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Geometric models for analyzing the shape of cauliflower heads

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Selected geometric properties of cauliflower heads cv. Gohan F1 were analyzed by building numerical models with the use of a 3D scanner. Geometric models of cauliflower heads were developed in ScanStudio HD PRO, FreeCAD, and MeshLab programs. Five geometric models describing the shape of cauliflower heads were generated with the use basic geometric figures and drawing tools in FreeCAD. The geometry of numerical models and geometric models was compared in GOM Inspect. The surface area, volume, and detailed geometric dimensions of the developed models were determined. The deviations in cauliflower dimensions calculated by geometric models were mapped. The surface area, volume, and geometric dimensions of cauliflower heads were most accurately represented by the model generated with the Quadric Edge Collapse Decimation (QECD) function. In this model, the relative error of surface area measurements did not exceed 5%, and the relative error of volume measurements did not exceed 4%. This model was also characterized by the smallest average maximum deviation (+) and the smallest average minimum deviation (-) which was estimated at 8%. The proposed geometric model can be used for research and design purposes.
Rocznik
Tom
Strony
231–--247
Opis fizyczny
Bibliogr. 37 poz., rys., tab., wykr., zdj.
Twórcy
  • Department of Heavy Duty Machines and Research Methodology, University of Warmia and Mazury in Olsztyn
  • Katedra Maszyn Roboczych i Metodologii Badań, Uniwersytet Warmińsko-Mazurski, ul. Oczapowskiego 11, 10-719 Olsztyn
  • Department of Heavy Duty Machines and Research Methodology, University of Warmia and Mazury in Olsztyn
Bibliografia
  • ANDERS A., MARKOWSKI P., KALINIEWICZ Z. 2015. Numerical modelling of agricultural products on the example of bean and yellow lupine seeds. International Agrophysics, 29(4): 397-403.
  • ANDUJAR D., RIBEIRO A., QUINTANILLA C.F., DORADO J. 2016. Using depth cameras to extract structural parameters to assess the growth state and yield of cauliflower crops. Computers and Electronics in Agriculture, 122: 67-73.
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  • BALCERZAK K., WERES J., GÓRNA K., IDZIASZEK P. 2015. Modeling of agri-food products on the basis of solid geometry with examples in autodesk 3ds Max and finite element mesh generation. Journal of Research and Applications in Agricultural Engineering, 60(2): 5-8.
  • BECERRA L.D., ZULUAGA M., MAYORGA E.Y., MORENO F.L., RUÍZ R.Y., ESCOBAR S. 2022. Cocoa seed transformation under controlled process conditions: Modelling of the mass transfer of organic acids and reducing sugar formation analysis. Food and Bioproducts Processing, 136: 211-225.
  • BORYGA M., KOŁODZIEJ P. 2022. Reverse Engineering in Modeling Agricultural Products. Agricultural Engineering, 26(1): 105-117.
  • CIGNONI P., CALLIERI M., CORSINI M., DELLEPIANE M., GANOVELLI F., RANZUGLIA G. 2008. MeshLab: an Open-Source Mesh Processing Tool Sixth Eurographics. Italian Chapter Conference. http://dx.doi.org/10.2312/LocalChapterEvents/ItalChap/ItalianChapConf2008/129-136
  • CROCOMBE J.P., LOVATT S.J., CLARKE R.D. 1999. Evaluation of chilling time shape factors through the use of three-dimensional surface modeling. Proceedings of 20th International Congress of Refrigeration, IIR/IIF, Sydney (Paper 353).
  • DATTA A.K., HALDER A. 2008. Status of food process modeling and where do we go from here (synthesis of the outcome from brainstorming). Comprehensive Reviews in Food Science and Food Safety, 7: 117-120.
  • ERDOGDU F., BALABAN M.O., CHAU K.V. 1998. Modeling of heat conduction in elliptical cross-section: II. Adaptation to thermal processing of shrimp. Journal of Food Engineering, 38: 241-258.
  • FLORKIEWICZ A., FILIPIAK-FLORKIEWICZ A., TOPOLSKA K., CIEŚLIK E., KOSTOGRYS R.B. 2014. The effect of technological processing on the chemical composition of cauliflower. Italian Journal of Food Science, 26: 275-281.
  • FRĄCZEK J., WRÓBEL M. 2006. Methodic aspects of seed shape assessment. Inżynieria Rolnicza, 12(87): 155-163.
  • FreeCAD 0.20.2. 2023. https://www.freecadweb.org.
  • GASTÓN A.L., ABALONE R.M., GINER S.A. 2002. Wheat drying kinetics. Diffusivities for sphere and ellipsoid by finite elements. Journal of Food Engineering, 52(4): 313-322.
  • GOM Inspect. 2023. https://www.gom.com.
  • GONI S.M., PURLIS E., SALVADORI V.O. 2007. Three-dimensional reconstruction of irregular foodstuffs. Journal of Food Engineering, 82: 536-547.
  • GONI S.M., PURLIS E., SALVADORI V.O. 2008. Geometry modeling of food materials from magnetic resonance imaging. Journal of Food Engineering, 88: 561-567.
  • JADWISIEŃCZAK K., KALINIEWICZ Z. 2011. Analysis of the mustard seeds cleaning process. Part 1. Physical properties of seeds. Inżynieria Rolnicza, 9(134): 57-64.
  • JANCSOK P.T., CLIJMANS L., NICOLAI B.M., DE BAERDEMAEKER J. 2001. Investigation of the effect of shape on the acoustic response of ‘conference’ pears by finite element modeling. Postharvest Biology and Technology, 23: 1-12.
  • JIAN X., XIAOMING W., ZHENBANG Z., WEIBIN W. 2020. Discrete element modeling and simulation of soybean seed using multi-spheres and super-ellipsoids. IEEE Access, 8: 222672-222683.
  • JIANGANG L., XIANGMING X., YONGHUAI L., ZEXI R., MELVYN L. SMITH, LIPING J., BO L. 2021. Quantitative potato tuber phenotyping by 3D imaging. Biosystems Engineering, 210: 48-59.
  • KIM J., MOREIRA R.G., HUANG Y., CASTELL-PEREZ M.E. 2007. 3-D dose distributions for optimum radiation treatment planning of complex foods. Journal of Food Engineering, 79: 312321.
  • LONG Z., JIANQUN Y., YANG W., DONGXU Y., YAJUN Y. 2020. A study on the modelling method of maize-seed particles based on the discrete element method. Powder Technology, 374: 353-376.
  • MeshLab Visual Computing Lab - ISTI - CNR. 2013. http://meshlab.sourceforge.net.
  • MIESZKALSKI L. 2013. Computer-aiding of mathematical modeling of the carrot (Daucus carota L.) root shape. Annals of Warsaw University of Life Sciences – SGGW. Agriculture, 61: 17-23.
  • NASRINA T.A.A., YASMINB L., ARFINA M.S., RAHMANA MD. A., MOLLAC M.M., SABUZ A.A., AFROZ M. 2022. Preservation of postharvest quality of fresh cut cauliflower through simple and easy packaging techniques. Applied Food Research, 2: 1-12.
  • NextEngine User Manual. 2010. http://www.nextengine.com.
  • OLESEN J.E., GREVSEN K. 1997. Effects of temperature and irradiance on vegetative growth of cauliflower (Brassica oleracea L. botrytis) and broccoli (Brassica oleracea L. italic). Journal of Experimental Botany, 48: 1591-1598.
  • RAHMI U., FERRUH E. 2009. Potential use of 3-dimensional scanners for food process modeling. Journal of Food Engineering, 93: 337-343.
  • SABLIOV C.M., BOLDER D., KEENER K.M., FARKAS B.E. 2002. Image processing method to determine surface area and volume of axi-symmetric agricultural products. International Journal of Food Properties, 5: 641-653.
  • SCHEERLINCK N., MARQUENIE D., JANCSOK P.T., VERBOVEN P., MOLES C.G., BANGA J.R., NICOLAI B.M. 2004. A model-based approach to develop periodic thermal treatments for surface decontamination of strawberries. Postharvest Biology and Technology, 34: 39-52.
  • SHUAI W., ZHIHONG Y., AORIGELE, WENJIE Z. 2022. Study on the modeling method of sunflower seed particles based on the discrete element method. Computers and Electronics in Agriculture, 198: 1-16.
  • SINNOTT M.D., HARRISON SM., CLEARY P.W. 2021. A particle-based modelling approach to food processing operations. Food and Bioproducts Processing, 127: 14-57.
  • SIRIPON K., TANSAKUL A., MITTAL G.S. 2007. Heat transfer modeling of chicken cooking in hot water. Food Research International, 40: 923-930.
  • SZWEDZIAK K., RUT J. 2008. Assessment of pollutants of the grain corn with the help of computer analysis of the image. Postępy Techniki Przetwórstwa Spożywczego, 1: 14-15.
  • THAKUR A., BANERJEE A.G., GUPTA S.K. 2009. A survey of CAD model simplification techniques for physics-based simulation applications. Computer-Aided Design, 41: 65-80.
  • VERBOVEN P., DE BAERDEMAEKER J., NICOLAI B.M. 2004. Using computational fluid dynamics to optimize thermal processes. Richardson. P. (Ed.), Improving the Thermal Processing of Foods. CRC Press. Boca Raton, FL, p. 82-102.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-33410e5e-5d53-42bb-a950-ae51e0121725
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