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AgriEngineering, Volume 1, Issue 4 (December 2019) – 8 articles

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19 pages, 4267 KiB  
Article
Integration of Soil Electrical Conductivity and Indices Obtained through Satellite Imagery for Differential Management of Pasture Fertilization
by João Serrano, Shakib Shahidian, José Marques da Silva, Luís Paixão, José Calado and Mário de Carvalho
AgriEngineering 2019, 1(4), 567-585; https://doi.org/10.3390/agriengineering1040041 - 2 Dec 2019
Cited by 21 | Viewed by 4056
Abstract
Dryland pastures in the Alentejo region, located in the south of Portugal, normally occupy soils that have low fertility but, simultaneously, important spatial variability. Rational application of fertilizers requires knowledge of spatial variability of soil characteristics and crop response, which reinforces the interest [...] Read more.
Dryland pastures in the Alentejo region, located in the south of Portugal, normally occupy soils that have low fertility but, simultaneously, important spatial variability. Rational application of fertilizers requires knowledge of spatial variability of soil characteristics and crop response, which reinforces the interest of technologies that facilitates the identification of homogeneous management zones (HMZ). In this work, a pasture field of about 25 ha, integrated in the Montado mixed ecosystem (agro-silvo-pastoral), was monitored. Surveys of apparent soil electrical conductivity (ECa) were carried out in November 2017 and October 2018 with a Veris 2000 XA contact sensor. A total of 24 sampling points (30 × 30 m) were established in tree-free zones to allow readings of normalized difference vegetation index (NDVI) and normalized difference water index (NDWI). Historical time series of these indices were obtained from satellite imagery (Sentinel-2) in winter and spring 2017 and 2018. Three zones with different potential productivity were defined based on the results obtained in terms of spatial variability and temporal stability of the measured parameters. These are the basis for the elaboration of differentiated prescription maps of fertilizers with variable application rate technology, taking into account the variability of soil characteristics and pasture development, contributing to the sustainability of this ecosystem. Full article
(This article belongs to the Special Issue Selected Papers from 10th Iberian Agroengineering Congress)
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Figure 1
<p>Schematic representation of the steps proposed in this work for establishing homogeneous management zones.</p>
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<p>Limit of the experimental field with approximate location of the 24 sampling areas (<b>a</b>) and respective altimetry map (<b>b</b>).</p>
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<p>Soil electrical conductivity (EC<sub>a</sub>) maps of experimental field in November 2017 (<b>a</b>) and October 2018 (<b>b</b>) at 0–0.30 m depth.</p>
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<p>Soil clay (<b>a</b>) and cation exchange capacity (CEC) (<b>b</b>) maps of experimental field in November 2017 at 0–0.30 m depth.</p>
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<p>(<b>a</b>) Soil organic matter (OM) and phosphorus (P<sub>2</sub>O<sub>5</sub>) (<b>b</b>) maps of experimental field in November 2017 at 0–0.30 m depth.</p>
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<p>Normalized difference vegetation index (NDVI) (<b>a</b>) and normalized difference water index (NDWI) (<b>b</b>) maps of experimental field: Mean of historical time series records of Sentinel-2 optical images captured between Winter and Spring of 2017 and 2018.</p>
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<p>(<b>a</b>) Maps of management classes of the experimental field based on soil electrical conductivity (EC<sub>a</sub>); (<b>b</b>) normalized difference vegetation index (NDVI); and (<b>c</b>) normalized difference water index (NDWI). Legend: 1—Greater than field mean value of parameter and stable; 2—Greater than field mean value of parameter and moderately stable; 3—Less than field mean value of parameter and stable; 4—Less than field mean value of parameter and moderately stable; 5—Unstable.</p>
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<p>Potential cumulative map of experimental field.</p>
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<p>Relationship between mean soil electrical conductivity (EC<sub>a</sub>) and mean soil moisture content (SMC) of experimental field at 0–0.30 m depth.</p>
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<p>Relationship between mean values of normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) of experimental field at 0–0.30: Historical time series records of Sentinel-2 optical images captured between Winter and Spring of 2017 and 2018.</p>
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<p>Relationship between normalized difference vegetation index (NDVI) and: (<b>a</b>) Pasture productivity (green matter, GM); (<b>b</b>) pasture quality (crude protein, CP) of experimental field in 10 May 2018.</p>
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<p>Phosphorus prescription map (P<sub>2</sub>O<sub>5</sub> application levels) proposed for the experimental field based in three homogenous management zones (HMZ).</p>
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17 pages, 3644 KiB  
Article
Development and Identification of Working Parameters for a Lychee Peeling Machine Combining Rollers and a Pressing Belt
by Lu Minh Le, Thong Chung Nguyen, Binh Thai Pham, Hai-Bang Ly, Vuong Minh Le and Tien-Thinh Le
AgriEngineering 2019, 1(4), 550-566; https://doi.org/10.3390/agriengineering1040040 - 18 Nov 2019
Cited by 6 | Viewed by 6045
Abstract
This work describes the development, design, and parameter identification of a lychee peeling machine. The working principle of the machine combines two rollers with a pressing belt to separate the peel from the fruits. It was designed and its operational parameters identified on [...] Read more.
This work describes the development, design, and parameter identification of a lychee peeling machine. The working principle of the machine combines two rollers with a pressing belt to separate the peel from the fruits. It was designed and its operational parameters identified on the basis of experimental data on the Thieu lychee, which currently covers about 80% of the plantation area in Vietnam. To this end, the first step was to measure the physical characteristics of the fruits, such as size, shape, and density. Moreover, the coefficient of static friction between lychees and rubber rollers, and the critical peeling force, were identified, with a view to optimizing the operational parameters later on. Results showed that a minimum tangential force of 10.5 N is needed to break the peel and separate it from the pulp. Based on the balanced force principle, various optimal machine parameters such as roller rotation speed, roller diameter, roller length, gap size between the two rollers, belt velocity, and minimum pressure of the belt were calibrated. In addition, spiral grooves were created on the roller surface to facilitate the motion of the fruits. The optimal results were roller size 900 × 100 mm (length × diameter), rotation speed 159 RPM, gap size between rollers 4 mm, belt size 850 × 60 mm (length × width), belt pressure 13.5 N, and belt velocity 140 mm/s. Using the design and operational parameters mentioned above, the machine was able to perform regularly at a throughput of 100 kg/h, as demanded by the current market. Moreover, it would be easily feasible to combine multiple pairs of rollers and pressing belts in order to increase throughput. The methodology for the design of this peeling machine and identification of working parameters with respect to experimental data could be applied in many other post-harvesting configurations. Full article
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Figure 1
<p>Visualisation of lychee fruits: (<b>a</b>) clusters and (<b>b</b>) composition of lychee fruit: (b-1) peel; (b-2) flesh, and (b-3) seed.</p>
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<p>Mettler Toledo MS1602S electronic scale used in this study.</p>
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<p>Diagram of experimental setup to determine critical peeling force.</p>
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<p>GuntTM22 device for measuring coefficient of friction.</p>
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<p>Diagram of the peeling part of the machine—(1) pressing belt; (2) lychee fruit; (3) rollers.</p>
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<p>Diagram of the peeling machine—(1) sorting conveyor; (2) gutter, (3) blade; (4) rubber-covered roller; (5) collection bin; (6) screw; (7) machine part for collecting juice; (8) pressing belt; (9) conveyor of peeled fruits; (10) spiral groove on the roller surface.</p>
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<p>Flowchart methodology of the present study.</p>
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<p>Diagram of forces exerted on the fruit when rollers are at rest.</p>
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<p>Diagram of forces exerted on the fruit when rollers are rotating.</p>
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<p>Diagram illustrating the influence of roller diameter and gap size. (<b>a</b>) When roller diameter and gap size are large; (<b>b</b>) When roller diameter and gap size are small.</p>
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<p>Assembly of different parts by Autodesk Inventor: (1) rollers; (2) gear box, (3) engine; (4) collection of peels; (5) spiral groove; (6) conveyor of peeled fruits; (7) pressing belt; (8) sorting conveyor; (9) blade; (10) hopper.</p>
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11 pages, 3727 KiB  
Technical Note
Thermal Performance of Double-Sided Metal Core PCBs
by Mathew G. Pelletier, Stone C. Preston, Jim A. Cook, Kevin D. Tran, John D. Wanjura and Greg A. Holt
AgriEngineering 2019, 1(4), 539-549; https://doi.org/10.3390/agriengineering1040039 - 13 Nov 2019
Cited by 1 | Viewed by 3772
Abstract
Thermal management in printed circuit boards is becoming increasingly more important as the use of LEDs is now widespread across all industries. Due to availability of the preferred electronic LED current drivers and system constraints for a machine-vision application, the design dictated the [...] Read more.
Thermal management in printed circuit boards is becoming increasingly more important as the use of LEDs is now widespread across all industries. Due to availability of the preferred electronic LED current drivers and system constraints for a machine-vision application, the design dictated the need for a double-sided metal core printed circuit board (MCPCB). However, design information for this relatively new MCPCB offering is sparse to non-existent. To fill-in this missing information in the literature, experiments were conducted where LEDs were arranged on a double-sided metal core printed circuit board (MCPCB), and their impact on the board temperature distribution was tested in a static fan-less configuration where the first condition was at room temperature, 23 °C, and the second configuration was for a heated environment, 40 °C. Two MCPCB orientations were tested (vertical and horizontal). Additionally, several LED arrangements on the MCPCB were configured, and temperatures were measured using a thermocouple as well as with a deep-infrared thermal imaging camera. Maximum temperatures were found to be 65.3 °C for the room temperature tests and 96.4 °C for the heated tests with high temperatures found in near proximity to the heat sources (LEDs), indicating less than ideal heat-conduction/dissipation by the MCPCB. The results indicate that the double-sided MCPCB topology is not efficient for high thermally loaded systems, especially when the target is a fan-less system. The results of testing indicate that for fan-less systems requiring high-performance heat-transfer, these new MCPCB are not a suitable design alternative, and instead, designers should stick with the more traditional single-sided metal-back PCB. Full article
(This article belongs to the Special Issue Robotics and Automation Engineering in Agriculture)
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Figure 1
<p>(<b>a</b>) Typical single-sided metal-core printed circuit board, MCPCB, Stack-Up design (<b>b</b>) Double-Sided MCPCB Stack-Up design.</p>
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<p>(<b>a</b>) LED group position layout configuration (<b>b</b>) and associated printed-circuit-board, PCB, design schematic utilized in the thermal dissipation experiments.</p>
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<p>Temperature vs. time plots of LED configurations for room temperature tests.</p>
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<p>Thermal infrared temperature image of configuration 5 at time, t = 11 min.</p>
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<p>Infrared temperature transects, from <a href="#agriengineering-01-00039-f004" class="html-fig">Figure 4</a>, for 20 °C room temperature test, configuration 5, snapshot shown at time, t = 11 min.</p>
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<p>Figure details the hottest location on the printed-circuit-board’s temperature vs. time for the room heated tests, for configuration 1, in both horizontal and vertical orientations of the circuit-board.</p>
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<p>Thermal infrared temperature image of the heated room test, configuration 1, at time t = 21 min, with the circuit-board oriented horizontally.</p>
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<p>Temperatures across the thermal infrared image transects of <a href="#agriengineering-01-00039-f007" class="html-fig">Figure 7</a>, for the heated-room, configuration 1 test with circuit-board in horizontal orientation, at time t = 21 min.</p>
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<p>Thermal infrared temperature image of heated-room test, configuration 1, for circuit-board in vertical orientation, at time t = 19 min.</p>
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<p>Temperatures across the thermal-infrared image transects, for heated-room test, configuration 1, for circuit-board in vertical orientation, at time t = 19 min.</p>
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16 pages, 11608 KiB  
Technical Note
Electronic Design of a Cotton Harvester Yield Monitor Calibration System
by Mathew G. Pelletier, John D. Wanjura and Greg A. Holt
AgriEngineering 2019, 1(4), 523-538; https://doi.org/10.3390/agriengineering1040038 - 22 Oct 2019
Cited by 5 | Viewed by 4218
Abstract
Several yield monitors are available for use on cotton harvesters, but none are able to maintain yield measurement accuracy across cultivars and field conditions that vary spatially and/or temporally. Thus, the utility of yield monitors as tools for on-farm research is limited unless [...] Read more.
Several yield monitors are available for use on cotton harvesters, but none are able to maintain yield measurement accuracy across cultivars and field conditions that vary spatially and/or temporally. Thus, the utility of yield monitors as tools for on-farm research is limited unless steps are taken to calibrate the systems as cultivars and conditions change. This technical note details the electronic system design for a harvester-based yield monitor calibration system for basket-type cotton strippers. The system was based upon the use of pressure sensors to measure the weight of the basket by monitoring the static pressure in the hydraulic lift cylinder circuit. To ensure accurate weighing, the system automatically lifted the basket to a target lift height, allowed the basket time to settle, then weighed the contents of the basket. The software running the system was split into two parts that were run on an embedded low-level micro-controller and a mobile computer located in the harvester cab. The system was field tested under commercial conditions and found to measure basket load weights within 2.5% of the reference scale. As such, the system was proven to be capable of providing an on-board auto-correction to a yield monitor for use in multi-variety field trials. Full article
(This article belongs to the Special Issue Robotics and Automation Engineering in Agriculture)
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Figure 1

Figure 1
<p>The printed circuit artwork for a vehicular load-dump spike-resistant hydraulic controller and precision 22-bit analog-to-digital converter that forms the heart of the cotton harvester’s basket weighing system. Section A is the analog sub-section, section B is the digital microcontroller section and section C is the power regulation and output solenoid drivers. The air points to the separation of the ground plane that provides isolation for the sensitive analog section from the noise in the digital section.</p>
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<p>The printed-circuit-board, PCB for a vehicular load-dump spike-resistant hydraulic controller and precision 22-bit analog-to-digital converter that forms the heart of the cotton harvester’s basket weighing system.</p>
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<p>The schematic for a vehicular load-dump spike-resistant interface between the harvester’s high-voltage, high-noise 12 Volt-Direct-Current, VDC, power to the systems low-noise linear regulator that was used to convert from the harvester’s 12 VDC power to the system’s first voltage regulation 11.5 VDC stage. Component values for this figure provided in <a href="#agriengineering-01-00038-t001" class="html-table">Table 1</a>.</p>
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<p>The schematic of a very low-noise linear regulator that was used to convert from the system’s 11.5 VDC first stage power to the system’s precision 5 V stage. Component values for this figure provided in <a href="#agriengineering-01-00038-t002" class="html-table">Table 2</a>.</p>
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<p>The schematic of the third-stage low-noise linear regulator that was used to convert from the system’s second stage 5 VDC power to the digital 3.3 VDC supply to the micro-controller. Component values for this figure provided in <a href="#agriengineering-01-00038-t003" class="html-table">Table 3</a>.</p>
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<p>The schematic for the Analog Devices precision voltage references (ADR4520) that were used to provide both the 2.0 V reference (<b>a</b>), as well as the 3.3 V power to supply all the analog integrated circuits (<b>b</b>). Component values for this figure are provided in the <a href="#agriengineering-01-00038-t004" class="html-table">Table 4</a>.</p>
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<p>The schematic of the LC filters that were used to help isolate the analog plane from the rest of the digital circuits on the printed circuit board. Component values for this figure provided in <a href="#agriengineering-01-00038-t005" class="html-table">Table 5</a>.</p>
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<p>The schematic of the bridge amplifier that is connected directly to the bridge-style pressure sensor. Component values for this figure are provided in <a href="#agriengineering-01-00038-t006" class="html-table">Table 6</a>.</p>
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<p>The schematic of the two stage unity-gain Sallen–Key low-pass filters [<a href="#B22-agriengineering-01-00038" class="html-bibr">22</a>] that are cascaded in series, as the instrumentation section’s main noise rejection filter that immediately follows the bridge amplifier section. Component values for this figure provided in <a href="#agriengineering-01-00038-t007" class="html-table">Table 7</a>.</p>
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<p>Filter response that achieved greater than 80 dB noise-rejection roll-off for the frequency response of both stages of this filter as configured per the schematic in <a href="#agriengineering-01-00038-f009" class="html-fig">Figure 9</a>.</p>
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<p>The schematic design for the 22-bit analog-to-digital converter, MCP3553, that is used as the final section of the analog subsection. Component values for this figure provided in <a href="#agriengineering-01-00038-t008" class="html-table">Table 8</a>.</p>
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<p>The schematic of the low-voltage serial-to-RS232 converter that was used to communicate between the micro-controller and the industrial PC in the harvester’s cab that provided the operator interface. Component values for this figure are provided in <a href="#agriengineering-01-00038-t009" class="html-table">Table 9</a>.</p>
Full article ">Figure 13
<p>The schematic of the micro-controller that provided control of the feedback control system used to lift the harvester’s basket to the weigh position as well as provide the control and interface to the system’s 22-bit ADC and communication back to the industrial PC in the harvester’s cab which provided the operator interface. Component values for this figure are provided in <a href="#agriengineering-01-00038-t010" class="html-table">Table 10</a>.</p>
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<p>The schematic detail for one of the Omron solid-state relays, SSR (G3VM), that were used to drive the hydraulic solenoids that were plumbed into the tractor’s basket hydraulic lift cylinders. Component values for this figure are provided in <a href="#agriengineering-01-00038-t011" class="html-table">Table 11</a>.</p>
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<p>The mounting location of the two limit switches, inset box A in both images, that let the micro-controller know when the basket is in the weigh position. The arrow in the image (<b>a</b>) is pointing to the roller arm on the second, final destination, limit switch that senses when the basket passes this location and has arrived at its target weighing height. Large view (<b>b</b>) shows where on the harvester the limit switch is mounted.</p>
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12 pages, 2531 KiB  
Technical Note
Man-Machine-Interface Software Design of a Cotton Harvester Yield Monitor Calibration System
by Mathew G. Pelletier, John D. Wanjura and Greg A. Holt
AgriEngineering 2019, 1(4), 511-522; https://doi.org/10.3390/agriengineering1040037 - 21 Oct 2019
Cited by 6 | Viewed by 3709
Abstract
Several yield monitors are available for use on cotton harvesters, but none are able to maintain yield measurement accuracy across cultivars and field conditions that vary spatially and/or temporally. Thus, the utility of yield monitors as tools for on-farm research is limited unless [...] Read more.
Several yield monitors are available for use on cotton harvesters, but none are able to maintain yield measurement accuracy across cultivars and field conditions that vary spatially and/or temporally. Thus, the utility of yield monitors as tools for on-farm research is limited unless steps are taken to calibrate the systems as cultivars and conditions change. This technical note details the man-machine-interface software system design portion of a harvester-based yield monitor calibration system for basket-type cotton strippers. The system was based upon the use of pressure sensors to measure the weight of the basket by monitoring the static pressure in the hydraulic lift cylinder circuit. To ensure accurate weighing, the system automatically lifted the basket to a target lift height, allowed basket time to settle, then weighed the contents of the basket. The software running the system was split into two parts that were run on an embedded low-level micro-controller, and a mobile computer located in the harvester cab. The system was field tested under commercial conditions and found to measure basket load weights within 2.5% of the reference scale. As such, the system was proven to be capable of providing an on-board auto-correction to a yield monitor for use in multi-variety field trials. Full article
(This article belongs to the Special Issue Robotics and Automation Engineering in Agriculture)
Show Figures

Figure 1

Figure 1
<p>The main screen that provides the main operator interface screen provides the main user interface to control the harvester yield monitor calibration system.</p>
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<p>The setup screen that allows for user input so the software can associate the client-farm-field information with the subsequent data-acquisitions.</p>
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<p>The state diagram that describes the flow for the main program loop in the man-machine-interface software.</p>
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<p>The state-diagram chart for the global-positioning-satellite-system, GPS, serial receive and processing functions that perform key functions inside the main processing loop of the man-machine-interface software.</p>
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<p>The flow chart for the GPS serial receive function that operates inside the main-loop of the man-machine-interface software.</p>
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<p>Spherical triangle solved by the law of haversines, equations [<a href="#B1-agriengineering-01-00037" class="html-bibr">1</a>,<a href="#B2-agriengineering-01-00037" class="html-bibr">2</a>,<a href="#B3-agriengineering-01-00037" class="html-bibr">3</a>].</p>
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<p>The state-diagram chart for the GPS serial receive function that forms one of the key events the main loop for the man-machine-interface software.</p>
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<p>The C++ class definitions used in the man-machine-interface software. In the figure’s class specifications, the leading ‘+’ signifies public functions. While the leading ‘-‘ signifies private functions and the leading ‘<span>$</span>’ signifies event response function, SLOT, that are called and used by the windowing event loop structures. The SLOT functions provide the equivalent of an interrupt service routine that frees up active process from having to continuously poll various resources for data event occurrences. The class structure is flat with no inheritance by any of the classes; the arrows between classes only indicate which class is calling other classes by means of publicly visible functions.</p>
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15 pages, 2005 KiB  
Article
Ultrasound-Enhanced Hot Air Drying of Germinated Highland Barley Seeds: Drying Characteristics, Microstructure, and Bioactive Profile
by Yan Song, Yang Tao, Xiaoyu Zhu, Yongbin Han, Pau Loke Show, Changnain Song and Hayyiratul Fatimah Mohd Zaid
AgriEngineering 2019, 1(4), 496-510; https://doi.org/10.3390/agriengineering1040036 - 14 Oct 2019
Cited by 10 | Viewed by 3492
Abstract
The effects of ultrasound-enhanced hot air drying on the drying characteristics, microstructure and bioactive profile of germinated highland barley seeds (GHB) were studied. GHB was dried by hot air at 55 °C and 70 °C and ultrasonic intensities of 125.1 W/dm2 and [...] Read more.
The effects of ultrasound-enhanced hot air drying on the drying characteristics, microstructure and bioactive profile of germinated highland barley seeds (GHB) were studied. GHB was dried by hot air at 55 °C and 70 °C and ultrasonic intensities of 125.1 W/dm2 and 180.2 W/dm2, respectively. The results showed that when the drying temperature was 55 °C or 70 °C, the sonicated groups could shorten the drying time by 17.4–26.1% or 18.8–31.3%, respectively. Ultrasound drying at 125.1 W/dm2 and 55 °C could mostly increase the content of organic selenium and the rehydration rate, improve the color and maintain the original structure of GHB. Compared with hot air drying alone, the phenolic content did not increase due to ultrasound-enhanced hot air drying. Therefore, drying at an ultrasonic intensity of 125.1 W/dm2 and a temperature of 55 °C could effectively shorten the drying time, and enhance the quality of GHB. Full article
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Figure 1
<p>Schematic diagram of ultrasonic assisted hot air drying equipment. 1: ultrasonic generator; 2: drying chamber; 3: tray; 4: ultrasonic transducer; 5: thermometer; 6: anemometer.</p>
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<p>Drying curves of germinated highland barley seeds(GHB) under different temperatures: (<b>a</b>) 55 °C; (<b>b</b>) 70 °C. DM: dry matter.</p>
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<p>Drying rate curves of GHB under different temperatures: (<b>a</b>) 55 °C; (<b>b</b>) 70 °C.</p>
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<p>Shrinkage of GHB under different temperatures: (<b>a</b>) 55 °C; (<b>b</b>) 70 °C.</p>
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<p>Scanning electron micrographs (SEM) of GHB microstructure under different drying methods: (<b>a</b>) before drying; (<b>b</b>) dried at 55 °C; (<b>c</b>) dried at 55 °C and 125.1 W/dm<sup>2</sup>; and (<b>d</b>) dried at 55 °C and 180.2 W/dm<sup>2</sup>.</p>
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<p>Effects of different drying methods on rehydration of GHB. Note: 55–0 is drying at 55 °C without sonication; 55–125.1 is drying at 55 °C and 125.1 W/dm<sup>2</sup>; 55–180.2 is drying at 55 °C and 180.2 W/dm<sup>2</sup>; 70–0 is drying at 70 °C without sonication; 70–125.1 is drying at 70 °C and 125.1 W/dm<sup>2</sup>; 70–180.2 is drying at 70 °C and 180.2 W/dm<sup>2</sup>. Different letters indicate significant differences in different drying methods (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effects of different drying methods on the contents of (<b>a</b>) organic selenium, (<b>b</b>) free phenolic, (<b>c</b>) bound phenolic, and (<b>d</b>) total phenolic in GHB. Note: 1.55–0 is drying at 55 °C without sonication; 55–125.1 is drying at 55 °C and 125.1 W/dm<sup>2</sup>; 55–180.2 is drying at 55 °C and 180.2 W/dm<sup>2</sup>; 70–0 is drying at 70 °C without sonication; 70–125.1 is drying at 70 °C and 125.1 W/dm<sup>2</sup>; 70–180.2 is drying at 70 °C and 180.2 W/dm<sup>2</sup>. Different letters indicate significant differences in different drying methods (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 7 Cont.
<p>Effects of different drying methods on the contents of (<b>a</b>) organic selenium, (<b>b</b>) free phenolic, (<b>c</b>) bound phenolic, and (<b>d</b>) total phenolic in GHB. Note: 1.55–0 is drying at 55 °C without sonication; 55–125.1 is drying at 55 °C and 125.1 W/dm<sup>2</sup>; 55–180.2 is drying at 55 °C and 180.2 W/dm<sup>2</sup>; 70–0 is drying at 70 °C without sonication; 70–125.1 is drying at 70 °C and 125.1 W/dm<sup>2</sup>; 70–180.2 is drying at 70 °C and 180.2 W/dm<sup>2</sup>. Different letters indicate significant differences in different drying methods (<span class="html-italic">p</span> &lt; 0.05).</p>
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11 pages, 3800 KiB  
Technical Note
Embedded Micro-Controller Software Design of a Cotton Harvester Yield Monitor Calibration System
by Mathew G. Pelletier, John D. Wanjura and Greg A. Holt
AgriEngineering 2019, 1(4), 485-495; https://doi.org/10.3390/agriengineering1040035 - 10 Oct 2019
Cited by 7 | Viewed by 3371
Abstract
Several yield monitors are available for use on cotton harvesters, but none are able to maintain yield measurement accuracy across cultivars and field conditions that vary spatially and/or temporally. Thus, the utility of yield monitors as tools for on-farm research is limited unless [...] Read more.
Several yield monitors are available for use on cotton harvesters, but none are able to maintain yield measurement accuracy across cultivars and field conditions that vary spatially and/or temporally. Thus, the utility of yield monitors as tools for on-farm research is limited unless steps are taken to calibrate the systems as cultivars and conditions change. This technical note details the embedded micro-controller software system design portion of a harvester-based yield monitor calibration system for basket-type cotton strippers. The system was based upon the use of pressure sensors to measure the weight of the basket by monitoring the static pressure in the hydraulic lift cylinder circuit. To ensure accurate weighing, the system automatically lifted the basket to a target lift height, allowed the basket time to settle, and then weighed the contents of the basket. The software running the system was split into two parts, which were run on an embedded low-level micro-controller and a mobile computer located in the harvester cab. The system was field tested under commercial conditions and found to measure basket load weights within 2.5% of the reference scale. As such, the system was proven to be capable of providing an on-board auto-correction to a yield monitor for use in multi-variety field trials. Full article
(This article belongs to the Special Issue Robotics and Automation Engineering in Agriculture)
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Figure 1

Figure 1
<p>The left-pane figure (<b>a</b>) of the picture shows the main loop that the micro-controller is performing. The “Run Scan” box in the left-pane is detailed in figure (<b>b</b>), where the system basically iterates through a custom list of possible operations that are provided by the calling client industrial computer. The figure (<b>c</b>) loop shows how the software builds up the custom Scan-List of operations that will be executed during the “Scan” phase portion of operation, which includes the pre-programmed initialization routines for the particular operation that was called into play.</p>
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<p>Pictures showing the mounting location of the two limit switches, inset box A in both images, that let the micro-controller know when the basket is in the weigh position. The arrow in image (<b>a</b>) is pointing to the roller arm on the second, final destination, limit switch that senses when the basket passes this location and has arrived at its target weighing height. (<b>b</b>) harvester.</p>
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<p>Picture detailing the flow-charts of the troubleshooting, delay only, basket lift routine. Figure pane (<b>a</b>) shows the high-level routine, pane (<b>b</b>) shows the Delay1 sub-routine, and pane (<b>c</b>) shows the Delay2 sub-routine.</p>
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<p>Picture detailing flow-charts of the feed-back controlled precise-placement basket lift routine. The figure pane (<b>a</b>) shows the main high-level loop of the function. Figure panes (<b>b</b>,<b>c</b>) depict the limit-switch wait sub-functions.</p>
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10 pages, 273 KiB  
Communication
Development of a Novel Enzymatic Pretreatment for Improving the Digestibility of Protein in Feather Meal
by Guillaume Pfeuti, Vernon Osborne, Anna K. Shoveller, Eric H. Ignatz and Dominique P. Bureau
AgriEngineering 2019, 1(4), 475-484; https://doi.org/10.3390/agriengineering1040034 - 7 Oct 2019
Cited by 4 | Viewed by 3798
Abstract
This study describes the process of developing an enzymatic pretreatment to improve the nutritional value of feather meal (FeM). In a first experiment, a full factorial design was used to examine the effects of various incubation conditions on the solubilization of nitrogen in [...] Read more.
This study describes the process of developing an enzymatic pretreatment to improve the nutritional value of feather meal (FeM). In a first experiment, a full factorial design was used to examine the effects of various incubation conditions on the solubilization of nitrogen in FeM. We incubated FeM for 3 h with various levels of a commercial alkaline serine protease (Savinase® 16L), sodium sulphite (Na2SO3), and digestion buffer. A Savinase® 16L level of 3% (%FeM v/w), Na2SO3 level of 3% (%FeM w/w), and digestion buffer level of 500% (%FeM w/w) were identified as the optimal conditions. Under these optimal conditions, 45% of the nitrogen in FeM was solubilized. In a second experiment, we evaluated the effect of more economically sustainable incubation conditions on the in vitro digestibility of protein (pepsin-HCl digestibility and multistep protein evaluation) in FeM. Two FeMs were incubated with 0.5% Savinase® 16L (%FeM v/w), 2% Na2SO3 (%FeM w/w), and 200% buffer (%FeM w/w) for 24 h. The pretreatment improved pepsin-HCl digestibility by 7–16% and the total tract degradable protein content by 14–50%. Accordingly, this novel pretreatment could be applied in the animal feed industry to improve the nutritional value of FeM. Full article
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