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  Subjects -> AGRICULTURE (Total: 772 journals)
    - AGRICULTURAL ECONOMICS (74 journals)
    - AGRICULTURE (524 journals)
    - CROP PRODUCTION AND SOIL (94 journals)
    - DAIRYING AND DAIRY PRODUCTS (30 journals)
    - POULTRY AND LIVESTOCK (50 journals)

AGRICULTURE (524 journals)                  1 2 3 4 5 6 | Last

Aceh International Journal of Science and Technology     Open Access   (Followers: 2)
Acta agriculturae Slovenica     Open Access   (Followers: 5)
Acta Agrobotanica     Open Access   (Followers: 5)
Acta Agronomica Hungarica     Full-text available via subscription   (Followers: 1)
Acta Agronomica Sinica     Full-text available via subscription   (Followers: 6)
Acta Scientiarum. Animal Sciences     Open Access   (Followers: 2)
Acta Scientiarum. Technology     Open Access  
Acta Technologica Agriculturae     Open Access   (Followers: 1)
Acta Universitatis Sapientiae, Alimentaria     Open Access  
Advances in Agriculture     Open Access   (Followers: 2)
Advances in Agriculture & Botanics     Open Access   (Followers: 10)
Advances in Agronomy     Full-text available via subscription   (Followers: 12)
Advances in Life Science and Technology     Open Access   (Followers: 8)
AFBM Journal     Open Access  
Africa Development     Open Access   (Followers: 20)
Africa Research Bulletin: Political, Social and Cultural Series     Hybrid Journal   (Followers: 9)
African Journal of Agricultural Research     Open Access   (Followers: 3)
African Journal of Food Science     Open Access   (Followers: 5)
African Journal of Food, Agriculture, Nutrition and Development     Open Access   (Followers: 14)
African Journal of Horticultural Science     Open Access   (Followers: 2)
African Journal of Range & Forage Science     Hybrid Journal   (Followers: 4)
African Journal of Sustainable Development     Full-text available via subscription   (Followers: 6)
Agra Europe     Full-text available via subscription   (Followers: 2)
Agribusiness : an International Journal     Hybrid Journal   (Followers: 8)
Agricultura Tecnica     Open Access   (Followers: 6)
Agricultura Tropica et Subtropica     Open Access   (Followers: 1)
Agricultural Advances     Open Access   (Followers: 3)
Agricultural and Food Science     Open Access   (Followers: 18)
Agricultural Commodities     Full-text available via subscription  
Agricultural Economics     Hybrid Journal   (Followers: 49)
Agricultural History     Full-text available via subscription   (Followers: 75)
Agricultural History Review     Full-text available via subscription   (Followers: 3)
Agricultural Research     Hybrid Journal   (Followers: 5)
Agricultural Science     Full-text available via subscription   (Followers: 5)
Agricultural Science     Open Access  
Agricultural Sciences     Open Access   (Followers: 7)
Agricultural Sciences in China     Full-text available via subscription   (Followers: 3)
Agricultural Systems     Hybrid Journal   (Followers: 22)
Agricultural Water Management     Hybrid Journal   (Followers: 18)
Agriculture     Open Access   (Followers: 7)
Agriculture & Food Security     Open Access   (Followers: 11)
Agriculture (Poľnohospodárstvo)     Open Access   (Followers: 1)
Agriculture and Agricultural Science Procedia     Full-text available via subscription  
Agriculture and Food Sciences Research     Open Access  
Agriculture and Human Values     Hybrid Journal   (Followers: 12)
Agriculture, Ecosystems & Environment     Hybrid Journal   (Followers: 44)
Agriprobe     Full-text available via subscription  
Agriscientia     Open Access  
Agrivita : Journal of Agricultural Science     Open Access   (Followers: 3)
Agro-Science     Full-text available via subscription  
Agroalimentaria     Open Access   (Followers: 1)
Agrociencia     Open Access   (Followers: 2)
Agrociencia Uruguay     Open Access  
Agrokémia és Talajtan     Full-text available via subscription   (Followers: 1)
Agronomía Colombiana     Open Access  
Agronomía Costarricense     Open Access   (Followers: 1)
Agronomía Mesoamericana     Open Access  
Agronomie Africaine     Full-text available via subscription  
Agronomy     Open Access   (Followers: 7)
Agrosearch     Open Access   (Followers: 1)
AI & Society     Hybrid Journal   (Followers: 4)
Alinteri Zirai Bilimler Dergisi : Alinteri Journal of Agricultural Sciences     Open Access  
Ambiência     Open Access  
Ambiente & Agua : An Interdisciplinary Journal of Applied Science     Open Access   (Followers: 1)
American Journal of Agricultural and Biological Sciences     Open Access   (Followers: 12)
American Journal of Botany     Full-text available via subscription   (Followers: 14)
American Journal of Economics and Sociology     Hybrid Journal   (Followers: 25)
American Journal of Potato Research     Hybrid Journal   (Followers: 2)
American Journal of Rural Development     Open Access   (Followers: 3)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Annales des Sciences Agronomiques     Full-text available via subscription  
Annals of Agricultural and Environmental Medicine     Open Access   (Followers: 1)
Annals of Agricultural Sciences     Open Access   (Followers: 1)
Annals of Silvicultural Research     Open Access   (Followers: 1)
Annual Review of Resource Economics     Full-text available via subscription   (Followers: 10)
APCBEE Procedia     Partially Free   (Followers: 2)
Applied Economics Letters     Hybrid Journal   (Followers: 25)
Applied Financial Economics Letters     Hybrid Journal   (Followers: 6)
Arboricultural Journal : The International Journal of Urban Forestry     Hybrid Journal   (Followers: 7)
Archivos de Zootecnia     Open Access   (Followers: 4)
Arquivos do Instituto Biológico     Open Access  
Arthropod-Plant Interactions     Hybrid Journal   (Followers: 1)
Asian Economic Papers     Hybrid Journal   (Followers: 4)
Asian Journal of Agricultural Research     Open Access   (Followers: 3)
Asian Journal of Medical and Biological Research     Open Access  
Asian Journal of Plant Sciences     Open Access   (Followers: 1)
Australian Cottongrower, The     Full-text available via subscription   (Followers: 1)
Australian Economic Papers     Hybrid Journal   (Followers: 6)
Australian Economic Review     Hybrid Journal   (Followers: 6)
Australian Forest Grower     Full-text available via subscription   (Followers: 2)
Australian Forestry     Full-text available via subscription   (Followers: 3)
Australian Grain     Full-text available via subscription   (Followers: 4)
Australian Holstein Journal     Full-text available via subscription   (Followers: 2)
Australian Journal of Agricultural and Resource Economics     Hybrid Journal   (Followers: 4)
Australian Journal of Agricultural Engineering     Open Access   (Followers: 1)
Australian Sugarcane     Full-text available via subscription  
Avances en Investigacion Agropecuaria     Open Access   (Followers: 1)
B.E. Journal of Theoretical Economics     Full-text available via subscription  
Bangladesh Journal of Agricultural Research     Open Access   (Followers: 2)
Bangladesh Journal of Scientific Research     Open Access   (Followers: 1)

        1 2 3 4 5 6 | Last

Journal Cover Biosystems Engineering
  [SJR: 0.773]   [H-I: 66]   [1 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1537-5110 - ISSN (Online) 1537-5129
   Published by Elsevier Homepage  [2801 journals]
  • Design of an eye-in-hand sensing and servo control framework for
           harvesting robotics in dense vegetation
    • Abstract: Publication date: Available online 25 January 2016
      Source:Biosystems Engineering
      Author(s): Ruud Barth, Jochen Hemming, Eldert J. van Henten
      A modular software framework design that allows flexible implementation of eye-in-hand sensing and motion control for agricultural robotics in dense vegetation is reported. Harvesting robots in cultivars with dense vegetation require multiple viewpoints and on-line trajectory adjustments in order to reduce the amount of false negatives and correct for fruit movement. In contrast to specialised software, the framework proposed aims to support a wide variety of agricultural use cases, hardware and extensions. A set of Robotic Operating System (ROS) nodes was created to ensure modularity and separation of concerns, implementing functionalities for application control, robot motion control, image acquisition, fruit detection, visual servo control and simultaneous localisation and mapping (SLAM) for monocular relative depth estimation and scene reconstruction. Coordination functionality was implemented by the application control node with a finite state machine. In order to provide visual servo control and simultaneous localisation and mapping functionalities, off-the-shelf libraries Visual Servoing Platform library (ViSP) and Large Scale Direct SLAM (LSD-SLAM) were wrapped in ROS nodes. The capabilities of the framework are demonstrated by an example implementation for use with a sweet-pepper crop, combined with hardware consisting of a Baxter robot and a colour camera placed on its end-effector. Qualitative tests were performed under laboratory conditions using an artificial dense vegetation sweet-pepper crop. Results indicated the framework can be implemented for sensing and robot motion control in sweet-pepper using visual information from the end-effector. Future research to apply the framework to other use-cases and validate the performance of its components in servo applications under real greenhouse conditions is suggested.
      Graphical abstract image

      PubDate: 2016-01-30T06:19:29Z
       
  • Close-range air-assisted precision spot-spraying for robotic applications:
           Aerodynamics and spray coverage analysis
    • Abstract: Publication date: Available online 25 January 2016
      Source:Biosystems Engineering
      Author(s): Aleš Malneršič, Matevž Dular, Brane Širok, Roberto Oberti, Marko Hočevar
      Orchards and grapevines are currently sprayed overall. Most bush and tree crop sprayers use airflow assistance which generates movements in canopy exposing both sides of the leaves to the spray. Also, large coherent vortices are formed further contributing to improved spray coverage. A new close-range air-assisted spot-spraying method for the selective treatments of disease foci is evaluated here which is promising for reduction of pesticides. Targets structures are expected to have typical diameters around 150 mm and the size of the unit matches this. In contrast to conventional methods, this size of unit prevents the generation of large scale coherent turbulent structures in the airflow that could provide spray coverage of both sides of the target leaves. Therefore, to enhance the beneficial effects of local turbulence, and to induce leaf movement whilst retaining the small size of the spray unit, a rotating screen to generate airflow pulses with discrete peaks in velocity was added and tested. Experiments on the close-range spraying of young grapevine plants using the rotating airflow screen were performed. A high-speed camera, image analysis system and water sensitive papers were used for analysis of the spraying. Natural frequencies of individual leaves showed sharp fluctuations at discrete frequencies and single leaf fluctuations of root mean square velocity corresponded well to the pulsating airflow. Spraying was evaluated as percentage spray coverage and number of droplet impacts. Spray coverage of front side of leaves (facing the sprayer) was good, but coverage on the back of the leaves was limited.


      PubDate: 2016-01-30T06:19:29Z
       
  • Effect of surfactant concentration on the spreading properties of
           pesticide droplets on Eucalyptus leaves
    • Abstract: Publication date: March 2016
      Source:Biosystems Engineering, Volume 143
      Author(s): Huan Lin, Hongping Zhou, Linyun Xu, Heping Zhu, Huanhua Huang
      The area wetted by 500-μm diameter droplets of pesticide and deionised water placed at different positions on Eucalyptus urophylla × E. grandis (E.u × E.g) and Eucalyptus tereticornis (E.t) leaves was determined at an air temperature of 30 °C and a relative humidity of 60%. Dimethyl dichlorovinyl phosphate (DDVP), and efficient cypermethrin (EC) were diluted 1000 times in deionised water. Solutions the pesticides were prepared with surfactant concentrations (SC) of 0.1%, 0.25%, 0.5%, and 1%. For comparison SC solutions with water and deionised water were also used. Droplet deposition positions were located in the interveinal area, midrib, and secondary vein on both adaxial and abaxial surfaces. Without surfactant, all droplets remained nearly spherical and did not spread on the leaf surfaces. With surfactant, the deionised water and pesticide droplets had distinct spreading properties. For deionised water, both the wetted area and spread effectiveness peaked at 0.1% SC, while for pesticide droplets the wetted area peaked at 1% SC. However, the optimum SC was 0.25%. Compared with droplets on E.u × E.g leaves, droplets spread more on E.t leaves. The adaxial surface had better wettability than the abaxial surface. For pesticide droplets, the wetted area was a minimum on the midrib and the wetted area on the secondary vein was slightly larger than that on the interveinal area.
      Graphical abstract image

      PubDate: 2016-01-30T06:19:29Z
       
  • Effect of acidification on solid–liquid separation of pig slurry
    • Abstract: Publication date: March 2016
      Source:Biosystems Engineering, Volume 143
      Author(s): Giorgia Cocolo, Maibritt Hjorth, Agata Zarebska, Giorgio Provolo
      Manure management causes massive nutrient losses to the environment. Acidification can reduce ammonia emissions and solid–liquid separation improves organic nutrient distribution on fields. Because acidification changes slurry composition, it impacts on the subsequent operation of solid–liquid separators and products. The aim was to determine the effects of slurry acidification on separation processes: screw pressing, centrifugal decanting, and flocculation with drainage. Separators were operated at full scale, and the electrochemical, physical and chemical properties of raw slurries, solid fractions and liquid fractions were analysed. Acidification of slurry increased the flow rate in the screw press due to presence of larger particles; in the decanting centrifuge due to lower slurry viscosity; and for flocculation with drainage due to reduction in the electrical charges on slurry particles. The rapidity with which acidified slurry was separated increased the loss of slurry constituents to the liquid fraction, including particulate matter; e.g. was the dry matter content in the solid fraction 10–50% lower upon acidification. In the solid fraction, acidification reduced the amount and concentration of particulate species, increased the amount and concentration of divalent species, and decreased the amount of monovalent species but it did not affect their concentration. Overall, acidification simplified the operation of separators and increased the flow rate of the operation. Solid fraction volume, P:N ratio, fertilisation value and energy value all decreased, but increased in the liquid fraction. Thus management and environmental benefits can be realised from the combined acidification and subsequent separation of pig slurry.


      PubDate: 2016-01-23T21:17:08Z
       
  • Improving the trajectory tracking performance of autonomous orchard
           vehicles using wheel slip compensation
    • Abstract: Publication date: Available online 21 January 2016
      Source:Biosystems Engineering
      Author(s): Gokhan Bayar, Marcel Bergerman, Erhan i. Konukseven, Ahmet B. Koku
      In this paper, the effects of wheel slip estimation and compensation of trajectory tracking for orchard applications were investigated. A slippage estimator was developed and adapted into a car-like robot model. Steering and velocity commands were generated using a model-based control approach. The whole system was implemented and tested on an autonomous orchard vehicle that has steerable front wheels and actuated rear wheels. A high accuracy positioning system was used to estimate the longitudinal and lateral slip velocities while the vehicle is moving. A laser scanning range finder was placed at the front centre of the vehicle, which was used to detect rows of trees in the orchard. Procedures were first tested in a non-flat but open space, which was covered with snow. Then it was tested on an experimental orchard where the surface was covered with heavy mud and the vehicle was expected to follow trajectories that span multiple rows in the orchard. The vehicle detected individual trees as well as rows of trees to track the centre of each row and manoeuvred from one row to the next. The experimental results showed that trajectory tracking performance of the vehicle was enhanced via integrating a slippage estimator into the system model. Furthermore, using the slippage estimation in the system model increased the accuracy, repeatability and performance of the control system.


      PubDate: 2016-01-23T21:17:08Z
       
  • Editorial Board
    • Abstract: Publication date: February 2016
      Source:Biosystems Engineering, Volume 142




      PubDate: 2016-01-23T21:17:08Z
       
  • Corrigendum to “Rapid milk cooling control with varying water and
           energy consumption” [Biosyst Eng 116 (2013) 15–22]
    • Abstract: Publication date: Available online 22 January 2016
      Source:Biosystems Engineering
      Author(s): Michael D. Murphy, John Upton, Michael J. O'Mahony



      PubDate: 2016-01-23T21:17:08Z
       
  • In-field automatic observation of wheat heading stage using computer
           vision
    • Abstract: Publication date: March 2016
      Source:Biosystems Engineering, Volume 143
      Author(s): Yanjun Zhu, Zhiguo Cao, Hao Lu, Yanan Li, Yang Xiao
      Growth stage information is an important factor for precision agriculture. It provides accurate evidence for agricultural management as well as early evaluation of yield. However, the observation of critical growth stages mainly relies on manual labour at present. This has some limitations because it is time-consuming, discontinuous and non-objective. Computer vision technology can help to alleviate these difficulties when monitoring growth status. This paper describes a novel automatic observation system for wheat heading stage based on computer vision. Images compliant with statistical requirements are taken in natural conditions where illumination changes frequently. Wheat plants with low spatial resolution overlap substantially, which increases observational difficulties. To adapt to the complex environment, a two-step coarse-to-fine wheat ear detection mechanism is proposed. In the coarse-detection step, machine learning technology is used to emphasise the candidate ear regions. In the fine-detection step, non-ear areas are eliminated through higher-level features. For that purpose, scale-invariant feature transform (SIFT) is densely extracted as the low-level visual descriptor, then Fisher vector (FV) encoding is employed to generate the mid-level representation. Based on three consecutive year's data of seven image sequences, a series of experiments are conducted to demonstrate the effectiveness and robustness of our proposition. Experimental results show that the proposed method significantly outperforms other existing methods with an average value of absolute error of 1.14 days on the test dataset. The results indicate that automatic observation is quite acceptable compared to manual observations.
      Graphical abstract image

      PubDate: 2016-01-23T21:17:08Z
       
  • Effect of spectrum measurement position variation on the robustness of NIR
           spectroscopy models for soluble solids content of apple
    • Abstract: Publication date: March 2016
      Source:Biosystems Engineering, Volume 143
      Author(s): Shuxiang Fan, Baohua Zhang, Jiangbo Li, Wenqian Huang, Chaopeng Wang
      In this paper, the influence of variation of spectrum measurement position on the near-infrared (NIR) spectroscopy analysis of soluble solids content (SSC) of apple was studied. The spectra were collected around stem, equator and calyx positions for each apple. Partial least squares (PLS) was used to develop compensation models of SSC for each measurement position separately (local position models) and for the full data set containing all positions (global position model). The results indicated that the influence of measurement position on the spectra affected the prediction accuracy of SSC. Compared with the local position models, the global position model was well suited to control the prediction accuracy of the calibration model for SSC with respect to the variation of spectrum measurement position. Next, competitive adaptive reweighted sampling (CARS) was used for the robust global position model to select the most effective wavelengths (EWs). It indicated that the global model established with effective wavelengths (EWs-global position model) achieved more promising results, with rp and RMSEP values for three measurement positions being 0.977, 0.977, 0.955 and 0.409, 0.386, 0.486 °Brix, respectively. Moreover, the local position models based on these effective variables (EWs-local position models) were more accurate than the models built with full range spectrum. The overall results indicated that the EWs-global position model could make the variation of spectrum measurement position a negligible interference for SSC prediction.


      PubDate: 2016-01-19T21:09:07Z
       
  • Enzymatic saccharification and fermentation of rice processing residue for
           ethanol production at constant temperature
    • Abstract: Publication date: February 2016
      Source:Biosystems Engineering, Volume 142
      Author(s): Raul J. Santos Michel, Nicholas I. Canabarro, Cláudia Alesio, Tanisa Maleski, Tiago Laber, Pamela Sfalcin, Edson L. Foletto, Flávio D. Mayer, Raquel C. Kuhn, Marcio A. Mazutti
      The aim was to investigate the enzymatic saccharification and fermentation for ethanol production. The rice bran, inoculum, corn steep liquor, soybean bran, amylase, cellulase concentrations and time of inoculum addition were evaluated using a Plackett-Burman (PB) experimental design. Furthermore, a central composite rotational design (CCRD) for three independent variables was carried out to optimise the ethanol production. Inoculum was added after 18 h of enzymatic hydrolysis and all the process was carried out at 35 °C during 48 h. Maximum ethanol production was 175 ± 5.8 g kg−1 obtained at 15% (m/m) concentration of inoculum, 150 g l−1 of rice bran and 3% (m/m) of cellulase. Rice bran is therefore a promising raw material for ethanol production.


      PubDate: 2016-01-15T20:50:39Z
       
  • Selective spraying of grapevines for disease control using a modular
           agricultural robot
    • Abstract: Publication date: Available online 13 January 2016
      Source:Biosystems Engineering
      Author(s): Roberto Oberti, Massimo Marchi, Paolo Tirelli, Aldo Calcante, Marcello Iriti, Emanuele Tona, Marko Hočevar, Joerg Baur, Julian Pfaff, Christoph Schütz, Heinz Ulbrich
      Due to their recognised role in causing environmental pressures, the need to reduce production costs and public concerns over the healthfulness of fresh products and food, reducing pesticide use in agriculture is a major objective. In current farming practice, pesticides are typically applied uniformly across fields, despite many pests and diseases exhibiting uneven spatial distributions and evolving around discrete foci. This is the fundamental rationale for implementing the selective targeting of pesticide applications such that pesticides are deposited only where and when they are needed and at the correct dose. This approach is explored using the example of powdery mildew on grape vines controlled by means of a modular agricultural robot developed within the EU-project CROPS. The CROPS manipulator was configured to six degrees of freedom and equipped with a new precision-spraying end-effector with an integrated disease-sensing system based on R-G-NIR multispectral imaging. The robotic system was tested on four different replicates of grapevine canopy plots (5 m in length × 1.8 m in height) prepared in a greenhouse setup by aligning potted plants exhibiting different levels of disease. The results indicate that the robot was able to automatically detect and spray from 85% to 100% of the diseased area within the canopy and to reduce the pesticide use from 65% to 85% when compared to a conventional homogeneous spraying of the canopy. This work, to the best of our knowledge, is the first using a totally automatic selective system for spraying of diseases in specialty crops.


      PubDate: 2016-01-15T20:50:39Z
       
  • Autonomous systems for precise spraying – Evaluation of a
           robotised patch sprayer
    • Abstract: Publication date: Available online 13 January 2016
      Source:Biosystems Engineering
      Author(s): Mariano Gonzalez-de-Soto, Luis Emmi, Manuel Perez-Ruiz, Juan Aguera, Pablo Gonzalez-de-Santos
      Advances in different technologies, such as global navigation satellite systems, geographic information systems, high-resolution vision systems, innovative sensors and embedded computing systems, are finding direct application in agriculture. These advances allow researchers and engineers to automate and robotise agricultural tasks no matter the inherent difficulties of the natural, semi-structured environment in which these tasks are performed. Following this current trend, this article aims to describe the development and assessment of a robotised patch spraty -20ying system that was devised for site-specific herbicide application in agricultural crops and is capable of working in groups or fleets of autonomous robots. The robotised patch sprayer consisted of an autonomous mobile robot based on a commercial agricultural vehicle chassis and a direct-injection spraying boom that was tailor-made to interact with the mobile robot. There were diverse sources (on-board and remote sensors) that can supply the weed data for the treatment. The main features of both the mobile robot and the sprayer are presented along with the controller that harmonised the behaviour of both main subsystems. Laboratory characterisation and field tests demonstrated that the system was reliable and accurate enough to accomplish the treatment over 99.5% of the detected weeds and treatment of the crop with no weed treated was insignificant; approximately 0.5% with respect to the total weed patches area, achieving a significant herbicide savings.


      PubDate: 2016-01-15T20:50:39Z
       
  • Integration of perception capabilities in gripper design using
           graspability maps
    • Abstract: Publication date: Available online 13 January 2016
      Source:Biosystems Engineering
      Author(s): Danny Eizicovits, Bart van Tuijl, Sigal Berman, Yael Edan
      Agricultural environments impose high demands on robotic grippers since the objects to be grasped (e.g., fruit) suffer from inherent uncertainties in size, shape, weight, and texture, are typically highly sensitive to excessive force, and tend to be partly or fully occluded. This paper presents a methodology for evaluating the influence of perception capabilities on grasping and on gripper design using graspability maps. Graspability maps are spatial representations of grasp quality grades from wrist poses (position and orientation) about an object and are generated using simulation. A new module was developed to enable the insertion of object pose errors for testing the effects of perception inaccuracies on grasping. The methodology was implemented for comparing two grippers (Fin-Ray and Lip-type) for harvesting two sweet-pepper cultivars. A 3D model of each gripper was constructed and suitable grasp quality measures were developed and validated in a physical environment. Task and gripper-specific grasp quality measures were developed for each implementation. Sensitivity analyses included varying pepper dimensions and perception inaccuracies. These were followed by analyses of the influence of gripper design parameters on grasp capabilities. Results indicate that the Lip-type gripper is less sensitive to inaccuracies in object orientation, while both grippers are similarly sensitive to inaccuracies in object position. Specific perception system demands and design recommendations are given for each gripper, and cultivar. The results illustrate the importance of integrating perception analysis in the gripper design phase and the utility of the graspability simulation tool for design analysis.


      PubDate: 2016-01-15T20:50:39Z
       
  • Algebraic path tracking to aid the manual harvesting of olives using an
           automated service unit
    • Abstract: Publication date: February 2016
      Source:Biosystems Engineering, Volume 142
      Author(s): Fernando A. Auat Cheein, Gustavo Scaglia, Miguel Torres-Torriti, José Guivant, Alvaro Javier Prado, Jaume Arnò, Alexandre Escolà, Joan R. Rosell-Polo
      Service units used in precision agriculture are able to improve processes such as harvesting, sowing, agrochemical application, and manure spreading. This two-part work presents, a path tracking controller based on an algebraic approach for an articulated service unit, suitable for embedded applications, and its implementation to a hierarchical navigation strategy to aid a manual harvesting process. The path tracking controller approach can be scaled to several trailers attached to the service unit. For harvesting, the service unit drives within an olive grove environment following the previously developed path and a trailer is used as a mobile hopper where olives, collected by human labour, are deposited. The service unit also registers and geo-references the amount of olives (mass) collected for the subsequent creation of yield maps. The developed navigation strategy improved the time associated with harvesting olives by approximately 42–45%. The mathematical formulation of the problem, some real time experimental results, the creation of a yield map and the statistical analysis that validated the method are included.


      PubDate: 2016-01-11T20:36:13Z
       
  • Non-destructive assessment of kiwifruit physico-chemical parameters to
           optimise the osmotic dehydration process: A study on FT-NIR spectroscopy
    • Abstract: Publication date: February 2016
      Source:Biosystems Engineering, Volume 142
      Author(s): Patricio R. Santagapita, Urszula Tylewicz, Valentina Panarese, Pietro Rocculi, Marco Dalla Rosa
      Non-destructive rapid method based on FT-NIR spectroscopy is assessed to predict the processing response of raw materials at different ripening stages. During osmotic dehydration (61.5% sucrose solution, 5 h) ripe and unripe kiwifruits were analysed with FT-NIR spectroscopy and the most representative physico-chemical parameters to osmotic dehydration (dry matter, soluble solids content, water self-diffusion coefficient and firmness) were assessed by destructive measurements. Predictive models were successfully built by means of partial least square regression (PLSR) analysis (R2 > 0.772, test set validations) for all the four parameters destructively measured. The application of vector normalisation pre-processing was critical to eliminate spectral information that did not relate to the OD process. FT-NIR spectroscopy can successfully predict the evolution of kiwifruit physico-chemical parameters during osmotic dehydration. Thus it can be used as a tool to tune online the process parameters (e.g. time and temperature) to obtain a standardised final product starting from non-homogeneous raw materials.


      PubDate: 2016-01-11T20:36:13Z
       
  • Leaf classification from binary image via artificial intelligence
    • Abstract: Publication date: February 2016
      Source:Biosystems Engineering, Volume 142
      Author(s): Kateřina Horaisová, Jaromír Kukal
      The invariant recognition of 2D binary images is the main subject of the paper. Two methods for invariant pattern recognition based on 2D Fourier power spectrum with guaranteed translation invariance are proposed. First method introduce the features invariant to translation, scaling, rotation and mirroring (TSO invariance). The second method introduces the features invariant to general affine transform (A invariance). The methods are used to obtain TSO/A invariant spectra except of the rotation effect which are analysed on circular paths with fixed radii. Harmonic analysis of power fluctuations around paths generates Fourier coefficients and their square absolute values are used as TSO/A invariant descriptors. The proposed methods were tested on two large sets of 2D digital images of tree leaves. After TSO/A invariant processing of thresholded digital images, kernel Support Vector Machine or self-organizing neural network were used for leaf categorisation.


      PubDate: 2016-01-11T20:36:13Z
       
  • Dielectric characterization of rapeseed (Brassica napus L.) from 10 to
           3000 MHz
    • Abstract: Publication date: March 2016
      Source:Biosystems Engineering, Volume 143
      Author(s): Namita Bansal, Amarjit S. Dhaliwal, Kuldip S. Mann
      Dielectric characterization of rapeseed (Brassica napus L.) in the temperature range of 20–60 °C and at moisture contents of 8.5, 12.5 and 16% wet basis (w.b.) was performed by determining the dielectric constant and loss factor at frequencies from 10 to 3000 MHz. This range of frequencies includes the ISM (Industrial, Scientific and Medical) frequencies of 13, 27, 40, 915 and 2450 MHz. An open-ended coaxial probe (Speag DAK, 12) and a vector network analyzer (Agilent Technologies, E5071C) were used to measure the dielectric properties (dielectric constant and loss factor). Compressed ground samples of rapeseed at densities nearly equivalent to seed density were used. Determined data at the ISM frequencies was fitted to polynomials to represent the dependence of the dielectric constant as well as the loss factor on temperature and moisture content. The calculated penetration depth of the electromagnetic field in rapeseed at the ISM frequencies shows that at a given moisture content and temperature, it decreases with increasing frequency. The reported data are useful in designing and developing radio-frequency (RF) and microwave (MW) applicators for dielectric heating of rapeseed.


      PubDate: 2016-01-11T20:36:13Z
       
  • Adaptive thresholding with fusion using a RGBD sensor for red sweet-pepper
           detection
    • Abstract: Publication date: Available online 8 January 2016
      Source:Biosystems Engineering
      Author(s): Efi Vitzrabin, Yael Edan
      An adaptive thresholding algorithm combined with sensor fusion to detect sweet-peppers with high detection rates for highly variable illumination conditions is presented. The objectives were to develop an algorithm for sweet-pepper detection, robust to illumination changes, with the aim of achieving high detection rates with low false alarms, that was robust to the selected thresholds and noise coming from the camera itself. An algorithm was developed that firstly divided the image into rectangular-shaped sub-images with approximately homogenous lighting conditions. The image was then further divided into amorphous-shaped sub-images and the RGB image was transformed to a 3D natural difference index image; for each sub-image, three thresholds were adaptively calculated and applied. In a final step, morphological operations and fusion with a depth sensor were developed to reduce false positives. Intensive evaluation was conducted on a database with normal lighting conditions. Twenty-five images were found to be the minimum training set required to achieve best performances. The true-positive rate was 0.909 and the false-positive rate was 0.046. Added noise up to 2% from the maximum available scale was found to have almost no influence on the performance. Validation using a second database with artificial lighting resulted with a true-positive rate of 1.00 and false-positive rate of 0.061, which suggests the importance of illumination. Fusion was critical for increasing the true-positive rate. The algorithm can also be used for detection in other crops.


      PubDate: 2016-01-11T20:36:13Z
       
  • Image analysis operations applied to hyperspectral images for non-invasive
           sensing of food quality – A comprehensive review
    • Abstract: Publication date: February 2016
      Source:Biosystems Engineering, Volume 142
      Author(s): Gamal M. ElMasry, Shigeki Nakauchi
      Image analysis involving mathematical, statistical and software programming approaches are the essential elements of any computer-integrated hyperspectral imaging systems. The theoretical and practical issues associated with the development, analysis, and application of essential image processing algorithms are explored in order to exploit hyperspectral imaging for application to food quality evaluations. The breadth of different image processing approaches adopted over the years in attempting to implement hyperspectral imaging for food quality monitoring was surveyed. Firstly, the fundamental configurations and working principles of hyperspectral systems, as well as the basic concept and structure of hyperspectral data, were described and explained. The understanding of different approaches used during image acquisition, data collection and visualisation were examined. Strategies and essential image processing routines necessary for making the appropriate decision during detection, classification, identification, quantification and/or prediction processes are presented. Examples and figures were selected to reinforce the main approach of each analysis algorithm applied in different agro-food products to answer the question “What does the user want to see in the target food samples?” The theoretical background for each algorithm was beyond the scope of this article thus only essential equations were addressed. The literature presented clearly revealed that hyperspectral imaging systems have gained a rapid interest from researchers to display the chemical structure and related physical properties of numerous types of food stuffs and hyperspectral imaging systems are expected to gain more considerably more potential and application in food processing and engineering plants.
      Graphical abstract image

      PubDate: 2016-01-07T19:25:06Z
       
  • Ambient awareness for agricultural robotic vehicles
    • Abstract: Publication date: Available online 6 January 2016
      Source:Biosystems Engineering
      Author(s): Giulio Reina, Annalisa Milella, Raphaël Rouveure, Michael Nielsen, Rainer Worst, Morten R. Blas
      In the last few years, robotic technology has been increasingly employed in agriculture to develop intelligent vehicles that can improve productivity and competitiveness. Accurate and robust environmental perception is a critical requirement to address unsolved issues including safe interaction with field workers and animals, obstacle detection in controlled traffic applications, crop row guidance, surveying for variable rate applications, and situation awareness, in general, towards increased process automation. Given the variety of conditions that may be encountered in the field, no single sensor exists that can guarantee reliable results in every scenario. The development of a multi-sensory perception system to increase the ambient awareness of an agricultural vehicle operating in crop fields is the objective of the Ambient Awareness for Autonomous Agricultural Vehicles (QUAD-AV) project. Different onboard sensor technologies, namely stereovision, LIDAR, radar, and thermography, are considered. Novel methods for their combination are proposed to automatically detect obstacles and discern traversable from non-traversable areas. Experimental results, obtained in agricultural contexts, are presented showing the effectiveness of the proposed methods.


      PubDate: 2016-01-07T19:25:06Z
       
  • Detection of tomatoes using spectral-spatial methods in remotely sensed
           RGB images captured by UAV
    • Abstract: Publication date: Available online 5 January 2016
      Source:Biosystems Engineering
      Author(s): J. Senthilnath, Akanksha Dokania, Manasa Kandukuri, Ramesh K.N., Gautham Anand, S.N. Omkar
      The spectral-spatial classification of high spatial resolution RGB images obtained from unmanned aerial vehicles (UAVs) for detection of tomatoes in the image is presented. Bayesian information criterion (BIC) was used to determine the optimal number of clusters for the image. Spectral clustering was carried out using K-means, expectation maximisation (EM) and self-organising map (SOM) algorithms to categorise the pixels into two groups i.e. tomatoes and non-tomatoes. Due to resemblance in spectral intensities, some of the non-tomato pixels were grouped into the tomato group and in order to remove them, spatial segmentation was performed on the image. Spatial segmentation was carried out using morphological operations and by setting thresholds for geometrical properties. The number of pixels grouped in the tomato cluster is different for each clustering method. EM doesn't pick up the land patches as tomato pixels. As a result, the size of the tomatoes picked up is different than K-means and SOM. Since threshold values chosen for carrying out spatial segmentation are shape and size dependent, different threshold values are applied to different methods of clustering. A synthetic image of 12 × 12 pixels with different labels is created to illustrate the effect of each method used for spatial segmentation on the clustered image. Two representative UAV images captured at different heights from the ground were used to demonstrate the performance of the proposed method. Results and comparison of performance parameters of different spectral-spatial classification methods were presented. It is observed that EM performed better than K-means and SOM.


      PubDate: 2016-01-07T19:25:06Z
       
  • Editorial Board
    • Abstract: Publication date: January 2016
      Source:Biosystems Engineering, Volume 141




      PubDate: 2016-01-03T19:13:18Z
       
  • Three-dimensional simulation and performance evaluation of air
           distribution in horizontal storage bins
    • Abstract: Publication date: February 2016
      Source:Biosystems Engineering, Volume 142
      Author(s): Oleg A. Khatchatourian, Manuel O. Binelo, Vanessa Faoro, Nelson A. Toniazzo
      A mathematical model and software were developed to simulate the air distribution in large horizontal grain storage bins fitted with aeration systems. Experimental data on the pressure distribution in a real large horizontal storage bin were obtained. Comparison between experimental and simulated data showed satisfactory agreement. Using the criteria proposed by the authors to estimate the effectiveness of the air distribution in storage bins, a performance evaluation of the considered system was carried out. The analysis of optimal air distribution in horizontal storage bin was carried out. It was shown that at a constant value of the global specific airflow rate, the increase in the area of air inlet section with corresponding pressure reduction is preferable to the increase in pressure under a smaller area. The optimum inlet pressure distribution for obtaining the optimum air distribution in large horizontal storage bins was proposed.


      PubDate: 2015-12-30T18:03:50Z
       
  • Heat-pump dehumidifier as an efficient device to prevent condensation in
           horticultural greenhouses
    • Abstract: Publication date: February 2016
      Source:Biosystems Engineering, Volume 142
      Author(s): Etienne Chantoiseau, Christophe Migeon, Gérard Chasseriaux, Pierre-Emmanuel Bournet
      In the context of increasing energy costs, alternative methods to the energy consuming venting-heating method must be considered for greenhouse dehumidification. In this paper the performance of a heat pump used as a dehumidifier is investigated. Contrary to the classical control aiming at maintaining the greenhouse air at a relative humidity set point, the considered device is designed as a preventive tool to avoid condensation on the crop and limit the energy consumption. The experimental set up was run during winter inside a 2350 m2 plastic greenhouse in the West of France for a set temperature of 16 °C. During the experiment, no condensation occurred on the plants with a mean condensation rate of 12 W m−2 and a mean electrical power of 7.62 kW, for an overall efficiency of 4.9. Moreover, the energy retrieved by vapour condensation was given back to the greenhouse as sensible heat, contributing to the total heating of the greenhouse. While dehumidifying the greenhouse air, the device reduces, or may even rule out the gas consumption. The total energy consumption of the heat pump during the season was compared to simulated values for venting-heating dehumidification, with or without an exchanger. The heat pump dehumidifier was shown to be 6 to 8.5 times less energy consuming than the former and 3-8 than the latter, depending on the exterior climate. Using the energy cost of several significant countries, a preliminary operative cost study was conducted and showed that the heat pump can be competitive as a dehumidification alternative.


      PubDate: 2015-12-26T17:30:46Z
       
  • Computer simulations to maximise fuel efficiency and work performance of
           agricultural tractors in rotovating and ploughing operations
    • Abstract: Publication date: February 2016
      Source:Biosystems Engineering, Volume 142
      Author(s): Jin W. Lee, Jae S. Kim, Kyeong U. Kim
      This study was conducted to investigate the effects of five control variables of a tractor: ballast, tyre inflation pressure, transmission gear, engine speed, and work load on three fuel efficiency parameters: fuel consumption per work hour (FC), fuel consumption per tilled area (FCA) and specific volumetric fuel consumption (SVFC). This was done for moldboard ploughing and rotovating operations by computer simulation. A tractor model was constructed with four sub-models: engine and power train, fuel consumption, tractive performance, and draught and power requirement. The simulated fuel efficiency values were in a range of 3.3–6.5% error in average when compared with those obtained from field experiments carried out in a paddy field under the same operational conditions. Based on these results, the tractor model was considered acceptable for simulations to find a general relationship between the fuel efficiency parameters and the control variables. Using the tractor model, 162 simulations were performed under the various combinations of the control variables on the basis of a full factorial design. The simulation results were used to develop linear regression models from which strategies can be established to maximise fuel efficiency. The best strategy reduced FC, FCA, and SVFC by 81.3, 61.1, and 52% under ploughing, and by 58.9, 75.7 and 28.6% under rotovating operations, respectively, when compared with those for the worst strategy.


      PubDate: 2015-12-23T17:07:47Z
       
  • CFD and weighted entropy based simulation and optimisation of Chinese
           Solar Greenhouse temperature distribution
    • Abstract: Publication date: February 2016
      Source:Biosystems Engineering, Volume 142
      Author(s): Xin Zhang, Hongli Wang, Zhirong Zou, Shaojin Wang
      Computer fluid dynamics (CFD) technique is considered as a powerful simulation tool to explore the temperature distribution in various buildings, especially for animal houses and greenhouses in recent years. However, its effective application in Chinese solar greenhouses (CSG) is still limited because of some technical problems and particular properties of CSG. A real-scale 2-D computer simulation model was developed with the finite-volume based commercial software, Fluent®, to simulate and analyse the temperature distributions caused only by thermal discharges from the north wall in CSG, governed by two computational domains, three conservation laws, and also five boundary conditions with k-ε turbulence model. A closed and empty CSG located in northwest of China was used to determine the thermal distribution and validate the simulation model during the night period on January 26th, 2013. Simulated and experimental results showed similar temperature distributions in CSG. The maximum and average absolute air temperature differences and mean squared deviation (MSD) were respectively 1.1, 0.8 and 0.1 K comparing measurement and simulation of inside air temperature and 0.7, 0.2 and 0.7 K for interior wall surface temperature. The simulation results demonstrated that temperature stratification and non-uniformity were more obvious when the north wall was thinner, suggesting a desirable thickness of north wall for energy conservation. The expanded polystyrene boards (EPS) play a more important role in preventing heat loss compared with perforated bricks (PB) in CSG. When the material cost was taken into consideration, a comprehensive evaluation model based on weighted entropy and fuzzy optimisation methods was employed to achieve the best north wall thickness (480 mm PB with 100 or 150 mm EPS) in CSG. The simulation and evaluation models in this study could be applied to enhance the indoor temperature environment and to optimise the thickness of the north wall in CSG.


      PubDate: 2015-12-23T17:07:47Z
       
  • Thermal performance of single span greenhouses with removable back walls
    • Abstract: Publication date: January 2016
      Source:Biosystems Engineering, Volume 141
      Author(s): Bin Wei, Shirong Guo, Jian Wang, Jie Li, Junwei Wang, Jian Zhang, Chuntao Qian, Jin Sun
      To improve the thermal performance of conventional single span greenhouses (SPGs), two types of greenhouses with removable back walls that are suitable for the climate in southern Jiangsu province, China were investigated, one with fully-removable back wall (FRG) and one with half-removable back wall (HRG). The removable back walls are made of jute fibre boards and installed in winter for heat preservation. They were removed in summer for ventilation. The thermal environment of the new greenhouses were studied experimentally. Results suggest the air temperature in the greenhouse with removable back walls could be maintained above 8.2 °C while the lowest temperature in the single span polyethylene greenhouse was only 2.9 °C, on sunny days in winter. During summer the highest indoor–outdoor air temperature difference of the SPG was 9.0 °C whereas with the HRG and FRG they were 6.8 °C and 6.1 °C, respectively. No significant difference of heat release was found inside room between HRG and FRG. The removable wall combined with jute fibre boards represents a potential design improvement for the back wall of solar greenhouses.


      PubDate: 2015-12-23T17:07:47Z
       
  • Evaluation of wind pressure coefficients of single-span greenhouses built
           on reclaimed coastal land using a large-sized wind tunnel
    • Abstract: Publication date: January 2016
      Source:Biosystems Engineering, Volume 141
      Author(s): Kyeong-seok Kwon, Dong-woo Kim, Rack-woo Kim, Taehwan Ha, In-bok Lee
      The government of Korea has announced a plan to develop large-scale greenhouse complexes on reclaimed coastal land. Wind characteristics over coastal regions are different from those of inland because of topographical and meteorological characteristics. A greenhouse facility is classified as a light-weight structure that is vulnerable to heavy wind loads. Reference to the newly modified greenhouse design standards, particularly for the reclaimed lands, has been required to ensure structural safety in strong winds. To evaluate the structural safety of greenhouses according to the wind characteristics for coastal reclaimed lands, the wind environments of these regions were simulated in a large scale Eiffel type wind tunnel. Variations in the windward terrain roughness were computed using the wind and turbulence intensity profiles based on ESDU (Engineering Sciences Data Unit, E01008) code. The wind pressure coefficients of four typical single-span greenhouses used in Korea, (Even-span, Three-quarter, Peach and Mono-span) were measured in the wind tunnel according to wind direction, roof slope and the radius of curvature of the roof. The wind pressure coefficients of the 4 types of greenhouses were proposed in terms of their structural design and cladding. The proposed wind pressure coefficients values will be valuable for greenhouse designers and manufacturers.


      PubDate: 2015-12-23T17:07:47Z
       
  • Detection of aphids in wheat fields using a computer vision technique
    • Abstract: Publication date: January 2016
      Source:Biosystems Engineering, Volume 141
      Author(s): Tao Liu, Wen Chen, Wei Wu, Chengming Sun, Wenshan Guo, Xinkai Zhu
      Aphids cause major damage in wheat fields resulting in significant yield losses. Monitoring aphid populations and the identification of aphid species provides important data related to pest population dynamics and integrated pest management. Manual identification and counting of wheat aphids is labour intensive, inefficient and subjective factors can influence its accuracy. A method of aphid identification and population monitoring based on digital images was developed. It used a maximally stable extremal region descriptor to simplify the background of field images containing aphids, and then used histograms of oriented gradient features and a support vector machine to develop an aphid identification model. This method was compared with five other commonly used methods of aphid detection; their performance was analysed using images with different aphid density, colour, or location on the plant. The results demonstrated that our new method provided mean identification and error rates of 86.81% and 8.91%, respectively, which is superior to other methods. The proposed method was easy-to-use and provides efficient and accurate aphid population data, and therefore can be used for aphid infestation surveys in wheat fields.


      PubDate: 2015-12-23T17:07:47Z
       
  • SWATDRAIN, a new model to simulate the hydrology of agricultural Lands,
           model development and evaluation
    • Abstract: Publication date: January 2016
      Source:Biosystems Engineering, Volume 141
      Author(s): Golmar Golmohammadi, Shiv O. Prasher, Ali Madani, Ramesh P. Rudra, Mohamed A. Youssef
      In this study, a new model was developed by fully incorporating the DRAINMOD model into the Soil and Water Assessment Tool (SWAT). In this modeling approach, surface flow is simulated using SWAT model and subsurface flow is estimated using the DRAINMOD model. The newly developed model, referred to as SWATDRAIN, has the potential to perform simulations of multiple scenarios such as controlled drainage, subsurface irrigation and wastewater treatment to determine cost-effective water management at the watershed scale. The model was evaluated for Green Belt Watershed, located in southern Ontario. Measured tile drainage and water table depth data from this watershed were used to evaluate the capability of the new model to simulate water balance components for this tile-drained agricultural watershed. Simulations were carried out over the period 1991–1993; 1991 and 1992 data were used for model calibration and 1993 data were used for validation. During both calibration and validation periods, SWATDRAIN simulated the watershed hydrologic response, the water table depth, and tile flow very well. Model accuracy statistics for monthly and daily water table depth over the validation period were, respectively, 0.86 and 0.70 for Coefficient of Determination, 0.11 and 2.90 for Percent Bias, and 0.80 and 0.67 for the Nash Sutcliffe Efficiency. Model accuracy statistics for events, monthly and daily tile drainage over the validation period were, respectively, 0.86, 0.88 and 0.70 for R2, 11.7, 13.26 and 13.26 for Percent Bias, and 0.82, 0.86 and 0.69 for Nash Sutcliffe Efficiency. This clearly demonstrates that integrated DRAINMOD approach in SWAT provides an effective water management tool for tile-drained watersheds.


      PubDate: 2015-12-13T07:12:09Z
       
  • Determination of K value for fish flesh with ultraviolet–visible
           spectroscopy and interval partial least squares (iPLS) regression method
    • Abstract: Publication date: January 2016
      Source:Biosystems Engineering, Volume 141
      Author(s): Anisur Rahman, Naoshi Kondo, Yuichi Ogawa, Tetsuhito Suzuki, Katsuhiro Kanamori
      The objective of this study is to develop a high performance prediction model for K value of fish flesh determination based on ultraviolet–visible (UV–VIS) spectra of fish eye fluid using an interval partial least squares (iPLS) regression method. Several preprocessing methods were initially compared during this study, i.e. moving weighted average smoothing, normalisation, multiplicative scatter correction (MSC), Savitzky-Golay (SG) first and second-order derivative. Full spectrum partial least squares (FS-PLS) and interval partial least squares (iPLS) regression methods were used to develop calibration models using these different pre-processed spectra. Compared to models developed by FS-PLS, the results showed that the regression model developed by iPLS based on MSC preprocessed spectra gave the best performance model with a determination coefficient of prediction ( R p r e d 2 ) of 0.96, and a root mean square error of prediction (RMSEP) of 5.12%.


      PubDate: 2015-12-13T07:12:09Z
       
  • Monitoring pig movement at the slaughterhouse using optical flow and
           modified angular histograms
    • Abstract: Publication date: January 2016
      Source:Biosystems Engineering, Volume 141
      Author(s): Ruta Gronskyte, Line Harder Clemmensen, Marchen Sonja Hviid, Murat Kulahci
      We analyse the movement of pig herds through video recordings at a slaughterhouse by using statistical analysis of optical flow (OF) patterns. Unlike the previous attempts to analyse pig movement, no markers, trackers nor identification of individual pigs are needed. Our method handles the analysis of unconstrained areas where pigs are constantly entering and leaving. The goal is to improve animal welfare by real-time prediction of abnormal behaviour through proper interventions. The aim of this study is to identify any stationary pig, which can be an indicator of an injury or an obstacle. In this study, we use the OF vectors to describe points of movement on all pigs and thereby analyse the herd movement. Subsequently, the OF vectors are used to identify abnormal movements of individual pigs. The OF vectors, obtained from the pigs, point in multiple directions rather than in one movement direction. To accommodate the multiple directions of the OF vectors, we propose to quantify OF using a summation of the vectors into bins according to their angles, which we call modified angular histograms. Sequential feature selection is used to select angle ranges, which identify pigs that are moving abnormally in the herd. The vector lengths from the selected angle ranges are compared to the corresponding median, 25th and 75th percentiles from a training set, which contains only normally moving pigs. We show that the method is capable of locating stationary pigs in the recordings regardless of the number of pigs in the frame.


      PubDate: 2015-12-13T07:12:09Z
       
  • Editorial Board
    • Abstract: Publication date: December 2015
      Source:Biosystems Engineering, Volume 140




      PubDate: 2015-12-01T06:15:24Z
       
  • Effect of light microclimate on the quality of ‘d’Anjou’
           pears in mature open-centre tree architecture
    • Abstract: Publication date: January 2016
      Source:Biosystems Engineering, Volume 141
      Author(s): Jingjin Zhang, Sara Serra, Rachel S. Leisso, Stefano Musacchi
      Light availability within trees is an important factor for canopy and fruit development as light drives photosynthetic processes. The effect of pre-harvest light microclimate on ‘d’Anjou’ pear fruit quality from harvest through to cold storage and ripening on fruit grown in open vase pear tree canopy was investigated. Light penetration was used to determine the light availability at different positions within the tree canopy. Five light penetration levels were predefined as 0–20%, 20%–40%, 40%–60%, 60%–80%, and 80%–100% and 60 fruits were selected from each level for quality assessment during three-month cold storage and postharvest ripening period. At harvest, upper canopy portions had a greater number of fruit than lower portions, but average single fruit mass was similar. During the cold storage and ripening period, the I AD index, a measure of chlorophyll degreening indicating fruit maturity, decreased. Fruit mass decreased for all light penetration levels during cold storage. No significant difference was found in fruit mass between light penetration levels following cold storage. Fruit soluble solids increased with light penetration while firmness exhibited an inverse relationship with light penetration level. Fruit from 80% to 100% light penetration level had significantly lower titratable acidity compared to other levels. This study indicated that light microclimate had consequential effects on ‘d'Anjou’ pear fruit quality, and effects of light penetration on quality were most pronounced in extreme light conditions, which are suggested to be the focus of further research.


      PubDate: 2015-12-01T06:15:24Z
       
  • Corrigendum to “Semi-mechanistic modelling of ammonia absorption in
           an acid spray wet scrubber based on mass balance” [Biosyst Eng 136
           (2015) 14–24]
    • Abstract: Publication date: Available online 21 November 2015
      Source:Biosystems Engineering
      Author(s): Lara Jane S. Hadlocon, Lingying Zhao, Barbara E. Wyslouzil, Heping Zhu



      PubDate: 2015-11-22T17:22:00Z
       
  • Effects of sunflower meal quality on the technical parameters of the
           pelleting process and pellet quality
    • Abstract: Publication date: December 2015
      Source:Biosystems Engineering, Volume 140
      Author(s): Radmilo R. Čolović, Lato L. Pezo, Đuro M. Vukmirović, Dušica S. Čolović, Oskar J. Bera, Vojislav V. Banjac, Jovanka D. Lević
      The impact of sunflower meal quality (i.e. crude protein content and crude fibre content) on the technical parameters of the pelleting process and the physical properties of produced pellets was investigated. Five model mixtures were prepared for pelleting, with different ratios of corn, sunflower meal (SFM) and soybean meal (SBM). Three grades of sunflower meal were used in the experiments with crude protein contents of approximately 37%, 40%, and 43%. Within each of the mixtures, granulation of material and retention time in the steam conditioner were varied. In order to describe the effects of the test variables on the observed responses response surface methodology, standard score analysis and principal component analysis (PCA) were used. The increase in the protein content and the decrease in the crude fibre content of sunflower meals caused an increase in the pelleting temperature, specific energy consumption, pellet hardness, and pellet durability. In addition, an increase in retention time increased specific energy consumption of pellet press, and produced fines. In terms of pellet durability values, a longer retention time was more beneficial for SFM mixtures than for SBM mixture. The type of mixture was found to be the most influential variable for second order polynomial model calculation. Standard score analysis showed that the optimum values for energy consumption, quantity of the fines, and pellet durability indices were obtained for the mixture with 40% protein SFM, with no retention after conditioning and with the finest granulation of the components (0.933). PCA showed that the first two principal components (91.10% of the total variability) enabled a neat separation of the five mixtures.
      Graphical abstract image

      PubDate: 2015-11-14T17:09:09Z
       
  • Detection of cherry tree branches with full foliage in planar architecture
           for automated sweet-cherry harvesting
    • Abstract: Publication date: Available online 3 November 2015
      Source:Biosystems Engineering
      Author(s): Suraj Amatya, Manoj Karkee, Aleana Gongal, Qin Zhang, Matthew D. Whiting
      Fresh market sweet cherry harvesting is a labour-intensive operation that accounts for more than 50% of annual production costs. To minimise labour requirements for sweet cherry harvesting, mechanized harvesting technologies are being developed. These technologies utilise manually-placed limb actuators that apply vibrational energy to affect fruit release. Machine vision-based automated harvesting system have potential to further reduce harvest labour through improving efficiency by eliminating manual handling, positioning and operation of the harvester and/or harvesting mechanism. A machine-vision system was developed to segment and detect cherry tree branches with full foliage, when only intermittent segments of branches were visible. Firstly, an image segmentation method was developed to identify visible segments of the branches. Bayesian classifier was used to classify image pixels into four classes – branch, cherry, leaf and background. The algorithm achieved 89.6% accuracy in identifying branch pixels. The length and orientation of branch segments were then analysed to link individual sections of the same branch together and to represent the branches with an equation. Linear and logarithmic model equations were fitted to the branch segments and the equation with minimum residual was selected as the best-fit model representing the corresponding branch. Branches detected with this algorithm were compared with manual counting. The method achieved a branch detection accuracy of 89.2% in a set of 141 test images acquired during full-foliage canopy. This study shows the potential of using a machine vision system for automating shake-and-catch cherry harvesting systems.


      PubDate: 2015-11-06T15:56:02Z
       
  • Compressibility and equivalent bulk modulus of shelled corn
    • Abstract: Publication date: December 2015
      Source:Biosystems Engineering, Volume 140
      Author(s): Xuduo Cheng, Qiang Zhang, Xiaojie Yan, Cuixia Shi
      An oedometer was used to measure changes in bulk density of shelled corn at different compression pressures and moisture contents. An equivalent confining pressure (ECP) was introduced to quantify the compression action in grain bins by considering non-uniformity and variability of compression pressures. Two models were developed for predicting bulk density and bulk modulus, respectively, as functions of ECP and moisture content. It was found that the uncompressed bulk density of shelled corn (before applying compression pressure) decreased with grain moisture and the relationship could be adequately described by a linear equation in the moisture range from 12.6 to 17.1% wb (wet basis). Shelled corn was more compressible at higher moisture content. However, bulk density approached to the same maximum value as compression pressure increased regardless of moisture content. In other words, moisture content had little effect on the maximum compressed bulk density. The equivalent bulk modulus of shelled corn increased with compression pressure and decreased with moisture content. The predicted bulk density and bulk modulus values were in good agreement with the experimental data.


      PubDate: 2015-11-06T15:56:02Z
       
  • Evaluation of sampling strategies for estimating ammonia emission factors
           for pig fattening facilities
    • Abstract: Publication date: December 2015
      Source:Biosystems Engineering, Volume 140
      Author(s): Tim Ulens, Matthijs R.J. Daelman, Julio Mosquera, Sam Millet, Mark C.M. van Loosdrecht, Eveline I.P. Volcke, Herman Van Langenhove, Peter Demeyer
      Determining ammonia emission factors (EF) for fattening pig facilities is important from both a regulatory and a research point of view. However, measurements to determine an EF can be time consuming and costly. Several reduced sampling strategies were developed in the past to reduce the costs and measuring time, by taking into account parameters that influence NH3 emissions. A methodology to evaluate the precision and accuracy of estimated EFs solely as a function of the sampling frequency and strategy is demonstrated. This evaluation was done by using two long-term, high frequency datasets which both contained measurements during two consecutive pig fattening periods. These datasets were subjected to simulated sampling strategies. Long-term, low-frequency grab sampling proved to be more accurate than short-term monitoring. Repetitive short-term sampling events result in increased precision, but as this entails higher investment in time and money it is imperative to strike the balance between desired precision and available resources. A method to help as set guidelines to decide upon the number of short-term sampling events or the length of a long-term, low-frequency monitoring strategy is presented.


      PubDate: 2015-10-26T15:25:37Z
       
  • Reducing energy requirements for sand filtration in microirrigation:
           Improving the underdrain and packing
    • Abstract: Publication date: December 2015
      Source:Biosystems Engineering, Volume 140
      Author(s): Josep Bové, Gerard Arbat, Toni Pujol, Miquel Duran-Ros, Francisco Ramírez de Cartagena, Joaquim Velayos, Jaume Puig-Bargués
      Energy consumption in pressurised irrigation systems has become a major issue, even when microirrigation is used. Although the emitters used in microirrigation operate at low pressures, their filters require higher pressures and there is therefore no reduction in energy consumption. Part of the pressure drop found in filters is produced by the porous medium itself and this cannot be avoided. However, a large part of the pressure dissipated is caused by auxiliary elements of the filter and this could potentially be reduced without reducing the effectiveness of the filtration process. The auxiliary elements that produced most of the pressure drop in a sand filter were identified. The pressure drop in a scaled sand filter was measured at different points. A computational fluid dynamics (CFD) model of the filter was developed and validated using experimental data. Good agreement was observed between the measured and predicted pressures at the different locations. The CFD model was then used to analyse the regions and elements that produced most pressure drop in the filter and a new underdrain designed to reduce pressure drop was developed. It was predicted that the total pressure drop produced by the underdrain could be halved. In view of these results, a new underdrain design and packing strategy was proposed which could reduce the overall pressure drop in the filter by 35%.


      PubDate: 2015-10-26T15:25:37Z
       
  • Classification of nest-building behaviour in non-crated farrowing sows on
           the basis of accelerometer data
    • Abstract: Publication date: December 2015
      Source:Biosystems Engineering, Volume 140
      Author(s): Maciej Oczak, Kristina Maschat, Daniel Berckmans, Erik Vranken, Johannes Baumgartner
      The objective of the study was to test the effectiveness of classification, on the basis of accelerometer data, of nest-building behaviour in farrowing sows that are not confined in crates. The experiment took place in the research farm of University of Veterinary Medicine Vienna, using a herd of 120 Edelschwein sows. Data were collected from 9 sows housed in farrowing pens. The behaviour of 9 sows was video recorded and labelled for a period of 24 h before farrowing, with focus on nest-building activities. Each sow had a specific ear tag with an 3 axis accelerometer sensor mounted on the ear. Acceleration was measured at a frequency of 10 Hz. Out of nine sows under observation, six were assigned to the training set and three as a test set. Classification of nest-building events in the test set using accelerometer data with the generalised linear model indicated sensitivity of 87%, specificity of 85% and accuracy of 86%. The developed technique can be used as part of a Precision Livestock Farming (PLF) automatic monitoring system, where PLF can be defined as management of livestock production using the principles and technology of process engineering. On-farm application of the system would give the possibility to keep sows unconfined until the end of nest-building period. Thus, crating of individual sows could be limited to the first few days after farrowing when the risk of piglet crushing is high. This would improve welfare of sows, without an increase in piglet mortality and without extra labour demand for observation.


      PubDate: 2015-10-26T15:25:37Z
       
  • Improving the bioenergy production from wheat straw with alkaline
           pretreatment
    • Abstract: Publication date: December 2015
      Source:Biosystems Engineering, Volume 140
      Author(s): Xiaoying Liu, Steven M. Zicari, Guangqing Liu, Yeqing Li, Ruihong Zhang
      A pretreatment process for wheat straw using potassium hydroxide (KOH) and recycled black liquor as a treatment reagent was developed and the minimum fresh chemical and water requirement were determined. Black liquor recycling in the pretreatment process resulted in a 75% reduction in fresh water use and 25% in KOH use, when compared to no recycling. It was found that after five batches of treatment, the concentrations of reducing sugar, chemical oxygen demand (COD), and K+ in black liquor, reached stable levels. During the pretreatment with black liquor recycling, 32–35% lignin was reduced in wheat straw. The pretreated straw showed reducing sugar yield of 336–366 mg g−1 [total solid (TS)] and methane yield of 290–303 mg g−1 [volatile solid (VS)] when subjected to enzymatic hydrolysis and anaerobic digestion, respectively.
      Graphical abstract image

      PubDate: 2015-10-26T15:25:37Z
       
  • A mobile sensor for leaf area index estimation from canopy light
           transmittance in wheat crops
    • Abstract: Publication date: December 2015
      Source:Biosystems Engineering, Volume 140
      Author(s): Michael Schirrmann, André Hamdorf, Antje Giebel, Karl-Heinz Dammer, Andreas Garz
      The leaf area index (LAI) is a key parameter describing the state and progress of crop canopies. Determination of LAI via proximal sensing supports decision-making processes in precision agriculture and improves biophysical modelling. Here we introduce the Canopy-Meter – a mobile sensor designed for determining LAI while driving over the field. The operating principle is based on the transmittance of sunlight passing through the plant canopy. This approach has not been previously applied to a proximal sensor. The sensor setup, its working principle, and the first field measurements are described. The setup of the Canopy-Meter consists of light sensors embedded in the upper and lower end of a tube. While positioned vertically in the plant canopy, the Canopy-Meter measures the above and below canopy irradiation flux. LAI is estimated from the ratio of above and below canopy irradiation through radiation transfer modelling. Spot measurements with the Canopy-Meter were conducted within three wheat fields during growth stages from 45 to 75 (Zadoks). Relationship between the SunScan SS1 LAI and Canopy-Meter LAI was linear for each measurement run (averaged R2 = 0.80) and pooled measurement points (R2 = 0.71). The relationships with biomass were linear and significant. Changing environmental conditions had a minor effect on the Canopy-Meter. The initial online measurements in wheat canopies exhibited a high correlation with the biomass densities observed in aerial photographs and with the reference LAI (R2 = 0.86). The results encourage further investigation on the Canopy-Meter as a new proximal sensor for precision agriculture.


      PubDate: 2015-10-26T15:25:37Z
       
  • Calibration of a growth model for tomato seedlings (TOMSEED) based on
           heuristic optimisation
    • Abstract: Publication date: December 2015
      Source:Biosystems Engineering, Volume 140
      Author(s): Nikolaos Katsoulas, Konstantinos Peponakis, Konstantinos P. Ferentinos, Constantinos Kittas
      A mechanistic growth model for tomato seedlings cultivated in unheated beds is developed, based on modifications of existing tomato growth models. Photosynthetically active radiation at crop level, air temperature and CO2 concentration are taken into account, while simulated variables include dry weights of leaves, shoot and root, leaf area index (LAI) of the seedlings, number of leaves per plant and finally, shoot length and thickness. Model calibration is formed into an optimisation problem, taking into account model errors of the first five simulated variables, i.e., dry weight of leaves, shoot and root, LAI and number of leaves per plant. Three heuristic optimisation algorithms are explored during model calibration: genetic algorithms, simulated annealing and tabu search. Genetic algorithms proved to be the most successful approach, resulting in an overall average deviation between simulated and measured values of around 16%. The calibrated model is tested and validated on measurements not used for calibration, showing a satisfactory performance in modelling most seedling characteristics, like the number of leaves per plant, the shoot length and thickness and the dry weight distribution, while it is not so accurate in predicting of other features like leaf and shoot dry weight and LAI. The tomato seedling characteristics that are mainly related to seedling quality (shoot length and dry weight, and number of leaves) were satisfactorily modelled with an average deviation between measured and simulated values around 16% for most of the simulation period. Finally, possible improvement strategies for future research are also discussed.


      PubDate: 2015-10-26T15:25:37Z
       
  • Editorial Board
    • Abstract: Publication date: November 2015
      Source:Biosystems Engineering, Volume 139




      PubDate: 2015-10-10T14:51:49Z
       
  • Farm level approach to manage grass yield variation under climate change
           in Finland and north-western Russia
    • Abstract: Publication date: December 2015
      Source:Biosystems Engineering, Volume 140
      Author(s): Pellervo Kässi, Hannu Känkänen, Olli Niskanen, Heikki Lehtonen, Mats Höglind
      Cattle feeding in Northern Europe is based on grass silage, but grass growth is highly dependent on weather conditions. If ensuring sufficient silage availability in every situation is prioritised, the lowest expected yield level determines the cultivated area in farmers' decision-making. One way to manage the variation in grass yield is to increase grass production and silage storage capacity so that they exceed the annual consumption at the farm. The cost of risk management in the current and the projected future climate was calculated taking into account grassland yield and yield variability for three study areas under current and mid-21st century climate conditions. The dataset on simulated future grass yields used as input for the risk management calculations were taken from a previously published simulation study. Strategies investigated included using up to 60% more silage grass area than needed in a year with average grass yields, and storing silage for up to 6 months more than consumed in a year (buffer storage). According to the results, utilising an excess silage grass area of 20% and a silage buffer storage capacity of 6 months were the most economic ways of managing drought risk in both the baseline climate and the projected climate of 2046–2065. It was found that the silage yield risk due to drought is likely to decrease in all studied locations, but the drought risk and costs implied still remain significant.


      PubDate: 2015-10-05T14:37:03Z
       
  • Dielectric power spectroscopy as a potential technique for the
           non-destructive measurement of sugar concentration in sugarcane
    • Abstract: Publication date: December 2015
      Source:Biosystems Engineering, Volume 140
      Author(s): Mojtaba Naderi-Boldaji, Milad Fazeliyan-Dehkordi, Seyed Ahmad Mireei, Mahdi Ghasemi-Varnamkhasti
      One of the existing serious technical challenges in the sugarcane industry is the lack of a low cost technique for the non-destructive measurement of sugar concentration as °Brix (percent soluble solids) or %Pol (percent sucrose) from either standing sugarcane in the field or sugarcane stalk/internode samples in laboratory. This study aimed at investigating the potential of dielectric power spectroscopy as a simple technique for this purpose. A parallel-plate capacitor was developed and supplied with sinusoidal voltage waves swept within a frequency range of 0–10 MHz where the consumed power of the capacitor was monitored as a function of frequency by a spectrum analyser. Seventy five internode samples from four sugarcane cultivars were measured by the dielectric sensor and then analysed for °Brix and %Pol in laboratory. Multiple linear regression (MLR) models were developed for prediction of °Brix and %Pol as functions of dielectric power at the swept frequencies with R 2 >0.99 and RMSE <0.31. The water content of the internode samples was also strongly predicted by the dielectric power spectra with a RMSE of 0.17%. It was concluded that dielectric power spectroscopy can be implemented as a potent and simple technique for the non-destructive measurement of °Brix and %Pol of sugarcane.


      PubDate: 2015-09-28T14:16:34Z
       
  • Tracking oxygen and temperature dynamics in maize silage-novel application
           of a Clark oxygen electrode
    • Abstract: Publication date: November 2015
      Source:Biosystems Engineering, Volume 139
      Author(s): Yurui Sun, Menghua Li, Qiang Cheng, Kerstin H. Jungbluth, Christian Maack, Wolfgang Buescher, Daokun Ma, Haiyang Zhou, Hong Cheng
      Making silage involves a complicated biochemical process where oxygen (O2) is rapidly consumed within the sealed environment leading to fermentation and stable storage of the biomass. Reintroduction of the oxygen from a leak or the feed-out process results in silage degradation. Monitoring silage O2 concentration and temperature (T si) can provide critical insight regarding silage quality. Thus, an in situ biosensor for simultaneous monitoring of O2 and T si to track silage aerobic deterioration has long been needed but was unavailable. Although the Clark oxygen electrode (COE) is traditionally applied for O2 concentration dissolved in liquids, we extended its use to the gaseous phase of silage based on Henry's law. This study tested COE's using two trials, where trial-1 explored the initial-aerobic/ensiling phase and trial-2 examined the silage feed-out phase. The experimental results of both trials demonstrated that the COE can be an important monitoring tool for assessing the O2 dynamics throughout the silage lifecycle.


      PubDate: 2015-08-26T06:53:52Z
       
  • Sugar beet (Beta vulgaris L.) and thistle (Cirsium arvensis L.)
           discrimination based on field spectral data
    • Abstract: Publication date: November 2015
      Source:Biosystems Engineering, Volume 139
      Author(s): Francisco J. Garcia-Ruiz, Dvoralai Wulfsohn, Jesper Rasmussen
      Creeping thistle (Cirsium arvensis (L.) Scop.) is a perennial weed that causes yield loss in sugar beet (Beta vulgaris L.) crops. The weeds are usually mapped for site specific weed management because they tend to grow in patches. Remote sensing techniques have shown promising results in species discrimination and therefore provide potential for weed mapping. In this study we examined the feasibility of high-resolution imaging for sugar beet and thistle discrimination and proposed a protocol to select multispectral camera filters. Spectral samples from sugar beet and thistle were acquired with a field portable spectroradiometer under field conditions and Partial Least Squares Discriminant Analysis (PLS-DA) classification models were developed with 211 and 36 spectral features of 1.56 and 10 nm bandwidths, respectively. The classification rates obtained using these models were regarded as the maximum obtainable. Then, spectral responses of a multi-band camera equipped with the filter configuration proposed by the PLS-DA models were simulated. Finally, a simulation of crop-weed discrimination was made using small unmanned aerial vehicles (UAV)-based multispectral images. More than 95% of the thistles and 89% of the sugar beets were correctly classified when continuous spectral data were used with 1.56 and 10 nm bandwidths. Accuracy dropped to 93% of thistles identified and 84% of sugar beets correctly classified when only the four best bands were used. The validation based on aerial images showed that sugar beets and thistle plants could be discriminated in images if sufficient pure pixels containing leaf spectra were available, that is with spatial resolutions of 6 mm pixel−1 or finer.


      PubDate: 2015-08-26T06:53:52Z
       
  • The efficiency of shredded and briquetted wheat straw in anaerobic
           co-digestion with dairy cattle manure
    • Abstract: Publication date: November 2015
      Source:Biosystems Engineering, Volume 139
      Author(s): Cristiane A.N. Xavier, Verónica Moset, Radziah Wahid, Henrik B. Møller
      Anaerobic co-digestion of cattle manure (CM) with shredded or briquetted wheat straw (SS and BS, respectively) was evaluated in thermophilic continuously stirred tank reactors (CSTR) in two experiments (lab and full-scale). Three lab-scale CSTR (15 l) were used with 20 days hydraulic retention time (HRT); one was fed with CM and the other two with mixtures of CM (95% of fresh matter, FM) and SS or BS (5% FM). In the second experiment, two full-scale CSTR (30 m3) were operated with 25 days HRT; one reactor was fed with CM and the other with CM + BS (9% FM). Ultimate CH4 yield was analysed from each substrate. Biochemical CH4 potential at 21 days for CM, SS and BS were 128; 187 and 200 lSTP [CH4] kg−1 [VS]. Anaerobic digestion of CM, CM + SS and CM + BS in lab-scale reactors yielded 165; 214 and 217 lSTP [CH4] kg−1 [VS]. In full scale-reactors, CM and CM + BS yielded 264 and 351 lSTP [CH4] kg−1 [VS]. Increments of 31 and 33% on CH4 yield were achieved in CM + BS compared to CM in lab and full-scale reactors, respectively. Regarding the energy balance, the energy yields were the same for both reactors using straw as co-substrate (CM + SS and CM + BS) after subtracting the energy consumption of the pretreatment, corresponding to 1100 kWh of net energy output. However, briquetting technology could be advantageous for biogas plants where the straw might be transported over longer distances, due to reduction of the transportation costs.


      PubDate: 2015-08-26T06:53:52Z
       
 
 
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