechnological mitigation strategies on the impacts of the COVID-19 pandemic, risk assessment, and regulatory issues surrounding nano-crop farming, and this study provides an insight into future research directions for nanotechnological improvements in crop farming and the sustainable development of nano-enabled agriculture. Full article
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14 pages, 4108 KiB  
Article
Investigating the Potential of Cosmic-Ray Neutron Sensing for Estimating Soil Water Content in Farmland and Mountainous Areas
by Yifei Jiang, Kefan Xuan, Chen Gao, Yiren Liu, Yuan Zhao, Haodong Deng, Xiaopeng Li and Jianli Liu
Water 2023, 15(8), 1500; https://doi.org/10.3390/w15081500 - 12 Apr 2023
Viewed by 1794
Abstract
The conventional methods of estimating soil water content (SWC) are mainly based on in situ measurements at sampling points and remote sensing measurements over an entire region. In view of these methods, cosmic-ray neutron sensing (CRNS) has received increasing attention in recent years [...] Read more.
The conventional methods of estimating soil water content (SWC) are mainly based on in situ measurements at sampling points and remote sensing measurements over an entire region. In view of these methods, cosmic-ray neutron sensing (CRNS) has received increasing attention in recent years as a mesoscale, noncontact SWC estimation technology that can provide more accurate and timely estimates of SWC over a larger area. In this study, we estimated SWC using both CRNS and soil-mounted detectors in farmland and mountainous areas, and evaluated the accuracy of the estimations at two experimental sites. Ultra-rapid adaptable neutron-only simulation (URANOS) was used to simulate the detection radius and depth of the two experimental sites and to obtain the spatial weights of the CRNS footprint. The results show that the theoretical range of detection was reduced in farmland compared to mountainous areas during the experimental period, suggesting that farmland retained more SWC even with less precipitation. Spatial weights were simulated to calculate the SWC of sampling points, and the weighted and averaged SWC were then correlated with CRNS. The weighting calculation improves the accuracy of CRNS estimations, with a determination coefficient (R2) of 0.645 and a root mean square error (RMSE) of 0.046 cm3·cm−3 for farmland, and reproduces the daily dynamics of SWC. The R2 and RMSE in mountainous areas are 0.773 and 0.049 cm3·cm−3, respectively, and the estimation accuracy of CRNS cannot be improved by the weighting calculation. The estimation accuracy of CRNS is acceptable in both regions, but the mountainous terrain obstructs neutron transmission, causing a deviation between the actual and theoretical neutron footprints in mountainous areas. Thus, the accuracy of SWC estimation is limited in mountainous terrain. In conclusion, this study demonstrates that CRNS is suitable for use in farmland and mountainous areas and that further attention should be given to the effects of topography and vegetation when it is applied in mountainous environments. Full article
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18 pages, 1967 KiB  
Review
The Significance and Ethics of Digital Livestock Farming
by Suresh Neethirajan
AgriEngineering 2023, 5(1), 488-505; https://doi.org/10.3390/agriengineering5010032 - 26 Feb 2023
Cited by 17 | Viewed by 7006
Abstract
The emergence of precision and digital livestock farming presents an opportunity for sustainable animal farming practices that enhance animal welfare and health. However, this transformation of modern animal farming through digital technology has several implications for the technological, social, economic, and environmental aspects [...] Read more.
The emergence of precision and digital livestock farming presents an opportunity for sustainable animal farming practices that enhance animal welfare and health. However, this transformation of modern animal farming through digital technology has several implications for the technological, social, economic, and environmental aspects of farming. It is crucial to analyze the ethical considerations associated with the digitalization of modern animal farming, particularly in the context of human–animal relationships and potential objectification. This analysis can help develop frameworks for improving animal welfare and promoting sustainability in animal farming. One of the primary ethical concerns of digital livestock farming is the potential for a digital divide between farmers who have access to advanced technologies and those who do not. This could lead to a disparity in animal welfare and health outcomes for different groups of animals. Additionally, the use of artificial intelligence in digital livestock farming may lead to a loss of personal connection between farmers and animals, which could impact the animal’s well-being. Another ethical concern of digital livestock farming is the potential for the objectification of animals as mere data points. The use of sensors and other monitoring technologies can provide valuable data on animal health and behavior, but it is important to remember that animals are sentient beings with complex emotional and social needs. The use of digital technologies should not lead to neglect of animal welfare or a lack of human responsibility toward animals. Furthermore, social context becomes essential while integrating technologies in livestock farming to overcome ethics. By considering the cultural and societal norms of different communities, we can ensure that the use of digital technologies does not undermine these values. To address these ethical challenges, the development of standards and codes of conduct for the adoption and implementation of digital livestock farming tools and platforms can help ensure that animal welfare and sustainability are prioritized. This can help alleviate the privacy concerns of stakeholders and improve sustainability in animal farming practices. Additionally, the use of virtual and augmented reality technologies can provide a way to enhance human–animal interactions and provide more personalized care to animals, further promoting animal welfare. Full article
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12 pages, 1699 KiB  
Article
Determining the Influence of a Magnetic Field on the Vibration and Fuel Consumption of a Heavy Diesel Engine
by Yousef Darvishi, Seyed Reza Hassan-Beygi, Jafar Massah, Marek Gancarz, Arkadiusz Bieszczad and Hamed Karami
Sustainability 2023, 15(5), 4088; https://doi.org/10.3390/su15054088 - 23 Feb 2023
Cited by 1 | Viewed by 1617
Abstract
Most of the fuels used in internal combustion engines are liquid fuels. The magnetic behavior of fuel leads to a change in the interaction of hydrocarbon and oxygen molecules. This study aimed to evaluate the fuel consumption and engine vibration (time domain) of [...] Read more.
Most of the fuels used in internal combustion engines are liquid fuels. The magnetic behavior of fuel leads to a change in the interaction of hydrocarbon and oxygen molecules. This study aimed to evaluate the fuel consumption and engine vibration (time domain) of the Perkins A63544 diesel engine using magnetized fuel. The vibration of an internal combustion engine can cause failure in engine components and discomfort and injury to users. Engine vibration behavior changes due to changes in fuel types and engine combustion. Therefore, in this study, the vibration behavior of the tractor engine (Perkins model, four-stroke, direct injection diesel) was evaluated in stationary mode at different engine speeds due to changes in fuel types. Three accelerometers (CTC AC102 model) were used to measure the vibration acceleration. The fuels used included diesel as a normal control and fuels that had been subjected to magnetic field intensities of 1000, 2000, 3000, and 4000 gauss. The longitudinal, vertical, and lateral vibration signals with 5 levels of engine speed were measured. The results illustrated that the vibration root mean square (RMS) values were essentially (p < 0.01) affected by the engine speed, fuel type, and their interactions. It was found that for the 4000-gauss magnetized fuel, the average vibration acceleration using the five velocity settings reduced by 15%, 15.30%, 12.40%, 12.35%, and 15.38% compared to the respective control fuels. The results showed that engine fuel consumption and specific fuel consumption decreased by 2.3% using the 4000-gauss magnetized fuel compared with the normal control fuel. Full article
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19 pages, 5739 KiB  
Article
The Next Generation of Cotton Defoliation Sprayer
by Jyoti Neupane, Joe Mari Maja, Gilbert Miller, Michael Marshall, Matthew Cutulle, Jeremy Greene, Jun Luo and Edward Barnes
AgriEngineering 2023, 5(1), 441-459; https://doi.org/10.3390/agriengineering5010029 - 22 Feb 2023
Cited by 4 | Viewed by 2682
Abstract
Chemical spraying is one of the most important and frequently performed intercultural agricultural operations. It is imperative to select the appropriate spraying technology as a selection of ineffective one leads to the wastage of a considerable volume of applied chemicals to the non-target [...] Read more.
Chemical spraying is one of the most important and frequently performed intercultural agricultural operations. It is imperative to select the appropriate spraying technology as a selection of ineffective one leads to the wastage of a considerable volume of applied chemicals to the non-target area. Many precision technologies have been developed in the past few decades, such as image processing based on real-time variable-rate chemical spraying systems, autonomous chemical sprayers using machine vision and nozzle control, and use of unmanned aerial and ground vehicles. Cotton defoliation is a natural physiological process, but untimely and inadequate leaf defoliation by natural process hinders the mechanical cotton harvest. Induced defoliation is practiced by applying defoliants to address the issue with the natural process of defoliation. This paper covers spraying technologies in agriculture, cotton plants, cotton defoliation, new defoliant spraying systems, and the recent field test. The new spraying system attached to an autonomous mobile robot aims to improve the delivery of defoliant chemicals by adding a spray unit on the side of the plant. Preliminary results of the water-sensitive paper test at the field showed adequate penetration with low flow rates. This is a huge development as there is a huge potential to save on the cost of applying defoliant chemicals. Full article
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21 pages, 5130 KiB  
Article
Engineering Design, Kinematic and Dynamic Analysis of High Lugs Rigid Driving Wheel, a Traction Device for Conventional Agricultural Wheeled Tractors
by Hafiz Md-Tahir, Jumin Zhang, Yong Zhou, Muhammad Sultan, Fiaz Ahmad, Jun Du, Amman Ullah, Zawar Hussain and Junfang Xia
Agriculture 2023, 13(2), 493; https://doi.org/10.3390/agriculture13020493 - 19 Feb 2023
Cited by 1 | Viewed by 2692
Abstract
Traction failure on loose terrain is common in conventional agricultural wheeled tractors due to poor traction ability and lower power transfer efficiency of drive wheels, which leads to excessive energy consumption and soil compaction in agriculture. To overcome the problem, this paper presents [...] Read more.
Traction failure on loose terrain is common in conventional agricultural wheeled tractors due to poor traction ability and lower power transfer efficiency of drive wheels, which leads to excessive energy consumption and soil compaction in agriculture. To overcome the problem, this paper presents a new design of a rigid lugged wheel for use in field tillage operations. This wheel was designed according to field operational requirements and also provided with rubber pads for smooth on-road drives. Kinematic and dynamic analysis of new wheel designs were carried out to study how they move, how they interact with the soil, and how they generate drive force in loose terrain soil. The relationship of wheel lug motion trajectories, displacement, and velocity of the wheel relative to field conditions, different travel reduction rates, and lug penetration/wheel sinkage were analyzed. Wheel-terrain interaction and shear stress-shear displacement relationships when the wheel is driven in soft, deformable terrain were studied using classic soil mechanics principles. It is found that the component of thrust in the direction of driving, i.e., driving force, is ranged between 81.52% and 86.17%, while the vertical component is reported to be less than 30% and further decreases to 9%, which is the compaction avoiding factor. The relationships, thus developed, of wheel parameters, soil stress and thrust characteristics, and wheel drive force were derived and revealed that the traction performance, power transfer efficiency, and trafficability of tractors in loose terrain can be improved by using the newly proposed wheel. A finite element method was used to analyze the designed wheel model for structural stability and optimization. The theoretical analysis results of the new drive wheel are convincing, so further tests and field operation research are recommended for sustainable adoption. Full article
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30 pages, 4848 KiB  
Article
Improvement of Piglet Rearing’s Energy Efficiency and Sustainability Using Air-to-Air Heat Exchangers—A Two-Year Case Study
by Hauke F. Deeken, Alexandra Lengling, Manuel S. Krommweh and Wolfgang Büscher
Energies 2023, 16(4), 1799; https://doi.org/10.3390/en16041799 - 11 Feb 2023
Cited by 1 | Viewed by 1505
Abstract
Pig farming in mechanically ventilated barns requires much electricity for ventilation or exhaust air purification. Furthermore, thermal energy is needed to fulfill the animals’ temperature requirements, especially in piglet rearing. Electrical and thermal energy input leads to CO2 emissions and operating costs. [...] Read more.
Pig farming in mechanically ventilated barns requires much electricity for ventilation or exhaust air purification. Furthermore, thermal energy is needed to fulfill the animals’ temperature requirements, especially in piglet rearing. Electrical and thermal energy input leads to CO2 emissions and operating costs. Up to 90% of heat losses are due to the exhausted air. Heat exchangers can recover thermal energy from the warm exhaust air and transfer it to the cold fresh air. This study aimed to investigate energy consumption, efficiency, CO2 emissions, and energy costs when using heat exchangers in a German piglet rearing barn under practical conditions in combination with exhaust air purification. The following parameters were obtained for a two-year period: air temperatures, air flow rates, and electricity and liquefied natural gas consumption; the latter were used to calculate CO2 emissions and energy costs. In total, 576,042 kWhel,th and 616,893 kWhel,th (years 1 and 2) of energy were provided, including 290,414 kWhth and 317,913 kWhth of thermal energy recovered. Using heat exchangers reduced CO2 emissions by up to 37.5% and energy costs by up to 19.7% per year. The study shows that piglet rearing can increase its ecological and environmental sustainability by using heat recovery. Full article
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17 pages, 7069 KiB  
Article
UAV-Based Wireless Data Collection from Underground Sensor Nodes for Precision Agriculture
by Lucas Holtorf, Igor Titov, Frank Daschner and Martina Gerken
AgriEngineering 2023, 5(1), 338-354; https://doi.org/10.3390/agriengineering5010022 - 9 Feb 2023
Cited by 7 | Viewed by 3362
Abstract
In precision agriculture, information technology is used to improve farm management practices. Thereby, productivity can be increased and challenges with overfertilization and water consumption can be addressed. This requires low-power and wireless underground sensor nodes for monitoring the physical, chemical and biological soil [...] Read more.
In precision agriculture, information technology is used to improve farm management practices. Thereby, productivity can be increased and challenges with overfertilization and water consumption can be addressed. This requires low-power and wireless underground sensor nodes for monitoring the physical, chemical and biological soil parameters at the position of the plant roots. Three ESP32-based nodes with these capabilities have been designed to measure soil moisture and temperature. A system has been developed to collect the measurement data from the sensor nodes with a drone and forward the data to a ground station, using the LoRa transmission standard. In the investigations of the deployed system, an increase in the communication range between the sensor node and the ground station, from 300 m to 1000 m by using a drone, was demonstrated. Further, the decrease in the signal strength with the increasing sensor node depth and flight height of the drone was characterized. The maximum readout distance of 550 m between the sensor node and drone was determined. From this, it was estimated that the system enables the readout of the sensor nodes distributed over an area of 470 hectares. Additionally, analysis showed that the antenna orientation at the sensor node and the drone influenced the signal strength distribution around the node due to the antenna radiation pattern. The reproducibility of the LoRa signal strength measurements was demonstrated to support the validity of the results presented. It is concluded that the system design is suitable for collecting the data of distributed sensor nodes in agriculture. Full article
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26 pages, 5270 KiB  
Article
Operational, Economic, and Environmental Assessment of an Agricultural Robot in Seeding and Weeding Operations
by Mahdi Vahdanjoo, René Gislum and Claus Aage Grøn Sørensen
AgriEngineering 2023, 5(1), 299-324; https://doi.org/10.3390/agriengineering5010020 - 1 Feb 2023
Cited by 5 | Viewed by 2780
Abstract
The development of robotic-based agricultural machinery systems has significantly increased in recent years. Many autonomous systems have not yet been measured based on sustainability and economic performances, even though automation is regarded as an opportunity to increase safety, dependability, productivity, and efficiency. The [...] Read more.
The development of robotic-based agricultural machinery systems has significantly increased in recent years. Many autonomous systems have not yet been measured based on sustainability and economic performances, even though automation is regarded as an opportunity to increase safety, dependability, productivity, and efficiency. The operational aspect, economic viability, and environmental impact of replacing conventional machinery with robotized alternatives are the primary focus of this study. The robot considered in this research is designed for extensive fieldwork, where PTO and external hydraulics are required. This robot is equipped with two 75 (hp) Kubota diesel engines with a total engine gross power of up to 144 (hp). Both robotic system and conventional machinery were described, and different scenarios were used to examine various operational and environmental indicators, as well as individual cost elements, considering various field sizes and working widths of implements used in seeding and weeding operations. The findings demonstrate that the robotic system outperforms conventional machinery in terms of operational efficiency by as much as 9%. However, the effective field capacity comparison reveals that the conventional system has a field capacity that is up to 3.6 times greater than that of the robotic system. Additionally, the total cost per hour of the robotic system is up to 57% lower than that of the conventional system. The robotic system can save up to 63.3% of fuel during operation, resulting in the same percentage reduction in CO2 emissions as the conventional system, according to a comparison of fuel consumption. Full article
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21 pages, 39214 KiB  
Article
Impact-Type Sunflower Yield Sensor Signal Denoising Method Based on CEEMD-WTD
by Shuai Wang, Xiaodong Zhao, Wenhang Liu, Jianqiang Du, Dongxu Zhao and Zhihong Yu
Agriculture 2023, 13(1), 166; https://doi.org/10.3390/agriculture13010166 - 9 Jan 2023
Viewed by 1302
Abstract
During the crop harvesting process, it is important to obtain the crop yield quickly, accurately and in real time to accelerate the development of smart agriculture. This paper investigated a denoising method applicable to the impact-type sunflower yield sensor signal under the influence [...] Read more.
During the crop harvesting process, it is important to obtain the crop yield quickly, accurately and in real time to accelerate the development of smart agriculture. This paper investigated a denoising method applicable to the impact-type sunflower yield sensor signal under the influence of complex noise background in the pneumatic seed delivery structure for a sunflower combine harvester. A signal processing method combining complementary ensemble empirical mode decomposition (CEEMD) and wavelet threshold denoising (WTD) based on an adaptive decomposition capability was proposed by analyzing the non-smoothness of the signal with the impact-type sunflower yield sensor signal in sunflower fields. CEEMD was used to decompose the sunflower seed impact analog signal and field impact-type sunflower yield sensor signal adaptively, and the high frequency components were processed by WTD. Finally the de-noised signal was obtained by reconstruction. An evaluation objective function of the denoising ability of the algorithm based on signal-noise ratio, root mean square error, smoothness and waveform similarity indexes with different weights was also constructed. The results showed that the evaluation objective functions of the simulated and measured signals after denoising by the CEEMD-WTD method are 1.9719 and 4.5318, respectively, which are better than the single denoising methods of EMD (1.5096 and 4.0012), EEMD (1.8248 and 4.0724), CEEMD (1.9516 and 4.3384), and WTD (1.8737 and 4.5294). This method provides a new idea for signal denoising of the impact-type sunflower yield sensor installed in the pneumatic seed delivery structure, and further provides theoretical support and technical references for the development of sunflower high-precision yield measurements in smart agriculture. Full article
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15 pages, 6278 KiB  
Article
Optimization of a High-Pressure Soil Washing System for Emergency Recovery of Heavy Metal-Contaminated Soil
by Sang Hyeop Park, Agamemnon Koutsospyros and Deok Hyun Moon
Agriculture 2022, 12(12), 2054; https://doi.org/10.3390/agriculture12122054 - 30 Nov 2022
Cited by 4 | Viewed by 1629
Abstract
Recent natural disasters, such as typhoons in South Korea and other countries around the globe, have resulted in loss of human life and damage to property, often causing contamination of nearby soil environments. This study focused on the emergency recovery of soil contaminated [...] Read more.
Recent natural disasters, such as typhoons in South Korea and other countries around the globe, have resulted in loss of human life and damage to property, often causing contamination of nearby soil environments. This study focused on the emergency recovery of soil contaminated by heavy metals following a disaster such as typhoon flooding by applying a soil washing technique that used high-pressure water rather than chemical cleaning agents. Artificially contaminated soil containing 700 mg/kg Cu, 530 mg/kg Pb and 900 mg/kg Zn, was used. All three metals were present at levels higher than the Korean Warning Standards (500 mg/kg Cu, 400 mg/kg Pb, 600 mg/kg Zn) for region 2 (miscellaneous area). A high-pressure soil washing device was designed to treat 0.6 tons/h and optimal treatment was sought for varying levels of pressure (1, 3, 5 MPa), solid to liquid ratios (S/L) (1:1, 1:3, 1:5), and number of washing cycles (1, 2, 3). The high-pressure soil washing results showed that a 5 MPa washing pressure, 1:1 solid-liquid ratio, and one washing cycle were the optimum conditions to generate the highest heavy metal removal rates. Under optimal conditions, high-pressure soil washing attained removal efficiencies of Cu (37.7%), Pb (36.6%), and Zn (45.1%), and the residual concentrations of heavy metals in the remediated soil satisfied the Korean Warning Standard (Region 2). A comparison of the changes in particle size showed that after high-pressure washing, the mass fraction of coarse sand (CS, 2–0.42 mm) decreased by 23.3%, while that of fine sand (FS, 0.42–0.074 mm), silt, and clay (SC, <0.074 mm) increased by 4.2% and 19.1%, respectively. In addition, 31.1–34.6% of the CS heavy metal mass loading shifted to FS and SC fractions after washing. A comparative analysis of the soil surface morphology before and after washing using scanning electron microscopy (SEM) showed that the particles in the remediated soil became noticeably cleaner after high-pressure washing. This study demonstrated the feasibility of emergency recovery of heavy metal-contaminated soil using high-pressure washing without a chemical cleaning agent. Full article
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22 pages, 7942 KiB  
Article
Evaluating the Impact of Climate Change on the Stream Flow in Soan River Basin (Pakistan)
by Muhammad Ismail, Ehtesham Ahmed, Gao Peng, Ruirui Xu, Muhammad Sultan, Farhat Ullah Khan and Muhammad Aleem
Water 2022, 14(22), 3695; https://doi.org/10.3390/w14223695 - 15 Nov 2022
Cited by 5 | Viewed by 2762
Abstract
The global hydrological cycle is susceptible to climate change (CC), particularly in underdeveloped countries like Pakistan that lack appropriate management of precious freshwater resources. The study aims to evaluate CC impact on stream flow in the Soan River Basin (SRB). The study explores [...] Read more.
The global hydrological cycle is susceptible to climate change (CC), particularly in underdeveloped countries like Pakistan that lack appropriate management of precious freshwater resources. The study aims to evaluate CC impact on stream flow in the Soan River Basin (SRB). The study explores two general circulation models (GCMs), which involve Access 1.0 and CNRM-CM5 using three metrological stations (Rawalpindi, Islamabad, and Murree) data under two emission scenarios of representative concentration pathways (RCPs), such as RCP-4.5 and RCP-8.5. The CNRM-CM5 was selected as an appropriate model due to the higher coefficient of determination (R2) value for future the prediction of early century (2021–2045), mid-century (2046–2070), and late century (2071–2095) with baseline period of 1991–2017. After that, the soil and water assessment tool (SWAT) was utilized to simulate the stream flow of watersheds at the SRB for selected time periods. For both calibration and validation periods, the SWAT model’s performance was estimated based on the coefficient of determination (R2), percent bias (PBIAS), and Nash Sutcliffe Efficiency (NSE). The results showed that the average annual precipitation for Rawalpindi, Islamabad, and Murree will be decrease by 43.86 mm, 60.85 mm, and 86.86 mm, respectively, while average annual maximum temperature will be increased by 3.73 °C, 4.12 °C, and 1.33 °C, respectively, and average annual minimum temperature will be increased by 3.59 °C, 3.89 °C, and 2.33 °C, respectively, in early to late century under RCP-4.5 and RCP-8.5. Consequently, the average annual stream flow will be decreased in the future. According to the results, we found that it is possible to assess how CC will affect small water regions in the RCPs using small scale climate projections. Full article
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14 pages, 2709 KiB  
Article
Genome-Wide Association Study Based on Plant Height and Drought-Tolerance Indices Reveals Two Candidate Drought-Tolerance Genes in Sweet Sorghum
by Yue Xin, Lina Gao, Wenming Hu, Qi Gao, Bin Yang, Jianguo Zhou and Cuilian Xu
Sustainability 2022, 14(21), 14339; https://doi.org/10.3390/su142114339 - 2 Nov 2022
Cited by 6 | Viewed by 1764
Abstract
To understand the molecular mechanism of drought tolerance in sweet sorghum [Sorghum bicolor (L.) Moench], we found the genetic loci associated with single nucleotide polymorphism (SNP) markers and explored drought-tolerance candidate genes. A genome-wide association study (GWAS) of sweet sorghum was performed [...] Read more.
To understand the molecular mechanism of drought tolerance in sweet sorghum [Sorghum bicolor (L.) Moench], we found the genetic loci associated with single nucleotide polymorphism (SNP) markers and explored drought-tolerance candidate genes. A genome-wide association study (GWAS) of sweet sorghum was performed using the general linear model (GLM), mixed linear model (MLM) and the fixed and random model circulating probability unification (FarmCPU) method in R. Mean productivity (MP), relative drought index (RDI) and stress-tolerance index (STI), based on plant height under two water treatments, were obtained from 354 sweet sorghum accessions from home and abroad. These plant-height drought-tolerance indices showed continuous quantitative variation. Except for the RDI, the others were close to normal distribution. A total of 6186 SNPs were obtained from the resequencing data after quality control and filling. The marker densities on chromosomes 9, 10 and 5 were higher than those on other chromosomes, which were 40.4, 16.5 and 10.0 SNPs within 1 Mb, respectively. The GWAS results showed that 49, 5 and 25 significant SNP loci were detected by the GLM, the MLM and FarmCPU, respectively, many of which were detected by two or more models. Two candidate genes of drought tolerance were annotated: Sb08g019720.1, homologous to the gene encoding the early flowering MYB protein transcription factor in Arabidopsis thaliana; and Sb01g037050.1, homologous to the gene encoding the basic leucine zipper transcription factor in maize. The results of this study can facilitate the cultivar development of drought-tolerant sweet sorghum. Full article
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25 pages, 6893 KiB  
Article
Design of an Air Suction Wheel-Hole Single Seed Drill for a Wheat Plot Dibbler
by Xinchun Ma, Qixiang Gong, Qingjie Wang, Dijuan Xu, Yinggang Zhou, Guibin Chen, Xinpeng Cao and Longbao Wang
Agriculture 2022, 12(10), 1735; https://doi.org/10.3390/agriculture12101735 - 20 Oct 2022
Cited by 4 | Viewed by 2254
Abstract
Focusing on the problems of the poor filling ability and stability of the mechanical wheat seeder and the complicated structure of the pneumatic seeder, a special air suction wheel-hole single seed drill for remote controlled self-propelled single seed dibbler in wheat plots was [...] Read more.
Focusing on the problems of the poor filling ability and stability of the mechanical wheat seeder and the complicated structure of the pneumatic seeder, a special air suction wheel-hole single seed drill for remote controlled self-propelled single seed dibbler in wheat plots was designed in this paper. According to the agronomic requirements of precision seeding in wheat plots, the seeding wheel radius was set at 180 mm 16 suction holes. Using the discrete element simulation software EDEM to analyze the seed disturbance effect of different parameter designs, the thickness of seed suction ring was 16 mm, the height of seed suction mouth was 4.5 mm, and the diameter of seed suction cam was 12 mm. Through hydrodynamic simulation, the phase angle of the negative pressure chamber was 280 degrees, positive pressure chamber was 22 degrees, phase angle of the unpressurized interval zone was 20 degrees, thickness of the negative pressure chamber was 24.5 mm, diameter of transition pipe was 17.5 mm and length of the transition pipe was 14.5 mm. Based on the above design parameters, the samples were then processed and benchtop experiments carried out. The results showed that under the best operating parameters, the re-suction index was 0.82%, the leakage index was 6.67%, and the qualified index was 92.41%, which met the design requirements. This study could provide a reference for the design of single-seed dibbling technology in wheat plots. Full article
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18 pages, 3488 KiB  
Article
Food-Grade Cultivation of Saccharomyces cerevisiae from Potato Waste
by Na Cui and Victor Pozzobon
AgriEngineering 2022, 4(4), 951-968; https://doi.org/10.3390/agriengineering4040061 - 17 Oct 2022
Cited by 1 | Viewed by 2998
Abstract
Potato waste is generated in a high amount, stably over the year, by operators capable of recovering it. Currently, it is valorized as feed, bioethanol, or biogas. This work explores another avenue to increase the valorization of this waste: the production of yeast [...] Read more.
Potato waste is generated in a high amount, stably over the year, by operators capable of recovering it. Currently, it is valorized as feed, bioethanol, or biogas. This work explores another avenue to increase the valorization of this waste: the production of yeast production to serve as fodder or single-cell protein. First, potatoes were deconstructed into fermentable sugars by acid hydrolysis using food-grade techniques. Then, after pH adjustment, Saccharomyces cerevisiae was inoculated, and cell growth was monitored. For optimization purposes, this procedure was led over a large range of temperature (90–120 °C) and operation time (30–120 min), for a 1/2 solid/liquid ratio. Response surfaces methodology allowed to achieve a maximum sugar release (44.4 g/L) for 99 min under 103 °C. Then, a numerical model combining biological performances and factory process planning was used to derive process productivity (the best compromise between sugar release and cell growth). Maximal productivity (82.8 gYeast/w/L in batch mode, 110 gYeast/w/L in fed-batch mode) was achieved for 103 min under 94 °C. Furthermore, the process’s robustness was confirmed by a sensibility analysis. Finally, as the proposed procedure preserves the food-grade quality of the substrate, the produced yeast can be used as food or feed. Full article
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14 pages, 2589 KiB  
Article
Early Detection of Bacterial Blight in Hyperspectral Images Based on Random Forest and Adaptive Coherence Estimator
by Yuqiang Wu, Yifei Cao and Zhaoyu Zhai
Sustainability 2022, 14(20), 13168; https://doi.org/10.3390/su142013168 - 13 Oct 2022
Cited by 4 | Viewed by 1530
Abstract
Rice disease detection is of great significance to rice disease management. It is difficult to identify the rice leaves with different colors in different disease periods by RGB image and without aided eyes. Traditional equipment and methods are relatively inefficient in meeting the [...] Read more.
Rice disease detection is of great significance to rice disease management. It is difficult to identify the rice leaves with different colors in different disease periods by RGB image and without aided eyes. Traditional equipment and methods are relatively inefficient in meeting the needs of current disease detection. The accurate and efficient detection the infected areas from hyperspectral images has become a primary concern in current research. However, current spectral target detection research pays less attention to the time and computing resources consumed by detection. A disease detection method based on random forest (RF) and adaptive coherence estimator (ACE) is proposed here. Firstly, based on the spectral differences between diseased and healthy leaves, 18 characteristic spectral wavelengths with the highest importance were selected by an RF algorithm, and the spectral images of those characteristic wavelengths were synthesized. Then, the ACE model was established for the disease recognition of full wavelength spectral images, characteristic wavelength spectral images, and RGB images. At the same time, three other familiar target detection methods were selected as the control experiments. The detection results showed a similarity between the detection performance of the four detection methods for full wavelength spectral image and characteristic wavelength spectral image. This detection performance was higher than that of the RGB image, indicating that characteristic wavelength spectral image can replace full wavelength spectral image for disease detection. The detection performance of the ACE algorithm was better than other algorithms. The detection accuracy of 18 characteristic wavelengths was 97.41%. Compared with the hyperspectral full wavelength image detection results, the accuracy decreased by 1.12%, and the detection time decreased by 2/3, which greatly reduced the detection time. Based on these results, the target detection method combining the RF algorithm and the ACE algorithm can effectively and accurately detect rice bacterial blight disease, which provides a new method for automatic detection of plant disease in the field. Full article
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17 pages, 1875 KiB  
Article
Variations in Physicochemical Characteristics of Olive Oil (cv ‘Moroccan Picholine’) According to Extraction Technology as Revealed by Multivariate Analysis
by El Hassan Sakar, Adil Khtira, Zakarya Aalam, Ahmed Zeroual, Jamila Gagour and Said Gharby
AgriEngineering 2022, 4(4), 922-938; https://doi.org/10.3390/agriengineering4040059 - 10 Oct 2022
Cited by 20 | Viewed by 3371
Abstract
Olive oil is an important component of Mediterranean diet widely, consumed thanks to its numerous health-healing properties. Its quality is dependent upon a set of factors (genotypic, environmental, agronomic practices, ripening, etc). These are well documented, but little is known about the impact [...] Read more.
Olive oil is an important component of Mediterranean diet widely, consumed thanks to its numerous health-healing properties. Its quality is dependent upon a set of factors (genotypic, environmental, agronomic practices, ripening, etc). These are well documented, but little is known about the impact of extraction technology on ‘Moroccan Picholine’ olive oil quality. In this paper, physicochemical traits of olive oil (cv ‘Moroccan Picholine’) were investigated according to extraction technology namely super pressure (SP), 2-phase (2P), and 3-phase (3P) systems as well as traditionally extracted oil (Alwana Oil, AO). The obtained results revealed significant differences (p < 0.05) in terms of the studied physicochemical traits. The investigated oil samples were classified as extra-virgin olive oil. Oil samples from super pressure and AO marked by high records of peroxide value, acidity, K270, fatty acids and trans fatty acids likely due to partial oxidation during extraction. AO was marked by high MUFA, stigmasterol, brassicosterol, 2P displayed high SFA and β-sitosterol, and 3P had high PUFA, SFA, ∆7-avenasterol, and ∆7-stigmasterol. These results were confirmed by principal component analysis, cluster analysis and artificial neural networks. In conclusion, continuous systems (2- and 3-phase) produced olive oil of better quality as compared to super-pressure and traditionally extracted oil. Full article
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17 pages, 4831 KiB  
Article
A VGG-19 Model with Transfer Learning and Image Segmentation for Classification of Tomato Leaf Disease
by Thanh-Hai Nguyen, Thanh-Nghia Nguyen and Ba-Viet Ngo
AgriEngineering 2022, 4(4), 871-887; https://doi.org/10.3390/agriengineering4040056 - 5 Oct 2022
Cited by 24 | Viewed by 7577
Abstract
Tomato leaves can have different diseases which can affect harvest performance. Therefore, accurate classification for the early detection of disease for treatment is very important. This article proposes one classification model, in which 16,010 tomato leaf images obtained from the Plant Village database [...] Read more.
Tomato leaves can have different diseases which can affect harvest performance. Therefore, accurate classification for the early detection of disease for treatment is very important. This article proposes one classification model, in which 16,010 tomato leaf images obtained from the Plant Village database are segmented before being used to train a deep convolutional neural network (DCNN). This means that this classification model will reduce training time compared with that of the model without segmenting the images. In particular, we applied a VGG-19 model with transfer learning for re-training in later layers. In addition, the parameters such as epoch and learning rate were chosen to be suitable for increasing classification performance. One highlight point is that the leaf images were segmented for extracting the original regions and removing the backgrounds to be black using a hue, saturation, and value (HSV) color space. The segmentation of the leaf images is to synchronize the black background of all leaf images. It is obvious that this segmentation saves time for training the DCNN and also increases the classification performance. This approach improves the model accuracy to 99.72% and decreases the training time of the 16,010 tomato leaf images. The results illustrate that the model is effective and can be developed for more complex image datasets. Full article
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24 pages, 9255 KiB  
Article
Investigating Adsorption-Based Atmospheric Water Harvesting Potential for Pakistan
by Muhammad Bilal, Muhammad Sultan, Faizan Majeed, Muhammad Farooq, Uzair Sajjad, Sobhy M. Ibrahim, Muhammad Usman Khan, Shohreh Azizi, Muhammad Yasar Javaid and Riaz Ahmad
Sustainability 2022, 14(19), 12582; https://doi.org/10.3390/su141912582 - 3 Oct 2022
Cited by 3 | Viewed by 2680
Abstract
Atmospheric water harvesting (AWH) can provide clean and safe drinking water in remote areas. The present study provides a comprehensive review of adsorption-based AWH by using the scientometric approach. The publication types are mainly composed of articles and reviews, accounting for 75.37% and [...] Read more.
Atmospheric water harvesting (AWH) can provide clean and safe drinking water in remote areas. The present study provides a comprehensive review of adsorption-based AWH by using the scientometric approach. The publication types are mainly composed of articles and reviews, accounting for 75.37% and 11.19% of the total, respectively. Among these publications, ~95.1% were published in English and came from 154 different journals which demonstrates that researchers have shown a great interest in this field. However, much less contribution has been received thus far on this topic from Pakistan. Therefore, this study aims to explore a solar-driven adsorption-based AWH system in terms of varying relative humidity (RH), solar irradiance, and various types of adsorbent materials. Geospatial mapping and Monte Carlo simulations are carried out to integrate the operational parameters of the system and materials with Pakistan’s climatic conditions to forecast the AWH potential (L/m2/d). Probability distribution of 100,000 trials is performed by providing lower, mode, and upper values of the independent parameters. The possible outcomes of the adsorbed volume of water are determined by generating random values for the independent parameters within their specified distribution. It was found that MIL-101 (Cr) achieved the highest water-harvesting rate (WHR) of 0.64 to 3.14 (L/m2/d) across Pakistan, whereas the WHR was lowered to 0.58 to 1.59, 0.83 to 0.94, and 0.45 to 1.26 (L/m2/d) for COF-432, zeolite, and silica gel, respectively. Furthermore, parameter optimization and sensitivity analysis are performed to finalize the boundary conditions of the adsorption-based AWH system by ensuring the maximum volume values within the desired specification limits (1–4 L/m2/d). Full article
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17 pages, 5564 KiB  
Article
Design and Experiment with a Double-Roller Sweet Potato Vine Harvester
by Guizhi Mu, Wanshuai Wang, Tingting Zhang, Lianglong Hu, Wenxiu Zheng and Wanzhi Zhang
Agriculture 2022, 12(10), 1559; https://doi.org/10.3390/agriculture12101559 - 27 Sep 2022
Cited by 2 | Viewed by 2192
Abstract
The yield of sweet potato vines is large, making it a good source of food. However, it is difficult to harvest sweet potato vines due to creeping and intertwining. Therefore, according to the domestic sweet potato planting model, this paper designed a double [...] Read more.
The yield of sweet potato vines is large, making it a good source of food. However, it is difficult to harvest sweet potato vines due to creeping and intertwining. Therefore, according to the domestic sweet potato planting model, this paper designed a double roll sweet potato vine harvester which can complete the operations of vine picking, vine killing, conveying and header harvesting at one time. The machine adopts the process of front roll vine picking, rear roll vine killing and rod bar lifting. The key components of the vine picking device, vine killing device and lifting device were designed and calculated. A numerical simulation test of the vine harvesting process was carried out by using the discrete element numerical simulation method. It was determined that the length of the vine picking rod from the outside to the inside is 175 mm, 150 mm and 105 mm, respectively, and the inclination angle of the end is 160°. There are six vine killing knives on each vine killing knife plate. The inclination of the lifting device is 50°and the conveying speed is 3 m/s. Using the box Behnken experimental design method, taking the vine picking roller speed, vine killing roller speed and ground clearance as the experimental factors, and taking the sweet potato vine harvest rate, stubble height and potato injury rate as the evaluation indexes, a quadratic regression orthogonal test was carried out, the effects of various factors on the evaluation indexes were analyzed, and the experimental factors were optimized and verified. The experimental results showed that the optimal parameter combination is as follows: the rotation speed of vine picking roller should be 716 r/min, the rotation speed of vine killing roller should be 1960 r/min and the ground clearance should be 16 mm. With these parameters, the harvest rate of sweet potato vines is 93.1%, the stubble height is 29.5 mm and the potato injury rate is 0.174%. As such, the harvester meets the requirements for the mechanized harvesting of sweet potato vines and is of great significance as a light and simplified product for the sweet potato industry. Full article
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25 pages, 7954 KiB  
Essay
Research on the Control Strategy of Leafy Vegetable Harvester Travel Speed Automatic Control System
by Wenming Chen, Gongpu Wang, Lianglong Hu, Jianning Yuan, Wen Wu, Guocheng Bao and Zicheng Yin
AgriEngineering 2022, 4(4), 801-825; https://doi.org/10.3390/agriengineering4040052 - 21 Sep 2022
Viewed by 2046
Abstract
This paper used the 4UM-120D electric leafy vegetable harvester as the research object and designed a travel speed automatic control system to maintain the travel speed within a set value of ±2% in order to improve the efficiency and quality of leafy vegetable [...] Read more.
This paper used the 4UM-120D electric leafy vegetable harvester as the research object and designed a travel speed automatic control system to maintain the travel speed within a set value of ±2% in order to improve the efficiency and quality of leafy vegetable harvester operations and decrease the work intensity of the operator. The harvester’s travel speed was automatically controlled by using the PID, adaptive fuzzy PID, and sliding mode control techniques after the mechanical and electrical equations for the travel drive motor (a DC brushless motor) were established in MATLAB. By simulating various working situations, the stability, accuracy, and speed of the automatic control system were compared and analyzed using the adjustment time, overshoot, steady-state transition time, and maximum deviation from the set speed as evaluation indicators. The test results revealed that when the current value of the leafy vegetable harvester travel speed deviated from the set value by more than 2%, the dynamic response performance and stability of the DC brushless motor travel drive system based on the sliding mode control strategy was significantly better than that of the PID and adaptive fuzzy PID control strategies, and its anti-disturbance was stronger, achieving the function of automatic control of the harvester travel speed. When the travel motor started with a constant load and the sliding mode control strategy’s parameters were the gain factors A = 1/70, c = 100, ε = 100, and k = 100, the travel drive system regulation time was 1.5 s, and the overshoot was 10%. When the harvester was operating smoothly and had leafy vegetable collection baskets loaded and unloaded, the steady-state transition time was 0.3 s. According to the actual engineering application experience, the specific technical state of the control strategy of the agricultural machinery travel speed automatic control system was: regulation time 2.5~3 s; overshoot amount 20~25%; and steady-state transition time 1.0~1.5 s, so the travel speed automatic control system of the electric leafy vegetable harvester in sliding mode was in line with the technical state requirements. The results of the field trials demonstrated the accuracy of the simulation test results. This study offered a method to lessen the work intensity of operators and increase the operating efficiency and quality of a leafy vegetable harvester. Full article
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23 pages, 3395 KiB  
Review
Soil Moisture Measuring Techniques and Factors Affecting the Moisture Dynamics: A Comprehensive Review
by Muhammad Waseem Rasheed, Jialiang Tang, Abid Sarwar, Suraj Shah, Naeem Saddique, Muhammad Usman Khan, Muhammad Imran Khan, Shah Nawaz, Redmond R. Shamshiri, Marjan Aziz and Muhammad Sultan
Sustainability 2022, 14(18), 11538; https://doi.org/10.3390/su141811538 - 14 Sep 2022
Cited by 31 | Viewed by 14644
Abstract
The amount of surface soil moisture (SSM) is a crucial ecohydrological natural resource that regulates important land surface processes. It affects critical land–atmospheric phenomena, including the division of energy and water (infiltration, runoff, and evaporation), that impacts the effectiveness of agricultural output (sensible [...] Read more.
The amount of surface soil moisture (SSM) is a crucial ecohydrological natural resource that regulates important land surface processes. It affects critical land–atmospheric phenomena, including the division of energy and water (infiltration, runoff, and evaporation), that impacts the effectiveness of agricultural output (sensible and latent heat fluxes and surface air temperature). Despite its significance, there are several difficulties in making precise measurements, monitoring, and interpreting SSM at high spatial and temporal resolutions. The current study critically reviews the methods and procedures for calculating SSM and the variables influencing measurement accuracy and applicability under different fields, climates, and operational conditions. For laboratory and field measurements, this study divides SSM estimate strategies into (i) direct and (ii) indirect procedures. The accuracy and applicability of a technique depends on the environment and the resources at hand. Comparative research is geographically restricted, although precise and economical—direct measuring techniques like the gravimetric method are time-consuming and destructive. In contrast, indirect methods are more expensive and do not produce measurements at the spatial scale but produce precise data on a temporal scale. While measuring SSM across more significant regions, ground-penetrating radar and remote sensing methods are susceptible to errors caused by overlapping data and atmospheric factors. On the other hand, soft computing techniques like machine/deep learning are quite handy for estimating SSM without any technical or laborious procedures. We determine that factors, e.g., topography, soil type, vegetation, climate change, groundwater level, depth of soil, etc., primarily influence the SSM measurements. Different techniques have been put into practice for various practical situations, although comparisons between them are not available frequently in publications. Each method offers a unique set of potential advantages and disadvantages. The most accurate way of identifying the best soil moisture technique is the value selection method (VSM). The neutron probe is preferable to the FDR or TDR sensor for measuring soil moisture. Remote sensing techniques have filled the need for large-scale, highly spatiotemporal soil moisture monitoring. Through self-learning capabilities in data-scarce areas, machine/deep learning approaches facilitate soil moisture measurement and prediction. Full article
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35 pages, 5395 KiB  
Review
An Overview of End Effectors in Agricultural Robotic Harvesting Systems
by Eleni Vrochidou, Viktoria Nikoleta Tsakalidou, Ioannis Kalathas, Theodoros Gkrimpizis, Theodore Pachidis and Vassilis G. Kaburlasos
Agriculture 2022, 12(8), 1240; https://doi.org/10.3390/agriculture12081240 - 17 Aug 2022
Cited by 27 | Viewed by 7527
Abstract
In recent years, the agricultural sector has turned to robotic automation to deal with the growing demand for food. Harvesting fruits and vegetables is the most labor-intensive and time-consuming among the main agricultural tasks. However, seasonal labor shortage of experienced workers results in [...] Read more.
In recent years, the agricultural sector has turned to robotic automation to deal with the growing demand for food. Harvesting fruits and vegetables is the most labor-intensive and time-consuming among the main agricultural tasks. However, seasonal labor shortage of experienced workers results in low efficiency of harvesting, food losses, and quality deterioration. Therefore, research efforts focus on the automation of manual harvesting operations. Robotic manipulation of delicate products in unstructured environments is challenging. The development of suitable end effectors that meet manipulation requirements is necessary. To that end, this work reviews the state-of-the-art robotic end effectors for harvesting applications. Detachment methods, types of end effectors, and additional sensors are discussed. Performance measures are included to evaluate technologies and determine optimal end effectors for specific crops. Challenges and potential future trends of end effectors in agricultural robotic systems are reported. Research has shown that contact-grasping grippers for fruit holding are the most common type of end effectors. Furthermore, most research is concerned with tomato, apple, and sweet pepper harvesting applications. This work can be used as a guide for up-to-date technology for the selection of suitable end effectors for harvesting robots. Full article
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13 pages, 1012 KiB  
Article
Effects of Controlled Release Urea Formula and Conventional Urea Ratio on Grain Yield and Nitrogen Use Efficiency of Direct-Seeded Rice
by Shuang Cheng, Zhipeng Xing, Chao Tian, Shaoping Li, Jinyu Tian, Qiuyuan Liu, Yajie Hu, Baowei Guo, Qun Hu, Haiyan Wei, Hui Gao and Hongcheng Zhang
Agriculture 2022, 12(8), 1230; https://doi.org/10.3390/agriculture12081230 - 15 Aug 2022
Cited by 7 | Viewed by 1761
Abstract
A one-off application of bulk blend urea (BBU), which includes a controlled release urea formula and conventional urea, has been recommended to simplify fertilisation management for direct-seeded rice. However, the effects of different basal application ratios of controlled-release urea formula and conventional urea [...] Read more.
A one-off application of bulk blend urea (BBU), which includes a controlled release urea formula and conventional urea, has been recommended to simplify fertilisation management for direct-seeded rice. However, the effects of different basal application ratios of controlled-release urea formula and conventional urea on yield and nitrogen (N) use efficiency remain unknown in direct-seeded rice. This study set up three BBU treatments in which the controlled-release urea formula provided 50% (BBU1), 60% (BBU2), and 70% (BBU3) of the total N. This study measured their effects on grain yield and N use efficiency of direct-seeded rice. Split fertilisation with conventional urea was used as the control (CK). The study concluded four key points: (i) the grain yield of direct-seeded rice decreased as the proportion of controlled-release urea formula increased, (ii) BBU1 increased grain yields by 8.1–8.6% and 10.2–10.6% compared to BBU2 and BBU3, respectively, as well as a greater number of panicles and spikelets per m2, and post-anthesis dry matter accumulation, (iii) the N recovery efficiency and N agronomic efficiency of BBU1 were significantly higher than those of BBU2 and BBU3 treatments, and the nitrogen accumulation was also found to be more, and (iv) compared with the CK, BBU1 achieved considerable grain yield and nitrogen use efficiency while reducing the amount of fertilisation. In conclusion, the appropriate reduction of the basal application ratio of the controlled-release urea formula for direct-seeded rice increased grain yield and nitrogen use efficiency. Full article
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19 pages, 17847 KiB  
Article
Study on Heating and Cooling Performance of Air-to-Water Heat Pump System for Protected Horticulture
by Adnan Rasheed, Jong Won Lee, Hyeon Tae Kim and Hyun Woo Lee
Energies 2022, 15(15), 5467; https://doi.org/10.3390/en15155467 - 28 Jul 2022
Cited by 4 | Viewed by 1767
Abstract
There is much interest in alternative energy sources for greenhouse heating and cooling, due to the impact of severe climatic conditions and increasing fossil fuel prices. The main objective of this study was to experimentally evaluate the performance of an air-to-water heat pump [...] Read more.
There is much interest in alternative energy sources for greenhouse heating and cooling, due to the impact of severe climatic conditions and increasing fossil fuel prices. The main objective of this study was to experimentally evaluate the performance of an air-to-water heat pump (AWHP) system to fulfil the cooling and heating energy requirements of a three-spanned greenhouse under local weather conditions in Daegu, South Korea. For this purpose, a system comprising three air-to-water heat pumps, a water storage tank, and fan coil units (FCU)s was designed. Experiments were conducted extensively during the summer and winter seasons. The maximum heating and cooling energy supply to the greenhouse was 210 kcal∙h−1∙m−2 and 230 kcal∙h−1∙m−2, respectively. Based on the outcomes of this study, the AWHP system can provide heating during the winter season. During the summer season, the FCU capacity was insufficient to provide the desired cooling to achieve the setpoint air temperature inside the studied greenhouse. To achieve the desired microclimate during the summer season, the capacity of the FCU or number of FCUs must be increased. Moreover, one AWHP with a water storage tank, was sufficient to provide the required cooling and heating in both seasons. Two additional AWHPs can be used to provide energy to more greenhouse areas in the future. The results can be used as a case study to find a more resilient and reliable source for greenhouse heating and cooling. The average COP of the AWHP in heating mode was 2.2, while on cooling mode, it was 3.2. Full article
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12 pages, 3478 KiB  
Article
Estimation of Greenhouse Tomato Foliage Temperature Using DNN and ML Models
by Roei Grimberg, Meir Teitel, Shay Ozer, Asher Levi and Avi Levy
Agriculture 2022, 12(7), 1034; https://doi.org/10.3390/agriculture12071034 - 15 Jul 2022
Cited by 3 | Viewed by 1740
Abstract
Since leaf temperature (LT) is not a trivial measurement, deep-neural networks (DNN) and machine learning (ML) models were evaluated in this study as tools for estimating foliage temperature. Two DNN methods were used. The first DNN used convolutional layers, while the second DNN [...] Read more.
Since leaf temperature (LT) is not a trivial measurement, deep-neural networks (DNN) and machine learning (ML) models were evaluated in this study as tools for estimating foliage temperature. Two DNN methods were used. The first DNN used convolutional layers, while the second DNN was based on fully-connected layers and was trained by cross-validation techniques. The machine learning used the K-nearest neighbors (KNN) method for LT estimation. All models used the meteorological and microclimatic parameters (hereafter referred to as features) of the examined greenhouses to determine the average foliage temperature. The models were trained on 75% of the collected data and tested on the remaining 25%. RMS and absolute error were used to evaluate the performance of the different models compared to the LT values measured by a thermal camera. In addition, after finding the correlation of each feature to the leaf temperature, the models were trained based on the high-correlated features only. The machine learning model was superior to DNN when all available features were used and when only high-correlated features were used, resulting in errors of 0.7 °C and 0.8 °C, respectively. Full article
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17 pages, 2591 KiB  
Article
Characterisation of Pineapple Cultivars under Different Storage Conditions Using Infrared Thermal Imaging Coupled with Machine Learning Algorithms
by Maimunah Mohd Ali, Norhashila Hashim, Samsuzana Abd Aziz and Ola Lasekan
Agriculture 2022, 12(7), 1013; https://doi.org/10.3390/agriculture12071013 - 13 Jul 2022
Cited by 10 | Viewed by 3445
Abstract
The non-invasive ability of infrared thermal imaging has gained interest in various food classification and recognition tasks. In this work, infrared thermal imaging was used to distinguish different pineapple cultivars, i.e., MD2, Morris, and Josapine, which were subjected to different storage temperatures, i.e., [...] Read more.
The non-invasive ability of infrared thermal imaging has gained interest in various food classification and recognition tasks. In this work, infrared thermal imaging was used to distinguish different pineapple cultivars, i.e., MD2, Morris, and Josapine, which were subjected to different storage temperatures, i.e., 5, 10, and 25 °C and a relative humidity of 85% to 90%. A total of 14 features from the thermal images were obtained to determine the variation in terms of image parameters among the different pineapple cultivars. Principal component analysis was applied for feature reduction in order to prevent any effect of significant difference between the selected features. Several types of machine learning algorithms were compared, including linear discriminant analysis, quadratic discriminant analysis, support vector machine, k-nearest neighbour, decision tree, and naïve Bayes, to obtain the best performance for the classification of pineapple cultivars. The results showed that support vector machine achieved the best performance from the combination of optimal image parameters with the highest classification rate of 100%. The ability of infrared thermal imaging coupled with machine learning approaches can be potentially used to distinguish pineapple cultivars, which could enhance the grading and sorting processes of the fruit. Full article
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24 pages, 10985 KiB  
Article
Assessment of Multi-Satellite Precipitation Products over the Himalayan Mountains of Pakistan, South Asia
by Muhammad Umer Nadeem, Muhammad Naveed Anjum, Arslan Afzal, Muhammad Azam, Fiaz Hussain, Muhammad Usman, Muhammad Mashood Javaid, Muhammad Ahsan Mukhtar and Faizan Majeed
Sustainability 2022, 14(14), 8490; https://doi.org/10.3390/su14148490 - 11 Jul 2022
Cited by 10 | Viewed by 2022
Abstract
Performance assessment of satellite-based precipitation products (SPPs) is critical for their application and development. This study assessed the accuracies of four satellite-based precipitation products (PERSIANN-CDR, PERSIANN-CCS, PERSIANN-DIR, and PERSIANN) using data of in situ weather stations installed over the Himalayan Mountains of Pakistan. [...] Read more.
Performance assessment of satellite-based precipitation products (SPPs) is critical for their application and development. This study assessed the accuracies of four satellite-based precipitation products (PERSIANN-CDR, PERSIANN-CCS, PERSIANN-DIR, and PERSIANN) using data of in situ weather stations installed over the Himalayan Mountains of Pakistan. All SPPs were evaluated on annual, seasonal, monthly, and daily bases from 2010 to 2017, over the whole spatial domain and at point-to-pixel scale. The assessment was conducted using widely used evaluation indices (root mean square error (RMSE), correlation coefficient (CC), bias, and relative bias (rBias)) along with categorical indices (false alarm ratio (FAR), probability of detection (POD), success ratio (SR), and critical success index (CSI)). Results showed: (1) PERSIANN and PERSIANN-DIR products efficiently traced the spatio-temporal distribution of precipitation over the Himalayan Mountains. (2) On monthly scale, the estimates of all SPPs were more consistent with the reference data than on the daily scale. (3) On seasonal scale, PERSIANN and PERSIANN-DIR showed better performances than the PERSIANN-CDR and PERSIANN-CCS products. (4) All SPPs were less accurate in sensing daily light to medium intensity precipitation events. Subsequently, for future hydro-meteorological investigations in the Himalayan range, we advocate the use of monthly PERSIANN and PERSIANN-DIR products. Full article
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20 pages, 6482 KiB  
Article
Physicochemical Investigation of Rainfall for Managed Aquifer Recharge in Punjab (Pakistan)
by Ghulam Zakir-Hassan, Jehangir F. Punthakey, Ghulam Shabir, Fozia Yasmeen, Muhammad Sultan, Hadeed Ashraf, Ihsanullah Sohoo and Faizan Majeed
Water 2022, 14(14), 2155; https://doi.org/10.3390/w14142155 - 7 Jul 2022
Cited by 6 | Viewed by 2779
Abstract
In a water-scarce country such as Pakistan, rainfall is the third-largest source of freshwater. In most of the urban cities of the country, rainwater is mixed with sewerage and is rendered useless for managed aquifer recharge purposes. Therefore, this study investigates the rainfall [...] Read more.
In a water-scarce country such as Pakistan, rainfall is the third-largest source of freshwater. In most of the urban cities of the country, rainwater is mixed with sewerage and is rendered useless for managed aquifer recharge purposes. Therefore, this study investigates the rainfall potential for managed aquifer recharge in Lahore (Pakistan). The present research was designed and conducted by the Irrigation Research Institute (IRI). Three different sites were selected for rainwater sample collection across the study area (Lahore), ranging from urban to rural areas. The rainwater samples were collected and divided into three categories (direct capture, rooftop runoff, street runoff). For longer rainfall events, the effect of time on the quality of the collected rainwater samples was also studied. Spatiotemporal trends of turbidity, pH, electrical conductivity, total dissolved solids, carbonates, bicarbonates, chloride, calcium, magnesium, and hardness in the collected rainwater samples were investigated. In terms of TDS, results indicated that directly captured rainwater is most suitable for managed aquifer recharge (TDS < 50 ppm), followed by rooftop runoff (TDS < 100 ppm). In addition, the quality of rainwater samples collected at the rural site was comparatively better. Moreover, the quality of rainwater samples improved after the initial ten minutes. All in all, this study concludes that direct capture of rainwater is the most suitable option for managed aquifer recharge. Full article
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20 pages, 5612 KiB  
Article
Kinematic-Based Multi-Objective Design Optimization of a Grapevine Pruning Robotic Manipulator
by Faezeh Molaei and Shirin Ghatrehsamani
AgriEngineering 2022, 4(3), 606-625; https://doi.org/10.3390/agriengineering4030040 - 4 Jul 2022
Cited by 6 | Viewed by 3538
Abstract
Annual cane pruning of grape vineyards is a time-consuming and labor-intensive job, but no mechanized or automatic way has been developed to do it yet. Robotic pruning can be a perfect alternative to human labor. This article proposes a systematic seven-stage procedure to [...] Read more.
Annual cane pruning of grape vineyards is a time-consuming and labor-intensive job, but no mechanized or automatic way has been developed to do it yet. Robotic pruning can be a perfect alternative to human labor. This article proposes a systematic seven-stage procedure to design a kinematically optimized manipulator, named ‘Prubot’, to manage vineyards’ cane pruning. The manipulator structure was chosen, resulting in a 7R (Revolute) manipulator with a spherical shoulder and wrist. To obtain the design constraints, the manipulator task space was modeled. The robot’s second and third link lengths were determined by optimizing the global translational version of the measure of manipulability and the measure of isotropy of the manipulator arm section. Finally, simulations confirmed the appropriateness of the manipulator workspace. Furthermore, sampling-based path planning simulations were carried out to evaluate the manipulator’s kinematic performance. Results illustrated the impressive kinematic performance of the robot in terms of path planning success rate (100%). The simulations also suggest that among the eight single-query sampling-based path planning algorithms used in the simulations, Lazy RRT and KPIECE are the best (5 s & ~100%) and worst 5 s &25% path planning algorithms for such a robot in terms of computation time and success rate, respectively. The procedure proposed in this paper offers a foundation for the kinematic and task-based design of a cane pruning manipulator. It could be promisingly used for designing similar agricultural manipulators. Full article
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18 pages, 4654 KiB  
Article
A Continuous Single-Layer Discrete Tiling System for Online Detection of Corn Impurities and Breakage Rates
by Kun Wu, Min Zhang, Gang Wang, Xu Chen and Jun Wu
Agriculture 2022, 12(7), 948; https://doi.org/10.3390/agriculture12070948 - 30 Jun 2022
Cited by 5 | Viewed by 1400
Abstract
In order to improve the accuracy and efficiency of the methods that are used for the detection of impurities in and the breakage rate of harvested corn grains, we propose a classification and identification method using a feature threshold and a backpropagation (BP) [...] Read more.
In order to improve the accuracy and efficiency of the methods that are used for the detection of impurities in and the breakage rate of harvested corn grains, we propose a classification and identification method using a feature threshold and a backpropagation (BP) neural network that is based on a genetic algorithm. We also constructed a continuous single-layer discrete tile detection system for application to harvested corn grains containing impurities and broken kernels. We conducted an evaluation of the proposed approach with a three-factor and three-level orthogonal experimental design. By setting the working parameters, we realized the continuous single-layer discrete tiling of the grains and 50 grain materials were collected on average in a single picture. In the static test, the error between the system monitoring value and the manual detection value was small, the maximum absolute errors of the breakage and impurity rates were 2.16% and 1.03%, and the average time that was required for each image recognition was 1.71 s. In the experimental environment, the maximum absolute error values of the breakage and impurity rates were 3.48% and 1.78%. The system’s identification accuracy and processing time meet the requirements of the online detection of corn characteristics in grain harvesting. Full article
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15 pages, 2125 KiB  
Article
Structural Design and Simulation of Pneumatic Conveying Line for a Paddy Side-Deep Fertilisation System
by Qingzhen Zhu, Hengyuan Zhang, Zhihao Zhu, Yuanyuan Gao and Liping Chen
Agriculture 2022, 12(6), 867; https://doi.org/10.3390/agriculture12060867 - 15 Jun 2022
Cited by 3 | Viewed by 2113
Abstract
To improve the consistency of sectional gas velocities in different rows in the pneumatic conveying line for a paddy side-deep fertilisation system, a new airflow equaliser was designed based on the mechanism of gas flow in ventilation engineering. Subsequently, the effects of key [...] Read more.
To improve the consistency of sectional gas velocities in different rows in the pneumatic conveying line for a paddy side-deep fertilisation system, a new airflow equaliser was designed based on the mechanism of gas flow in ventilation engineering. Subsequently, the effects of key structural parameters and a position parameter of the airflow equaliser on the consistency of sectional gas velocities in different rows were investigated using the method of single-factor tests in Fluent, which provided a reasonable range for the next orthogonal test (notch angle (A): 120–180°, extended length (B): 18–30 mm and distance between adjacent branches (C): 120–160 mm). Thereafter, the parameters were optimised through an orthogonal test, using the coefficient of variation of the consistency of the sectional gas velocities in different rows (CV) as an indicator and using Fluent software. The results revealed that the order of primary and secondary factors was evaluated as B > A × B > C > A, and when A, B and C were selected as 150°, 30 mm and 120 mm, respectively, the consistency of the sectional gas velocities in different rows could get a very effective result (CV = 7.07%). Finally, to validate the feasibility of simulations of the performance of the airflow equalisers and to practically evaluate the contribution of the optimised airflow equalisers to improve the consistency of the sectional gas velocities in different rows, a bench test for the line with the optimised airflow equalisers and a simulation test for the line without the optimised airflow equalisers were carried out and the results showed that the CV values were 9.53%, 20.69%, respectively. It concluded that the optimised airflow equalisers could significantly improve the consistency of the sectional gas velocities in different rows by comparing the CV in the three tests including the simulation test for the line with the optimised airflow equalisers. This research provides a good reference for optimising the pneumatic conveying line for a paddy side-deep fertilisation system. Full article
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16 pages, 1610 KiB  
Article
Humic and Acetic Acids Have the Potential to Enhance Deterioration of Select Plastic Soil-Biodegradable Mulches in a Mediterranean Climate
by Brenda Madrid, Huan Zhang, Carol A. Miles, Michael Kraft, Deirdre Griffin-LaHue and Lisa Wasko DeVetter
Agriculture 2022, 12(6), 865; https://doi.org/10.3390/agriculture12060865 - 15 Jun 2022
Viewed by 2598
Abstract
The perceived variability of plastic soil-biodegradable mulch (BDM) degradation has generated concerns about its functionality and sustainability, especially in climates and regions where biodegradation may be limited. This study evaluated the effects of surface-applied products (compost tea, dairy-based compost, humic and acetic acids) [...] Read more.
The perceived variability of plastic soil-biodegradable mulch (BDM) degradation has generated concerns about its functionality and sustainability, especially in climates and regions where biodegradation may be limited. This study evaluated the effects of surface-applied products (compost tea, dairy-based compost, humic and acetic acids) on the surface deterioration and visible degradation of three plastic BDMs (BASF 0.6, Novamont 0.6, and Novamont 0.7) and one cellulose paper mulch (WeedGuard Plus) in a Mediterranean climate. Deterioration was monitored for 10 months, and degradation was evaluated 6- and 12 months following soil incorporation. Deterioration varied between the two years of the study; however, the average deterioration for WeedGuard Plus reached 100%, BASF 0.6 and Novamont 0.6 achieved ≥80%, while Novamont 0.7 reached ≥70%. Application of humic and acetic acids increased BASF 0.6 deterioration, but only humic acid increased Novamont 0.7 deterioration. Scanning electron microscopy of mulch surfaces demonstrated evidence of microbial colonization; however, the surface-applied products did not enhance microbial counts. In-soil degradation of BDMs was inconsistent, but faster degradation occurred overall for starch- and polybutylene adipate-co-terephthalate (PBAT)-based BDMs. Future studies should continue to explore on-farm strategies to enhance in-soil degradation to meet the production system’s goals. Full article
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16 pages, 3819 KiB  
Article
An Improved EfficientNet for Rice Germ Integrity Classification and Recognition
by Bing Li, Bin Liu, Shuofeng Li and Haiming Liu
Agriculture 2022, 12(6), 863; https://doi.org/10.3390/agriculture12060863 - 15 Jun 2022
Cited by 10 | Viewed by 2430
Abstract
Rice is one of the important staple foods for human beings. Germ integrity is an important indicator of rice processing accuracy. Traditional detection methods are time-consuming and highly subjective. In this paper, an EfficientNet–B3–DAN model is proposed to identify the germ integrity. Firstly, [...] Read more.
Rice is one of the important staple foods for human beings. Germ integrity is an important indicator of rice processing accuracy. Traditional detection methods are time-consuming and highly subjective. In this paper, an EfficientNet–B3–DAN model is proposed to identify the germ integrity. Firstly, ten types of rice with different germ integrity are collected as the training set. Secondly, based on EfficientNet–B3, a dual attention network (DAN) is introduced to sum the outputs of two channels to change the representation of features and further focus on the extraction of features. Finally, the network is trained using transfer learning and tested on a test set. Comparing with AlexNet, VGG16, GoogleNet, ResNet50, MobileNet, and EfficientNet–B3, the experimental illustrate that the detection overall accuracy of EfficientNet–B3–DAN is 94.17%. It is higher than other models. This study can be used for the classification of rice germ integrity to provide guidance for rice and grain processing industries. Full article
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