Journal of Agricultural Engineering
https://www.agroengineering.org/jae
<p>The <strong>Journal of Agricultural Engineering (JAE)</strong> covers a complete and interdisciplinary range of research topics in engineering for agriculture food, forestry and biosystems. The journal publishes papers of both theoretical and applied nature, with a special focus on experimental research, new design criteria and innovative approaches, relating to all fields of agricultural engineering.<br /><strong>JAE</strong> is the official journal of the <a href="http://www.aiia.it" target="_blank" rel="noopener"><strong>Italian Society of Agricultural Engineering</strong></a>.</p>PAGEPress Scientific Publications, Pavia, Italyen-USJournal of Agricultural Engineering1974-7071<p><strong>PAGEPress</strong> has chosen to apply the <a href="http://creativecommons.org/licenses/by-nc/4.0/" target="_blank" rel="noopener"><strong>Creative Commons Attribution NonCommercial 4.0 International License</strong></a> (CC BY-NC 4.0) to all manuscripts to be published.</p>Parametric evaluation of segmentation techniques for paddy diseases analysis
https://www.agroengineering.org/jae/article/view/1532
<p>In most paddy plant diseases, the leaf is the primary source of information for image-based disease identification and classification. Image segmentation is an important step in the plant disease analysis process. It is used to separate the normal part of the leaf from the disease-affected part of the leaf. In this paper diseases like Bacterial leaf blight (BLB), Brown spot (BS), and Leaf smut (LS) are segmented using existing, K-means clustering, the Otsu thresholding method. Color space-based segmentation is newly proposed for paddy disease analysis. The intelligence of segmentation techniques is evaluated using the Error Rate (ER) and Overlap Rate (OR) across the three paddy diseases namely, BLB, BS, and LS. The results were compared among the Otsu, K-means and color thresholding segmentation techniques. The results revealed that the color thresholding method using the Lab model emerged as a novel segmentation method for all three paddy diseases with an average ER and OR of [0.36, 0.95]. The proposed work is carried out in the Department of Electronics and Communication research center at Ballari Institute of Technology and Management, Ballari, Karnataka during the period from August 2022 to February 2023 with the expert suggestions of the plant pathologist, from the University of Agricultural Science, Dharwad, Karnataka.</p>Hemanthakumar R. KappaliSadyojatha K.M.Prashanthi S.K.
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2023-08-042023-08-0454410.4081/jae.2023.1532On evaluating the hypothesis of shape similarity between soil particle-size distribution and water retention function
https://www.agroengineering.org/jae/article/view/1542
<p>Two pedotransfer functions (PTFs) are available in the literature enabling the soil water retention function (WRF) to be estimated from knowledge of the soil particle-size distribution (PSD), oven-dry soil bulk density (rb), and saturated soil water content (qs): i) the Arya and Heitman model (PTF-AH), and ii) the Mohammadi and Vanclooster model (PTF-MV). These physicoempirical PTFs rely on the hypothesis of shape similarity between PSD and WRF, and do not require the calibration of the input parameters. In the first stage, twenty-seven PSD models were evaluated using 4,128 soil samples collected in Campania (southern Italy). These models were ranked according to the root mean square residuals (RMSR), corrected Akaike information criterion (AICc), and adjusted coefficient of determination (R2adj). In the second stage, three subsets of PSD and WRF data (DS-1, DS-2, and DS-3), comprising 282 soil samples, were used to evaluate the two PTFs using the best three PSD models selected in the first stage. The hypothesis of shape similarity was assumed as acceptable only when the RMSR value was lower than the field standard deviation of the WRFs (s*), which is viewed as a tolerance threshold and computed from the physically based scaling approach proposed by Kosugi and Hopmans (1998). In the first study area (DS- 1), characterized by a fairly uniform, loamy textured volcanic soil, the PTF-AH outperformed the PTF-MV and both PTFs provided reasonable performance within the acceptance threshold (i.e., RMSR < s*). In the other two heterogeneous field sites (DS-2 and DS-3, characterized by soil textural classes that span from clay and clay-loam to loam and even sandy-loam soils), the PTF-MV (with 3% to 6% RMSR surpassing s*) outperformed the PTF-AH (with 8% to 30% RMSR surpassing s*) and the majority of RMSR values were larger than those obtained in the original studies. The mean relative error (MRE) revealed that the PTF-MV systematically underestimates the measured WRFs, whereas the PTF-AH provided negative MRE values indicating an overall overestimation. The outcomes of our study provide a critical evaluation when using calibration-free PTFs to predict WRFs over large areas</p>Ugo LazzaroCaterina MazzitelliBenedetto SicaPaola Di FioreNunzio RomanoPaolo Nasta
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2023-10-262023-10-2654410.4081/jae.2023.1542Definition of thermal comfort of crops within naturally ventilated greenhouses
https://www.agroengineering.org/jae/article/view/1540
<p>Controlling the microclimate condition inside a greenhouse is very important to ensure the best indoor conditions for both crop growth and crop production. To this regard, this paper provides the results of a novel approach to study a greenhouse, aiming to define a porous media model simulating the crop presence. As first, an experimental campaign has been carried out to evaluate air temperature and air velocity distributions in a naturally ventilated greenhouse with sweet pepper plants cultivated in pots. Then, the main aspects of energy balance, in terms of mass transfer and heat exchange, and both indoor and outdoor climate conditions have been combined to set up a computational fluid dynamics model. In the model, in order to simulate the crop presence and its effects, an isotropic porous medium following Darcy’s law has been defined based on the physical characteristics of the crops. The results show that the porous medium model could accurately simulate the heat and mass transfer between crops, air, and soil. Moreover, the adoption of this model helps to clarify the mechanism of thermal exchanges between crop and indoor microclimate and allows to assess in more realistic ways the microclimate conditions close to the crops.</p>Shahad Al-RikabiEnrica SantoliniBeatrice PulvirentiMarco BovoAlberto BarbaresiDaniele TorreggianiPatrizia Tassinari
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2023-10-252023-10-2554410.4081/jae.2023.1540Design and experiment of brush-roller ginkgo leaf picker for the dwarf dense planting mode
https://www.agroengineering.org/jae/article/view/1541
<p>At present, ginkgo leaves are still picked manually. A brush roller ginkgo leaf picker has been designed to improve harvesting efficiency and reduce losses caused by manual failure to pick leaves in time under large-scale planting areas. The ginkgo leaf picker is mainly composed of crawler chassis, gantry frame, brush roller picking parts, and collecting box. The kinematics of the brush roller are analyzed for the picking omission situation. An experimental platform for picking ginkgo biloba leaves was established. Three parameters, namely roller speed, moving speed, and roller inclination were selected for optimization. Then the maximum net harvest rate and the minimum damage rate were achieved. The orthogonal test showed that when the roller speed was 130 rev/min, the moving speed was 0.25 m/s, and the roller inclination was 32°, the picking effect was the best, the net harvest rate was 93.32%, the damage rate was 1.42%, and the damage degree of the trunks was slight. The experiment proved that the brush-roller ginkgo leaf picker has a good picking effect, which can provide a reference for the optimization design of ginkgo leaf harvesting machinery under the dwarf dense planting mode.</p>Shanwen ZhangYongyuan SunSu LuLi WangSian LiuZhongliu WangMin DaiJicheng GaoHong Miao
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2023-10-252023-10-2554410.4081/jae.2023.1541Green infrastructure planning based on ecosystem services multicriteria evaluation: the case of the metropolitan wine landscapes of Bordeaux
https://www.agroengineering.org/jae/article/view/1531
<p>Excessive anthropogenic activities affect landscape patterns and trigger a decrease in natural capital and the quality of life. Green infrastructures (GIs) are commonly accepted by scholars as solutions for restoring degraded areas and providing a variety of ecosystem services (ESs). On the other hand, the capacity to deliver ESs can be assumed as a relevant starting point for GIs analysis and planning. The assessment of ESs needs extensive investigation and applications to provide planners, policymakers, and institutional stakeholders with an adequate evaluation tool. The multifaceted nature of ES assessment implies the use of complex tools able to consider many concerns. In this regard, multicriteria analysis (MCA) is a very popular tool due to its capacity to intertwine a variety of issues rigorously and to support participatory and transparent decision-making in the public domain. In this study, we aim to contribute to the integration of GI design into spatial planning, starting with the assessment of the net benefit delivered to local society by a GI in the metropolitan area of Bordeaux (France). We assessed the net benefit by confronting the ESs deliverable by the GI and the cost sustained for its construction and maintenance. We applied an MCA-based method to the selection of the most efficient alternative out of three GI paths. We demonstrate that our method is useful for the assessment of cultural and regulating ESs, comparing the GI design alternatives, and considering the preference model of the stakeholders within GI planning and design.</p>Giovanna CaliaVittorio SerraAntonio LeddaAndrea De Montis
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2023-08-042023-08-0454410.4081/jae.2023.1531Hyperspectral prediction of pigment content in tomato leaves based on logistic-optimized sparrow search algorithm and back propagation neural network
https://www.agroengineering.org/jae/article/view/1528
<p>Leaf pigment content can reflect the nutrient content of the cultivation medium indirectly. To rapidly and accurately predict the pigment content of tomato leaves, chlorophyll a, chlorophyll b, chlorophyll and carotenoid were extracted from the leaves of tomato seedlings cultured at different nitrogen concentrations. The visible/near-infrared hyperspectral imaging non-destructive measurement technology, 430-900 nm and 950-1650 nm, with total variables of 794, was used to obtain the reflection spectra of leaves. An improved strategy of the sparrow search algorithm (SSA) based on logistic chaotic mapping was proposed, and it optimized the back propagation neural network to predict the pigment content of leaves. Different pretreatment methods were used to effectively improve the prediction accuracy of the model. The results showed that when the nitrogen concentration in the nutrient solution was 302.84 mg·L-1, the pigment content of the leaves reached its maximum. Meanwhile, the inhibition effect of high concentrations was much stronger than that of low concentrations. To address the problem that the SSA is prone to premature convergence due to the reduction of population diversity at the end of the iteration, the initialization of the SSA population by logistic chaotic mapping improves the initial solution quality, convergence speed, and search capacity. The root mean squared error (RMSE), coefficient of determination (R2) and relative percent deviation (RPD) of chlorophyll a were 0.77, 0.77, and 2.08, respectively. The RMSE, R2 and RPD of chlorophyll b were 0.30, 0.66, and 1.71, respectively. The RMSE, R2 and RPD of chlorophyll were 0.88, 0.81, and 2.28, respectively. The RMSE, R2 and RPD of carotenoid were 0.14, 0.75, and 2.00, respectively. Hyperspectral imaging technology combined with machine learning algorithms can achieve rapid and accurate prediction of crop physiological information, providing data support for the precise management of fertilization in facility agriculture, which is conducive to improving the quality and output of tomatoes.</p>Jiangui ZhaoTingyu ZhuZhichao QiuTao LiGuoliang WangZhiwei LiHuiling Du
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2023-06-202023-06-2054410.4081/jae.2023.1528Definition of linear regression models to calculate the technical parameters of Italian agricultural tractors
https://www.agroengineering.org/jae/article/view/1525
<p style="font-weight: 400;">As it is known, the modern agricultural tractor is no longer just a machine capable to pull agricultural trailers and to operate implements but has evolved into a multi-purpose and mobile energy source with standardized interfaces (mechanical, hydraulic and electronic) to connect to a several typologies of agricultural operating machines. It follows that the selection of the most appropriate tractors for the specific production realities is a crucial aspect for farmers, advisors, contractors and farm machinery experts. The tractors choice thus must consider different parameters, concerning not only the cost of the machines but also their dimensions, power, weight, technological level, <em>etc</em>. The availability of simplified models for estimating the purchase investment and sizing the machine in relation to its mechanical characteristics could be a useful tool in the choice of the tractor more suitable for the specific agricultural context. The aim of this study was to collect and to analyse the technical parameters of tractors present on the Italian market (more than 1300 models), divided into: i) four wheel-drive (4WD) standard tractors, ii) two wheel-drive (2WD) standard tractors, iii) narrow track 4WD tractors, iv) Isodiametric specialized 4WD tractors, v) crawler tractors and vi) rubber-tracked tractors), in order to define the most relevant parameter-to-parameter and parameter-to-price relations for updating reference models to calculate the machine price and the weight to engine power ratio. Other relations, including the three-point hitch efficiency with respect to tractor’s weight and the relationship between the rated engine power and its displacement, are proposed in order to provide synthetic tools to characterise and to compare - from the mechanical point of view - the different categories of agricultural tractors.</p>Aldo CalcanteRoberto ObertiFrancesco M. Tangorra
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2023-06-162023-06-1654410.4081/jae.2023.1525Agricultural machinery photoelectric automatic navigation control system based on back propagation neural network
https://www.agroengineering.org/jae/article/view/1530
<p>To study the influence of speed factors on the stability of a tractor automatic navigation system, combined with the neural network control theory, the authors proposed a dual-objective joint sliding mode control method based on lateral position deviation and heading angle deviation, using a back propagation neural network to establish a two-wheel tractor-path dynamics model and a straight-line path tracking deviation model. The overall system simulation was carried out using Matlab/Simulink, and the reliability of the control method was verified. The experimental results showed that when the tractor was tracked with the automatic control of a linear path under the condition of variable speed, the maximum deviation of the lateral position deviation was 12.7 cm, and the average absolute deviation was kept within 4.88 cm; the maximum deviation of the heading angle deviation was 5°, and the average absolute deviation was kept within 2°; the maximum value of the actual rotation angle was 3.13°, and the standard deviation of the fluctuation was within 0.84°. Under the conditions of constant speed and variable speed, using the joint sliding mode control method designed by the authors, the dual-objective joint control of lateral position deviation and heading angle deviation could be realized, the controlled overshoot was small, the controlled deviation was small after reaching a stable state, and the adaptability to speed factors was strong, which basically could meet the accuracy requirements of farmland operations.</p>Yerong SunKechuan Yi
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2023-07-052023-07-0554410.4081/jae.2023.1530Assessment of the ecosystem services given by rural and urban green areas to preserve high-quality territories from land take: the case of the province of Monza Brianza (Italy)
https://www.agroengineering.org/jae/article/view/1526
<p>Rural and urban green areas are essential territories that support life and ecosystems. The significant reduction of these areas due to urbanization is a pressing issue. The process of land take consumes not only land resources but also the connected ecosystems and the benefits generated for human society. Reducing the quantity of land taken is imperative, but preserving high-quality territories is essential to achieving sustainable development. Evaluating the quality of non-urbanized areas can be done by assessing the ecosystem services (ESs) provided by these areas. In this paper, the authors present a further step: an evolution and deepening of the previous methodology (published in 2020) to evaluate the quality of rural and urban green areas through the assessment of the ESs provided. The methodology first allows the identification of the ESs provided by different typologies of rural and urban green areas according to the common international classification of ESs (provisioning, regulation and maintenance, and cultural). Then, it allows the calculation of several singular indexes and a final composite quality index through the use of geographical information systems. An analytic hierarchy process was performed with the creation of different scenarios to consider the different importance of the singular indexes assigned by planners and communities involved. The methodology was applied to the province of Monza Brianza (Italy), for testing and validation purposes. The application to the municipality of Sovico, which is presented in this report, allowed for the identification of areas with higher quality in the different scenarios that were created to consider the relative importance of the territorial characteristics.</p>Giulio SenesNatalia FumagalliPaolo Stefano FerrarioRoberto RovelliFederico RivaGiovanna SacchiPaolo GambaGiacomo RuffiniGiacomo Redondi
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2023-06-162023-06-1654410.4081/jae.2023.1526Hyperspectral imaging system to online monitoring the soy flour content in a functional pasta
https://www.agroengineering.org/jae/article/view/1535
<p>Pasta enriched with soy flour can be considered as a functional food, due to its content in nutraceutical compounds such as isoflavones, carotenoids, and other antioxidants. The quantification of the amount of a functional ingredient is an important step in food authenticity. The availability of non-destructive techniques for quantitative and qualitative analyses of food is therefore desirable. This research aimed to investigate the feasibility of hyperspectral imaging in reflectance mode for the evaluation of the soy flour content, also to investigate the possibility of implementing a feed-back control system to precisely dose the soy flour during the industrial production of pasta. Samples of pasta in shape of spaghetti were produced with durum wheat semolina and soy flour at increasing percentages (0, to 50%, steps of 5%). A feature selection algorithm was used to predict the amount of soy flour. The most influent wavelengths were selected, and a six-term Gauss function was trained, validated, and tested. The identified transfer function was able to predict the percentage of soy flour with high accuracy, with an R2adj value of 0.98 and a Root Mean Square Error of 1.31. The developed system could represent a feasible tool to control the process in a continuous mode.</p>Roberto RomanielloAntonietta Eliana BarrassoAntonio BerardiClaudio PeroneAntonia TamborrinoFilippo CatalanoAntonietta Baiano
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2023-08-042023-08-0454410.4081/jae.2023.1535A review of the discrete element method/modelling in agricultural engineering
https://www.agroengineering.org/jae/article/view/1534
<p>With the development of high-performance computing technology, the number of scientific publications regarding computational modelling of applications with the Discrete Element Method/Modelling (DEM) approaches in agricultural engineering has risen in the past decades. Many granular materials, <em>e.g.</em> grains, fruits and soils in agricultural engineering are processed, and thus a better understanding of these granular media with DEM is of great significance in design and optimization of tools and process in agricultural engineering. In this review, the theory and background of DEM have been introduced. Some improved contact models discussed in the literature for accurately predicting the contact force between two interacting particles have been compared. Accurate approximation of irregular particle shapes is of great importance in DEM simulations to model real particles in agricultural engineering. New algorithms to approximate irregular particle shapes, e.g. overlapping multi-sphere approach, ellipsoid, <em>etc.,</em> have been summarized. Some remarkable engineering applications of the improved numerical models developed and implemented in DEM are discussed. Finally, potential applications of DEM and some suggested further works are addressed in the last section of this review.</p>Qing GuoHuihuang Xia
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2023-08-042023-08-0454410.4081/jae.2023.1534