IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v250y2013icp101-110.html
   My bibliography  Save this article

A 3D model for light interception in heterogeneous crop:weed canopies: Model structure and evaluation

Author

Listed:
  • Munier-Jolain, N.M.
  • Guyot, S.H.M.
  • Colbach, N.

Abstract

Models predicting photosynthetically active radiation (PAR) in heterogeneous canopies are an essential component of process-based weed dynamics models for assessing integrated weed management strategies. Most existing light availability models either consider only homogeneous canopies or are based on optical principles that are too complex for multi-annual and large-scale simulations required for evaluating weed dynamics. The TROLL model adopted a simpler approach, discretizing the canopy into cubic volume cells (“voxels”) and successively calculating PAR transmitted between voxel layers as a function of leaf area and extinction coefficient in each voxel. The present study aimed at developing at a simple, generic individual-based 3D model predicting light availability and interception in heterogeneous canopies for subsequent introduction into a weed dynamics model called FlorSys. In a first step, TROLL was adapted to crop:weed canopies for arable crops in temperate latitudes by (1) developing a new function adapted to annuals for describing plant morphology, (2) accounting for lateral light transmission as a function of solar angle, and (3) predicting the variation in lateral transmission with season and latitude. In the second step, the predictions produced by the FlorSys light availability model were compared to PAR measurements in heterogeneous crop stands. The model was shown to rank situations correctly and to predict incident PAR satisfactorily. A sensitivity analysis of FlorSys identified the voxel size optimizing prediction quality. In the last step, simulations were run to evaluate the potential of biological weed regulation via crop:weed competition for light. The present model will be connected to emergence, growth and development models in further studies.

Suggested Citation

  • Munier-Jolain, N.M. & Guyot, S.H.M. & Colbach, N., 2013. "A 3D model for light interception in heterogeneous crop:weed canopies: Model structure and evaluation," Ecological Modelling, Elsevier, vol. 250(C), pages 101-110.
  • Handle: RePEc:eee:ecomod:v:250:y:2013:i:c:p:101-110
    DOI: 10.1016/j.ecolmodel.2012.10.023
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380012005261
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2012.10.023?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Graf, B. & Gutierrez, A. P. & Rakotobe, O. & Zahner, P. & Delucchi, V., 1990. "A simulation model for the dynamics of rice growth and development: Part II--The competition with weeds for nitrogen and light," Agricultural Systems, Elsevier, vol. 32(4), pages 367-392.
    2. Gardarin, Antoine & Dürr, Carolyne & Colbach, Nathalie, 2012. "Modeling the dynamics and emergence of a multispecies weed seed bank with species traits," Ecological Modelling, Elsevier, vol. 240(C), pages 123-138.
    3. Kiniry, James R. & Williams, J. R. & Gassman, Philip W. & Debacke, P., 1992. "General, Process-Oriented Model for Two Competing Plant Species (A)," Staff General Research Papers Archive 483, Iowa State University, Department of Economics.
    4. Bourgeois, A. & Gaba, S. & Munier-Jolain, N. & Borgy, B. & Monestiez, P. & Soubeyrand, S., 2012. "Inferring weed spatial distribution from multi-type data," Ecological Modelling, Elsevier, vol. 226(C), pages 92-98.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Colas, Floriane & Gauchi, Jean-Pierre & Villerd, Jean & Colbach, Nathalie, 2021. "Simplifying a complex computer model: Sensitivity analysis and metamodelling of an 3D individual-based crop-weed canopy model," Ecological Modelling, Elsevier, vol. 454(C).
    2. Queyrel, Wilfried & Van Inghelandt, Bastien & Colas, Floriane & Cavan, Nicolas & Granger, Sylvie & Guyot, Bérénice & Reau, Raymond & Derrouch, Damien & Chauvel, Bruno & Maillot, Thibault & Colbach, Na, 2023. "Combining expert knowledge and models in participatory workshops with farmers to design sustainable weed management strategies," Agricultural Systems, Elsevier, vol. 208(C).
    3. Confalonieri, R., 2014. "CoSMo: A simple approach for reproducing plant community dynamics using a single instance of generic crop simulators," Ecological Modelling, Elsevier, vol. 286(C), pages 1-10.
    4. Bürger, Jana & Darmency, Henri & Granger, Sylvie & Guyot, Sébastien H.M. & Messéan, Antoine & Colbach, Nathalie, 2015. "Simulation study of the impact of changed cropping practices in conventional and GM maize on weeds and associated biodiversity," Agricultural Systems, Elsevier, vol. 137(C), pages 51-63.
    5. Chéné, Yann & Belin, Étienne & Rousseau, David & Chapeau-Blondeau, François, 2013. "Multiscale analysis of depth images from natural scenes: Scaling in the depth of the woods," Chaos, Solitons & Fractals, Elsevier, vol. 54(C), pages 135-149.
    6. Pointurier, Olivia & Moreau, Delphine & Pagès, Loïc & Caneill, Jacques & Colbach, Nathalie, 2021. "Individual-based 3D modelling of root systems in heterogeneous plant canopies at the multiannual scale. Case study with a weed dynamics model," Ecological Modelling, Elsevier, vol. 440(C).
    7. Cavan, Nicolas & Omon, Bertrand & Dubois, Sophie & Toqué, Clotilde & Van Inghelandt, Bastien & Queyrel, Wilfried & Colbach, Nathalie & Angevin, Frédérique, 2023. "Model-based evaluation in terms of weed management and overall sustainability of cropping systems designed with three different approaches," Agricultural Systems, Elsevier, vol. 208(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Colas, Floriane & Gauchi, Jean-Pierre & Villerd, Jean & Colbach, Nathalie, 2021. "Simplifying a complex computer model: Sensitivity analysis and metamodelling of an 3D individual-based crop-weed canopy model," Ecological Modelling, Elsevier, vol. 454(C).
    2. Movedi, Ermes & Valiante, Daniele & Colosio, Alessandro & Corengia, Luca & Cossa, Stefano & Confalonieri, Roberto, 2022. "A new approach for modeling crop-weed interaction targeting management support in operational contexts: A case study on the rice weeds barnyardgrass and red rice," Ecological Modelling, Elsevier, vol. 463(C).
    3. Garcia y Garcia, Axel & Guerra, Larry C. & Hoogenboom, Gerrit, 2008. "Impact of generated solar radiation on simulated crop growth and yield," Ecological Modelling, Elsevier, vol. 210(3), pages 312-326.
    4. Xie, Yun & Kiniry, James R. & Williams, Jimmy R., 2003. "The ALMANAC model's sensitivity to input variables," Agricultural Systems, Elsevier, vol. 78(1), pages 1-16, October.
    5. Ricci, Benoît & Petit, Sandrine & Allanic, Charlotte & Langot, Marie & Parisey, Nicolas & Poggi, Sylvain, 2018. "How effective is large landscape-scale planning for reducing local weed infestations? A landscape-scale modelling approach," Ecological Modelling, Elsevier, vol. 384(C), pages 221-232.
    6. Čerkasova, Natalja & White, Michael & Arnold, Jeffrey & Bieger, Katrin & Allen, Peter & Gao, Jungang & Gambone, Marilyn & Meki, Manyowa & Kiniry, James & Gassman, Philip W., 2023. "Field scale SWAT+ modeling of corn and soybean yields for the contiguous United States: National Agroecosystem Model Development," Agricultural Systems, Elsevier, vol. 210(C).
    7. Kiniry, James R. & Bean, Brent & Xie, Yun & Chen, Pei-yu, 2004. "Maize yield potential: critical processes and simulation modeling in a high-yielding environment," Agricultural Systems, Elsevier, vol. 82(1), pages 45-56, October.
    8. Stéphane Cordeau & Richard G. Smith & Eric R. Gallandt & Bryan Brown & Paul Salon & Antonio DiTommaso & Matthew R. Ryan, 2017. "Disentangling the Effects of Tillage Timing and Weather on Weed Community Assembly," Agriculture, MDPI, vol. 7(8), pages 1-18, August.
    9. Iqbal, M. Anjum & Shen, Yanjun & Stricevic, Ruzica & Pei, Hongwei & Sun, Hongyoung & Amiri, Ebrahim & Penas, Angel & del Rio, Sara, 2014. "Evaluation of the FAO AquaCrop model for winter wheat on the North China Plain under deficit irrigation from field experiment to regional yield simulation," Agricultural Water Management, Elsevier, vol. 135(C), pages 61-72.
    10. Talebizadeh, Mansour & Moriasi, Daniel & Gowda, Prasanna & Steiner, Jean L. & Tadesse, Haile K. & Nelson, Amanda M. & Starks, Patrick, 2018. "Simultaneous calibration of evapotranspiration and crop yield in agronomic system modeling using the APEX model," Agricultural Water Management, Elsevier, vol. 208(C), pages 299-306.
    11. Ascough II, J.C. & Andales, A.A. & Sherrod, L.A. & McMaster, G.S. & Hansen, N.C. & DeJonge, K.C. & Fathelrahman, E.M. & Ahuja, L.R. & Peterson, G.A. & Hoag, D.L., 2010. "Simulating landscape catena effects in no-till dryland agroecosystems using GPFARM," Agricultural Systems, Elsevier, vol. 103(8), pages 569-584, October.
    12. Napoli, Marco & Orlandini, Simone, 2015. "Evaluating the Arc-SWAT2009 in predicting runoff, sediment, and nutrient yields from a vineyard and an olive orchard in Central Italy," Agricultural Water Management, Elsevier, vol. 153(C), pages 51-62.
    13. Kropff, M. J. & Teng, P. S. & Rabbinge, R., 1995. "The challenge of linking pest and crop models," Agricultural Systems, Elsevier, vol. 49(4), pages 413-434.
    14. Queyrel, Wilfried & Van Inghelandt, Bastien & Colas, Floriane & Cavan, Nicolas & Granger, Sylvie & Guyot, Bérénice & Reau, Raymond & Derrouch, Damien & Chauvel, Bruno & Maillot, Thibault & Colbach, Na, 2023. "Combining expert knowledge and models in participatory workshops with farmers to design sustainable weed management strategies," Agricultural Systems, Elsevier, vol. 208(C).
    15. Żyromski, Andrzej & Szulczewski, Wiesław & Biniak-Pieróg, Małgorzata & Jakubowski, Wojciech, 2016. "The estimation of basket willow (Salix viminalis) yield – New approach. Part I: Background and statistical description," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1118-1126.
    16. Mabhaudhi, Tafadzwanashe & Dirwai, Tinashe Lindel & Taguta, Cuthbert & Sikka, Alok & Lautze, Jonathan, 2023. "Mapping Decision Support Tools (DSTs) on agricultural water productivity: A global systematic scoping review," Agricultural Water Management, Elsevier, vol. 290(C).
    17. Larson, James A. & English, Burton C. & He, Lixia, 2008. "Risk and Return for Bioenergy Crops under Alternative Contracting Arrangements," 2008 Annual Meeting, February 2-6, 2008, Dallas, Texas 6842, Southern Agricultural Economics Association.
    18. Wu, G. W. & Wilson, L. T., 1998. "Parameterization, verification, and validation of a physiologically complex age-structured rice simulation model," Agricultural Systems, Elsevier, vol. 56(4), pages 483-511, April.
    19. Zand-Parsa, Sh. & Sepaskhah, A.R. & Ronaghi, A., 2006. "Development and evaluation of integrated water and nitrogen model for maize," Agricultural Water Management, Elsevier, vol. 81(3), pages 227-256, March.
    20. Alma Delia Baez-Gonzalez & James R. Kiniry & Manyowa N. Meki & Jimmy Williams & Marcelino Alvarez-Cilva & Jose L. Ramos-Gonzalez & Agustin Magallanes-Estala & Gonzalo Zapata-Buenfil, 2017. "Crop Parameters for Modeling Sugarcane under Rainfed Conditions in Mexico," Sustainability, MDPI, vol. 9(8), pages 1-19, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:250:y:2013:i:c:p:101-110. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.