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Crop 3D modeling allows site-specific management at different crop stages. In recent years, light detection and ranging (LiDAR) sensors have been widely used for gathering information about plant architecture to extract biophysical parameters for decision-making programs. The study reconstructed vineyard crops using light detection and ranging (LiDAR) technology. Its accuracy and performance were assessed for vineyard crop characterization using distance measurements, aiming to obtain a 3D reconstruction. A LiDAR sensor was installed on-board a mobile platform equipped with an RTK-GNSS receiver for crop 2D scanning. The LiDAR system consisted of a 2D time-of-flight sensor, a gimbal connecting the device to the structure, and an RTK-GPS to record the sensor data position. The LiDAR sensor was facing downwards installed on-board an electric platform. It scans in planes perpendicular to the travel direction. Measurements of distance between the LiDAR and the vineyards had a high spatial resolution, providing high-density 3D point clouds. The 3D point cloud was obtained containing all the points where the laser beam impacted. The fusion of LiDAR impacts and the positions of each associated to the RTK-GPS allowed the creation of the 3D structure. Although point clouds were already filtered, discarding points out of the study area, the branch volume cannot be directly calculated, since it turns into a 3D solid cluster that encloses a volume. To obtain the 3D object surface, and therefore to be able to calculate the volume enclosed by this surface, a suitable alpha shape was generated as an outline that envelops the outer points of the point cloud. The 3D scenes were obtained during the winter season when only branches were present and defoliated. The models were used to extract information related to height and branch volume. These models might be used for automatic pruning or relating this parameter to evaluate the future yield at each location. The 3D map was correlated with ground truth, which was manually determined, pruning the remaining weight. The number of scans by LiDAR influenced the relationship with the actual biomass measurements and had a significant effect on the treatments. A positive linear fit was obtained for the comparison between actual dry biomass and LiDAR volume. The influence of individual treatments was of low significance. The results showed strong correlations with actual values of biomass and volume with R2 = 0.75, and when comparing LiDAR scans with weight, the R2 rose up to 0.85. The obtained values show that this LiDAR technique is also valid for branch reconstruction with great advantages over other types of non-contact ranging sensors, regarding a high sampling resolution and high sampling rates. Even narrow branches were properly detected, which demonstrates the accuracy of the system working on difficult scenarios such as defoliated crops.
Hugo Moreno; Constantino Valero; José María Bengochea-Guevara; Ángela Ribeiro; Miguel Garrido-Izard; Dionisio Andújar. On-Ground Vineyard Reconstruction Using a LiDAR-Based Automated System. Sensors 2020, 20, 1102 .
AMA StyleHugo Moreno, Constantino Valero, José María Bengochea-Guevara, Ángela Ribeiro, Miguel Garrido-Izard, Dionisio Andújar. On-Ground Vineyard Reconstruction Using a LiDAR-Based Automated System. Sensors. 2020; 20 (4):1102.
Chicago/Turabian StyleHugo Moreno; Constantino Valero; José María Bengochea-Guevara; Ángela Ribeiro; Miguel Garrido-Izard; Dionisio Andújar. 2020. "On-Ground Vineyard Reconstruction Using a LiDAR-Based Automated System." Sensors 20, no. 4: 1102.
Nowadays farm machinery is incorporating new subsystems for the interchange of data between different mobile equipment and also with the base office. Such systems allow to know in real time basic information about how tasks are being performed in the field (where each tractor and machine is located, surface coverage, dose applied, fuel usage, etc. ) but also allow proper synchronization between machines working together (such a combine and a set of supporting trucks). The analysis and management of this information is important for the optimization of field tasks.
Miguel Garrido Izard. Telemetry and farm fleet management. Manuali – Scienze Tecnologiche 2020, 1 .
AMA StyleMiguel Garrido Izard. Telemetry and farm fleet management. Manuali – Scienze Tecnologiche. 2020; ():1.
Chicago/Turabian StyleMiguel Garrido Izard. 2020. "Telemetry and farm fleet management." Manuali – Scienze Tecnologiche , no. : 1.
The livestock sector seeks technologies and procedures to collect and manage data and information about its facilities and animals being the basis of the so-called precision livestock. The installation of unusual devices in commercial facilities, as well as the use of electronic feeding stations, allows observers to characterize the behavior pattern of each individual in order to improve farm management techniques and, therefore, its productivity. In this study, 30 Landrace pigs were monitored during the whole fattening period. Results from the study show that the ear skin temperatures of the animals can be used to distinguish animals with different thermal patterns. The parameters extracted from the feeding stations show consistent relationships between the parameters related to the frequency, size, and duration parameters, highlighting the differences in the feeding strategies. In this work, a complete fattening period (81 days) of a total of 30 Landrace pigs housed in two pens of a nucleus in Villatobas (Castilla-La Mancha, Spain) were supervised. The ear skin temperature of each animal was recorded every three minutes. The body weight, the date, the duration, and the amount of feed consumed per animal was monitored via an electronic feeding station. The objective was the identification of animals with different behaviors based on the integration of their thermal and intake patterns. The ear skin temperatures of the animals showed a negative relationship between the mean and the standard deviation (r = 0.83), distinguishing animals with different thermal patterns: individuals with high-temperature values show less thermal variability and vice versa. Feeding parameters showed differences in the feeding strategies of animals, identifying fast-eating animals with a high rate feed intake (60 g/min) and slow eaters (30 g/min). The correlation between the change in the rate of feed intake along with animal growth and feed efficiency reached a significant negative value (−0.57), indicating that animals that do not alter their rate of feed intake along breeding showed higher efficiencies. The difference in temperature of an animal with respect to the averaged group value has allowed us to identify animals with differentiated feeding patterns.
Miguel Garrido-Izard; Eva-Cristina Correa; José-María Requejo; Belén Diezma. Continuous Monitoring of Pigs in Fattening Using a Multi-Sensor System: Behavior Patterns. Animals 2019, 10, 52 .
AMA StyleMiguel Garrido-Izard, Eva-Cristina Correa, José-María Requejo, Belén Diezma. Continuous Monitoring of Pigs in Fattening Using a Multi-Sensor System: Behavior Patterns. Animals. 2019; 10 (1):52.
Chicago/Turabian StyleMiguel Garrido-Izard; Eva-Cristina Correa; José-María Requejo; Belén Diezma. 2019. "Continuous Monitoring of Pigs in Fattening Using a Multi-Sensor System: Behavior Patterns." Animals 10, no. 1: 52.
High or variable ambient temperature can affect thermal regulation in livestock, but few studies have studied thermal variability during air and road transport, partly due to the lack of tools to compare thermal data from a long time series over periods of different duration. In this study, we recorded the ear skin temperature (EST) of 11 Duroc breeder pigs (7 females and 4 males) during commercial intercontinental transport from Canada to Spain, which included both road and aircraft travel and lasted 65 h. The EST was measured using a logger placed inside the left ear. Phase space diagrams EST, that is EST time series vs. itself delayed in time, were used to quantify the variability of the time-temperature series based on the areas that included all the points in the phase space. Phase space areas were significantly higher for all the animals during air travel, almost doubling that of road transport. Using the phase spaces, we identified an event during air transport that lasted 57 min, leading to a general decrease in EST by 8 °C, with respect to the average EST (34.1 °C). We also found that thermal variability was more stable in males (F = 20.81, p = 0.0014), which were also older and heavier.
Miguel Garrido-Izard; Eva-Cristina Correa; José-María Requejo; Morris Villarroel; Belén Diezma. Phase Space Analysis of Pig Ear Skin Temperature during Air and Road Transport. Applied Sciences 2019, 9, 5527 .
AMA StyleMiguel Garrido-Izard, Eva-Cristina Correa, José-María Requejo, Morris Villarroel, Belén Diezma. Phase Space Analysis of Pig Ear Skin Temperature during Air and Road Transport. Applied Sciences. 2019; 9 (24):5527.
Chicago/Turabian StyleMiguel Garrido-Izard; Eva-Cristina Correa; José-María Requejo; Morris Villarroel; Belén Diezma. 2019. "Phase Space Analysis of Pig Ear Skin Temperature during Air and Road Transport." Applied Sciences 9, no. 24: 5527.
Since its inception approximately 50 years ago, the grape harvester has been one of the machines responsible for the expansion of viticulture in the world. In Spain, harvesters were introduced in the 1990s (there are now approximately 3,000 machines there as of 2017), while they were introduced in Brazil in 2010. Harvest mechanization requires specific crop adaption and new work features that deserve to be analysed from their very beginnings. The aim of this study was to evaluate the management of four commercial grape harvest machines under actual field conditions on an intercontinental basis in two locations in Brazil and Spain. Machine performance measured by work (ha h−1) and processing capacity (kg h−1), together with field efficiency (%) and task quality, as measured by grape losses (%), in soil and plant, as well as must release (%), were considered in relation to plot geometry, adaption of plots to mechanical harvesting, and machine type, in order to assess whether the initial steps towards harvest mechanization in Brazil have led to similar performance and quality levels compared to Spain, which represents an example of well-established mechanization. The theoretical work capacities were similar for towed equipment in both countries (0.81 ha h−1 in Brazil and 0.87 ha h−1 in Spain) and lower compared to self-propelled capacity (1.34 ha h−1). Significant differences were observed in terms of losses of grapes and must, with the highest values prevailing in Brazil (2 % grape losses in the ground; up to 23 % of the plant undetached grapes and must losses of 2-4 % (per kg vine productivity).
Wilson Valente Da Costa Neto; Pilar Barreiro Elorza; Miguel Garrido-Izard. Impact of local conditions and machine management on grape harvest quality. Scientia Agricola 2019, 76, 353 -361.
AMA StyleWilson Valente Da Costa Neto, Pilar Barreiro Elorza, Miguel Garrido-Izard. Impact of local conditions and machine management on grape harvest quality. Scientia Agricola. 2019; 76 (5):353-361.
Chicago/Turabian StyleWilson Valente Da Costa Neto; Pilar Barreiro Elorza; Miguel Garrido-Izard. 2019. "Impact of local conditions and machine management on grape harvest quality." Scientia Agricola 76, no. 5: 353-361.
The leaf area is an important plant parameter for plant status and crop yield. In this paper, a low-cost time-of-flight camera, the Kinect v2, was mounted on a robotic platform to acquire 3-D data of maize plants in a greenhouse. The robotic platform drove through the maize rows and acquired 3-D images that were later registered and stitched. Three different maize row reconstruction approaches were compared: reconstruct a crop row by merging point clouds generated from both sides of the row in both directions, merging point clouds scanned just from one side, and merging point clouds scanned from opposite directions of the row. The resulted point cloud was subsampled and rasterized, the normals were computed and re-oriented with a Fast Marching algorithm. The Poisson surface reconstruction was applied to the point cloud, and new vertices and faces generated by the algorithm were removed. The results showed that the approach of aligning and merging four point clouds per row and two point clouds scanned from the same side generated very similar average mean absolute percentage error of 8.8% and 7.8%, respectively. The worst error resulted from the two point clouds scanned from both sides in opposite directions with 32.3%.
Manuel Vázquez-Arellano; David Reiser; Dimitrios S. Paraforos; Miguel Garrido-Izard; Hans W. Griepentrog. Leaf Area Estimation of Reconstructed Maize Plants Using a Time-of-Flight Camera Based on Different Scan Directions. Robotics 2018, 7, 63 .
AMA StyleManuel Vázquez-Arellano, David Reiser, Dimitrios S. Paraforos, Miguel Garrido-Izard, Hans W. Griepentrog. Leaf Area Estimation of Reconstructed Maize Plants Using a Time-of-Flight Camera Based on Different Scan Directions. Robotics. 2018; 7 (4):63.
Chicago/Turabian StyleManuel Vázquez-Arellano; David Reiser; Dimitrios S. Paraforos; Miguel Garrido-Izard; Hans W. Griepentrog. 2018. "Leaf Area Estimation of Reconstructed Maize Plants Using a Time-of-Flight Camera Based on Different Scan Directions." Robotics 7, no. 4: 63.
Three dimensional (3-D) reconstruction of maize plant morphology by proximal sensing in agriculture brings high definition data that can be used for a number of applications related with precision agriculture and agricultural robotics. However, 3-D reconstruction without methodologies for extracting useful information is a senseless strategy. In this research, a methodology for stem position estimation is presented relying on the merging of four point clouds, using the Iterative Closes Point algorithm, that were generated from different 3-D perspective views. The proposed methodology is based on bivariate point density histograms for detecting the regional maxima and a radius filter based on the closest Euclidean distance. Then, single plant segmentation was performed by projecting a spatial cylindrical boundary around the estimated stem positions on a merged plant and soil point cloud. After performing a local Random Sample Consensus, the segmented plant point cloud was clustered using the Density-based spatial clustering of applications with noise algorithm. Additionally, a height profile was generated by rasterizing the plant and soil point clouds, separately, with different cell widths. The rasterized soil point cloud was meshed, and the rasterized plant points to soil mesh distance was calculated. The resulting plant stem positions were estimated with an average mean error and standard deviation of 24 mm and 14 mm, respectively. Equivalently, the average mean error and standard deviation of the individual plant height estimation was 30 mm and 35 mm, respectively. Finally, the overall plant height profile mean error average was 8.7 mm. Thus it is possible to determine the stem position and plant height of reconstructed maize plants using a low-cost time-of-flight camera.
Manuel Vázquez-Arellano; Dimitris S. Paraforos; David Reiser; Miguel Garrido-Izard; Hans W. Griepentrog. Determination of stem position and height of reconstructed maize plants using a time-of-flight camera. Computers and Electronics in Agriculture 2018, 154, 276 -288.
AMA StyleManuel Vázquez-Arellano, Dimitris S. Paraforos, David Reiser, Miguel Garrido-Izard, Hans W. Griepentrog. Determination of stem position and height of reconstructed maize plants using a time-of-flight camera. Computers and Electronics in Agriculture. 2018; 154 ():276-288.
Chicago/Turabian StyleManuel Vázquez-Arellano; Dimitris S. Paraforos; David Reiser; Miguel Garrido-Izard; Hans W. Griepentrog. 2018. "Determination of stem position and height of reconstructed maize plants using a time-of-flight camera." Computers and Electronics in Agriculture 154, no. : 276-288.
Mammalian skin temperature is often used as an indicator of health status but has also been used in animal production as a proxy measure for thermoregulatory effort or energy wastage. An animal with a higher skin temperature may also have a lower feed efficiency. With advances in technology it is now feasible to continuously record temperatures of livestock over protracted periods of time. In this study, the ear skin pig temperature was related to feed efficiency using phase space diagram methodology. Fourteen Landrace finishers (all male) housed in one pen over a week at relatively high temperatures (average temperature throughout the experiment 27 °C) were supervised. The date, time and amount of feed consumed per individual animals was monitored via an electronic feeding station. The number of visits to the feeding station was used as an indicator of physical locomotor activity. Each animal was weighed at the beginning and at the end of the experiment to calculate their feed efficiency. The areas of the phase space diagrams of skin temperatures were used to quantify the variability of the time temperature series. Two areas in the phase space were correlated with feed efficiency (r = 0.77) and physical locomotor activity (r = 0.53). An index was developed that includes both areas, which increased the correlation between the variability of ear skin temperature and feed efficiency to r = 0.85. This methodology could be used to help categorise pigs in terms of feed efficiency for rapid phenotyping.
Jose M. Requejo; Miguel Garrido-Izard; Eva C. Correa; Morris Villarroel; Belen Diezma. Pig ear skin temperature and feed efficiency: Using the phase space to estimate thermoregulatory effort. Biosystems Engineering 2018, 174, 80 -88.
AMA StyleJose M. Requejo, Miguel Garrido-Izard, Eva C. Correa, Morris Villarroel, Belen Diezma. Pig ear skin temperature and feed efficiency: Using the phase space to estimate thermoregulatory effort. Biosystems Engineering. 2018; 174 ():80-88.
Chicago/Turabian StyleJose M. Requejo; Miguel Garrido-Izard; Eva C. Correa; Morris Villarroel; Belen Diezma. 2018. "Pig ear skin temperature and feed efficiency: Using the phase space to estimate thermoregulatory effort." Biosystems Engineering 174, no. : 80-88.
New super-high-density (SHD) olive orchards designed for mechanical harvesting using over-the-row harvesters are becoming increasingly common around the world. Some studies regarding olive SHD harvesting have focused on the effective removal of the olive fruits; however, the energy applied to the canopy by the harvesting machine that can result in fruit damage, structural damage or extra stress on the trees has been little studied. Using conventional analyses, this study investigates the effects of different nominal speeds and beating frequencies on the removal efficiency and the potential for fruit damage, and it uses remote sensing to determine changes in the plant structures of two varieties of olive trees (‘Manzanilla Cacereña’ and ‘Manzanilla de Sevilla’) planted in SHD orchards harvested by an over-the-row harvester. ‘Manzanilla de Sevilla’ fruit was the least tolerant to damage, and for this variety, harvesting at the highest nominal speed led to the greatest percentage of fruits with cuts. Different vibration patterns were applied to the olive trees and were evaluated using triaxial accelerometers. The use of two light detection and ranging (LiDAR) sensing devices allowed us to evaluate structural changes in the studied olive trees. Before- and after-harvest measurements revealed significant differences in the LiDAR data analysis, particularly at the highest nominal speed. The results of this work show that the operating conditions of the harvester are key to minimising fruit damage and that a rapid estimate of the damage produced by an over-the-row harvester with contactless sensing could provide useful information for automatically adjusting the machine parameters in individual olive groves in the future.
Manuel Pérez-Ruiz; Pilar Rallo; M. Rocío Jiménez; Miguel Garrido-Izard; M. Paz Suárez; Laura Casanova; Constantino Valero; Jorge Martínez-Guanter; Ana Morales-Sillero. Evaluation of Over-The-Row Harvester Damage in a Super-High-Density Olive Orchard Using On-Board Sensing Techniques. Sensors 2018, 18, 1242 .
AMA StyleManuel Pérez-Ruiz, Pilar Rallo, M. Rocío Jiménez, Miguel Garrido-Izard, M. Paz Suárez, Laura Casanova, Constantino Valero, Jorge Martínez-Guanter, Ana Morales-Sillero. Evaluation of Over-The-Row Harvester Damage in a Super-High-Density Olive Orchard Using On-Board Sensing Techniques. Sensors. 2018; 18 (4):1242.
Chicago/Turabian StyleManuel Pérez-Ruiz; Pilar Rallo; M. Rocío Jiménez; Miguel Garrido-Izard; M. Paz Suárez; Laura Casanova; Constantino Valero; Jorge Martínez-Guanter; Ana Morales-Sillero. 2018. "Evaluation of Over-The-Row Harvester Damage in a Super-High-Density Olive Orchard Using On-Board Sensing Techniques." Sensors 18, no. 4: 1242.
Point cloud rigid registration and stitching for plants with complex architecture is a challenging task, however, it is an important process to take advantage of the full potential of 3-D cameras for plant phenotyping and agricultural automation for characterizing production environments in agriculture. A methodology for three-dimensional (3-D) reconstruction of maize crop rows was proposed in this research, using high resolution 3-D images that were mapped into the colour images using state-of-the art software. The point cloud registration methodology was based on the Iterative Closest Point (ICP) algorithm. The incoming point cloud was previously filtered using the Random Sample Consensus (RANSAC) algorithm, by reducing the number of soil points until a threshold value was reached. This threshold value was calculated based on the approximate number of plant points in a single 3-D image. After registration and stitching of the crop rows, a plant/soil segmentation process was done relying again on the RANSAC algorithm. A quantitative comparison showed that the number of points obtained with a time-of-flight (TOF) camera, compared with the ones from two light detection and ranging (LIDARs) from a previous research, was roughly 23 times larger. Finally, the reconstruction was validated by comparing the seedling positions as ground truth and the point cloud clusters, obtained using the k-means clustering, that represent the plant stem positions. The resulted maize positions from the proposed methodology closely agreed with the ground truth with an average mean and standard deviation of 3.4 cm and ±1.3 cm, respectively.
Manuel Vázquez-Arellano; David Reiser; Dimitris S. Paraforos; Miguel Garrido-Izard; Marlowe Edgar C. Burce; Hans W. Griepentrog. 3-D reconstruction of maize plants using a time-of-flight camera. Computers and Electronics in Agriculture 2018, 145, 235 -247.
AMA StyleManuel Vázquez-Arellano, David Reiser, Dimitris S. Paraforos, Miguel Garrido-Izard, Marlowe Edgar C. Burce, Hans W. Griepentrog. 3-D reconstruction of maize plants using a time-of-flight camera. Computers and Electronics in Agriculture. 2018; 145 ():235-247.
Chicago/Turabian StyleManuel Vázquez-Arellano; David Reiser; Dimitris S. Paraforos; Miguel Garrido-Izard; Marlowe Edgar C. Burce; Hans W. Griepentrog. 2018. "3-D reconstruction of maize plants using a time-of-flight camera." Computers and Electronics in Agriculture 145, no. : 235-247.
The feasibility of automated individual crop plant care in vegetable crop fields has increased, resulting in improved efficiency and economic benefits. A systems-based approach is a key feature in the engineering design of mechanization that incorporates precision sensing techniques. The objective of this study was to design new sensing capabilities to measure crop plant spacing under different test conditions (California, USA and Andalucía, Spain). For this study, three different types of optical sensors were used: an optical light-beam sensor (880 nm), a Light Detection and Ranging (LiDAR) sensor (905 nm), and an RGB camera. Field trials were conducted on newly transplanted tomato plants, using an encoder as a local reference system. Test results achieved a 98% accuracy in detection using light-beam sensors while a 96% accuracy on plant detections was achieved in the best of replications using LiDAR. These results can contribute to the decision-making regarding the use of these sensors by machinery manufacturers. This could lead to an advance in the physical or chemical weed control on row crops, allowing significant reductions or even elimination of hand-weeding tasks.
Jorge Martínez-Guanter; Miguel Garrido-Izard; Constantino Valero; David C. Slaughter; Manuel Pérez-Ruiz. Optical Sensing to Determine Tomato Plant Spacing for Precise Agrochemical Application: Two Scenarios. Sensors 2017, 17, 1096 .
AMA StyleJorge Martínez-Guanter, Miguel Garrido-Izard, Constantino Valero, David C. Slaughter, Manuel Pérez-Ruiz. Optical Sensing to Determine Tomato Plant Spacing for Precise Agrochemical Application: Two Scenarios. Sensors. 2017; 17 (5):1096.
Chicago/Turabian StyleJorge Martínez-Guanter; Miguel Garrido-Izard; Constantino Valero; David C. Slaughter; Manuel Pérez-Ruiz. 2017. "Optical Sensing to Determine Tomato Plant Spacing for Precise Agrochemical Application: Two Scenarios." Sensors 17, no. 5: 1096.
Active optical sensing (LIDAR and light curtain transmission) devices mounted on a mobile platform can correctly detect, localize, and classify trees. To conduct an evaluation and comparison of the different sensors, an optical encoder wheel was used for vehicle odometry and provided a measurement of the linear displacement of the prototype vehicle along a row of tree seedlings as a reference for each recorded sensor measurement. The field trials were conducted in a juvenile tree nursery with one-year-old grafted almond trees at Sierra Gold Nurseries, Yuba City, CA, United States. Through these tests and subsequent data processing, each sensor was individually evaluated to characterize their reliability, as well as their advantages and disadvantages for the proposed task. Test results indicated that 95.7% and 99.48% of the trees were successfully detected with the LIDAR and light curtain sensors, respectively. LIDAR correctly classified, between alive or dead tree states at a 93.75% success rate compared to 94.16% for the light curtain sensor. These results can help system designers select the most reliable sensor for the accurate detection and localization of each tree in a nursery, which might allow labor-intensive tasks, such as weeding, to be automated without damaging crops.
Miguel Garrido; Manuel Perez-Ruiz; Constantino Valero; Chris J. Gliever; Bradley D. Hanson; David C. Slaughter. Active Optical Sensors for Tree Stem Detection and Classification in Nurseries. Sensors 2014, 14, 10783 -10803.
AMA StyleMiguel Garrido, Manuel Perez-Ruiz, Constantino Valero, Chris J. Gliever, Bradley D. Hanson, David C. Slaughter. Active Optical Sensors for Tree Stem Detection and Classification in Nurseries. Sensors. 2014; 14 (6):10783-10803.
Chicago/Turabian StyleMiguel Garrido; Manuel Perez-Ruiz; Constantino Valero; Chris J. Gliever; Bradley D. Hanson; David C. Slaughter. 2014. "Active Optical Sensors for Tree Stem Detection and Classification in Nurseries." Sensors 14, no. 6: 10783-10803.
The study of temperature gradients in cold stores and containers is a critical issue in the food industry for the quality assurance of products during transport, as well as for minimizing losses. The objective of this work is to develop a new methodology of data analysis based on phase space graphs of temperature and enthalpy, collected by means of multidistributed, low cost and autonomous wireless sensors and loggers. A transoceanic refrigerated transport of lemons in a reefer container ship from Montevideo (Uruguay) to Cartagena (Spain) was monitored with a network of 39 semi-passive TurboTag RFID loggers and 13 i-button loggers. Transport included intermodal transit from transoceanic to short shipping vessels and a truck trip. Data analysis is carried out using qualitative phase diagrams computed on the basis of Takens–Ruelle reconstruction of attractors. Fruit stress is quantified in terms of the phase diagram area which characterizes the cyclic behaviour of temperature. Areas within the enthalpy phase diagram computed for the short sea shipping transport were 5 times higher than those computed for the long sea shipping, with coefficients of variation above 100 % for both periods. This new methodology for data analysis highlights the significant heterogeneity of thermohygrometric conditions at different locations in the container.
T. Jimenez-Ariza; E. C. Correa; B. Diezma; Ana Cecilia Silveira; P. Zócalo; F. J. Arranz; A. Moya-González; Miguel Garrido Izard; Pilar Barreiro; Margarita Ruiz Altisent. The Phase Space as a New Representation of the Dynamical Behaviour of Temperature and Enthalpy in a Reefer monitored with a Multidistributed Sensors Network. Food and Bioprocess Technology 2013, 7, 1793 -1806.
AMA StyleT. Jimenez-Ariza, E. C. Correa, B. Diezma, Ana Cecilia Silveira, P. Zócalo, F. J. Arranz, A. Moya-González, Miguel Garrido Izard, Pilar Barreiro, Margarita Ruiz Altisent. The Phase Space as a New Representation of the Dynamical Behaviour of Temperature and Enthalpy in a Reefer monitored with a Multidistributed Sensors Network. Food and Bioprocess Technology. 2013; 7 (6):1793-1806.
Chicago/Turabian StyleT. Jimenez-Ariza; E. C. Correa; B. Diezma; Ana Cecilia Silveira; P. Zócalo; F. J. Arranz; A. Moya-González; Miguel Garrido Izard; Pilar Barreiro; Margarita Ruiz Altisent. 2013. "The Phase Space as a New Representation of the Dynamical Behaviour of Temperature and Enthalpy in a Reefer monitored with a Multidistributed Sensors Network." Food and Bioprocess Technology 7, no. 6: 1793-1806.