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22 (2018) | nr 3 (167) | 21--28
Tytuł artykułu

Concepts and Methods of Mathematic Modelling of Plant Growth and Development. Plant Germination - Part II

Warianty tytułu
Koncepcje i metody modelowania matematycznego procesów wzrostu i rozwoju roślin. Wschody roślin - część II
Języki publikacji
EN
Abstrakty
EN
Interdisciplinary nature of scientific research with regard to agriculture caused a development of mathematical modelling with regard to plant growth and development. Application of mathematical sciences in agriculture suits well the area of agricultural engineering which covers the issues related to inter alia, application of mathematical sciences. This article presents mathematical models, in which the analysed system is described with mathematical formulas. The objective of the paper was to present the current state of knowledge on mathematical methods in description and prediction of plant germination. Possibilities of the use of mathematical models and new challenges occurring in the description of plant germination were presented.(original abstract)
Interdyscyplinarność badań naukowych w zakresie rolnictwa przyczyniła się do rozwoju modelowania matematycznego w zakresie wzrostu i rozwoju roślin. Stosowanie nauk matematycznych w rolnictwie wkomponowuje się w obszar inżynierii rolniczej, która to w swoim zakresie obejmuje zagadnienia związane m.in. z zastosowaniem nauk matematycznych. W artykule tym zostały przedstawione modele matematyczne, w których analizowany system jest opisany przy zastosowaniu formuł matematycznych. Celem pracy było przedstawienie dotychczasowego stanu wiedzy na temat metod matematycznych w opisywaniu i prognozowaniu wschodów roślin. Przedstawiono możliwości wykorzystania modeli matematycznych i nowe wyzwania pojawiające się w opisie wschodów roślin.(abstrakt oryginalny)
Rocznik
Numer
Strony
21--28
Opis fizyczny
Twórcy
  • University of Life Sciences in Lublin
Bibliografia
  • Aggarwal, P.K. (1993). Agro-ecological zoning using crop growth simulation models: characterization of wheat environments in India. F.W.T. Penning de Vries, P. Teng, K. Metselaar (Eds.), Systems approaches for sustainable agricultural development, Kluwer Academic Publishers, Dordrecht, The Netherlis, 97-109.
  • Aggarwal, P.K., Kalra, N. (1994). Analyzing the limitations set by climatic factors, genotype, and water and nitrogen availability on productivity of wheat II. Climatically potential yields and management strategies. Field Crops Research, 38, 93-103.
  • Angus, J.F., Cunningham, R.B., Moncur, M.W., Mackenzie, D.H. (1981). Phasic development in field crops. I. Thermal response in the seedling phase. Field Crops Research, 3, 365-378.
  • Benech Arnold, R.L., Ghersa, C.M., Sanchez, R.A., Insausti, P. (1990). A mathematical model to predict Sorghum halepense (L.) Pers. seedling emergence in relation to soil temperature. Weed Research, 30, 91-99.
  • Berge, N., Samaan, M., Juanole, G., Atamna J. (1994). Methodology for LAN modelling and analysis using Petri net based models. Proc. Int. Workshop on Modelling, Analysis and Simulation in Telecommunication Systems, Durham, NC, 269-275.
  • Bouman, B.A.M., van Keulen, H., van Laar, H.H., Rabbinge, R. (1996). The school of de Wit crop growth simulation models: a pedigree and historical overview Agricultural Systems, 52(2/3), 171-198.
  • Boydston, R.A. (1989). Germination and emergence of longspine sibur (Cenchrus longispinus). Weed Science, 37, 63-67.
  • Bradford, K.J. (1995). Water relations in seed germination. In: Kigel, J., Galili, G. (Eds.), Seed Development i Germination. Marcel Dekker, New York, pp. 351-396.
  • Brown, R.F., Mayer, D.G. (1988). Representing cumulative germination. 2. The use of the Weibull function and other empirically derived curves. Annals of Botany, 61, 127-138.
  • Carberry, P.S., Campbell, L.C. (1989). Temperature parameters useful for modeling the germination and emergence of pearl millet. Crop Science, 29, 220-223.
  • Carberry, P.S., Muchow, R.C., McCown, R.L. (1993). A simulation model of kenaf for assisting fibre industry planning in northern Australia. IV. Analysis of climatic risk. Australian Journal of Agricultural Research, 44, 713-730.
  • Cieśla A., Kraszewski, W., Skowron, M., Syrek P. (2015). Wpływ działania pola magnetycznego na kiełkowanie nasion. Przegląd Elektrotechniczny, 91(1), 125-128.
  • Colbach, N., Debaeke, P. (1998). Integrating crop management and crop rotation effects into models of weed population dynamics: a review. Weed Science, 46, 717-728.
  • Colbach, N., Dürr, C., Roger-Estrade, J., Caneill, J. (2005). How to model the effects of farming practices on weed emergence. Weed Research, 45, 2-17.
  • Cousens, R., Moss, S.R. (1990). A model of the effects of cultivation on the vertical distribution of weed seeds within the soil. Weed Research, 30, 61-70.
  • Cussans, G.W., Raudonius, S., Brain, P., Cumberworth, S. (1996). Effects of depth of seed burial and soil aggregate size on seedling emergence of Alopecurus myosuroides, Galiumaparine, Stellaria media, i wheat (Triticum aestivum). Weed Research, 36, 133-142.
  • Evans, E.J., Ludeke, F. (1987). Effect of sowing date on the flower and pod development of four winter oilseed rape cultivars. Annals of Applied Biology, 110, 170-171.
  • Fidanza, M., Dernoeden, P.H., Zhang, M. (1996). Degree-days for predicting smooth crabgrass emergence in cool-season turf. Crop Science, 36, 990-996.
  • Forcella, F. (1993). Seedling emergence model for velvetleaf. Agronomy Journal, 85, 929-933.
  • Forcella, F. (1998). Real-time assessment of seed dormancy and seedling growth for weed management. Seed Science Research, 8, 201-209.
  • Forcella, F., Benech-Arnold, R.L., Sánchez, R.A., Ghersa, C.M. (2000). Modeling seedling emergence. Field Crops Research, 67, 123-139.
  • Forcella, F., Durgan, B.R., Buhler, D.D. (1996). Management of weed seedbanks. In: Streibig, J. (Ed.), Proceedings of the Second International Weed Control Congress. International Weed Science Society, Copenhagen, 21-26.
  • Francik, S., Ślipek, Z., Frączek, J., Knapczyk, A. (2016). Present trends in research on application of artificial neural networks in agricultural engineering. Agricultural Engineering, 20(4), 15-25.
  • Fyfield, T.P., Gregory, P.J. (1989). Effects of temperature and water potential on germination, radicle elongation and emergence of mungbean. Journal of Experimental Botany, 40, 667-674.
  • Grundy, A.C. (2003). Predicting weed emergence: a review of approaches and future challenges. Weed Research, 43, 1-11.
  • Grundy, A.C., Mead, A., Bond, W. (1996). Modelling the effects of weed-seed distribution in the soil profile on seedling emergence. Weed Research, 36, 375-384.
  • Gummerson, R.J. (1986). The effect of constant temperatures and osmotic potential on the germination of sugar beet. Journal of Experimental Botany, 37, 729-741.
  • Habekotté, B. (1997). A model of the phenological development of winter oilseed rape. Field Crops Research, 54, 127-136.
  • Hodges, T., Ritchie, J.T. (1991). The CERES-Wheat Phenology Model. Hodges T. (Ed.), Predicting Crop Phenology, CRC Press, Boston.
  • Hodgson, A.S. (1978). Rapeseed adaptation in Northern New South Wales. II. Predicting plant development of Brassica campestris L. and Brassica napus L. and its implications for planting time, designed to avoid water deficit and frost. Australian Journal of Agricultural Research, 29, 711-726.
  • Jakubowski, T. (2011). Model plonowania roślin ziemniaka (Solanum tuberosum L.) wyrosłych z sadzeniaków napromienionych mikrofalami. Acta Agrophysica, 17(2), 311-323.
  • Keating, B.A., McCown, R.L., Wafula, B.M. (1993). Adjustment of nitrogen inputs in response to a seasonal forecast in a region of high climatic risk. F.W.T. Penning de Vries, P. Teng, K. Metselaar (Eds.), Systems approaches for sustainable agricultural development, Kluwer Academic Publishers, Dordrecht, The Netherlis.
  • Kremer, E., Lotz, L.A. (1998). Germination and emergence characteristics of triazine-susceptible and triazine-resistant biotypes of Solanum nigrum. Journal of Applied Ecology, 35, 302-310.
  • Michałek, R. (2008). Przyszłość inżynierii rolniczej jako nauki i kierunku kształcenia. Inżynieria Rolnicza, 1(99), 297-302.
  • Miglietta, F. (1992). Simulation of wheat ontogenesis. Ph.D. Thesis, Agricultural University Wageningen i Accademia deiGeorgofili, Italy.
  • Myers, L.F., Christian, K.R., Kirchner, R.J. (1982). Flowering responses of 48 lines of oilseed rape (Brassica spp.) to vernalization i daylenth. Australian Journal of Agricultural Research, 33, 927-936.
  • Oryokot, J.O.E., Murphy, D.D., Thomas, A.G., Swanton, C.J. (1997). Temperature- and moisterdependent models of seed germination and shoot elongation in green and redroot pigweed (Amaranthus powellii, A. retroflexus). Weed Science, 45, 488-496.
  • Ritchie, J.T. (1993). Genetic specific data for crop modeling F. Penning de Vries, P. Teng, K. Metselaar (Eds.), Systems Approaches for Agricultural Development, Kluwer Academic Press, Boston. 77-93.
  • Roberts, E.H., Summerfield R.J. (1987). Measurements i prediction of flowering in annual crops.
  • Atherton J.G. (Ed.), Manipulation of Flowering, Butterworth, London.
  • Roman, E.S., Murphy, S.D., Swanton, C.J. (2000). Simulation of Chenopodium album seedling emergence. Weed Science, 48, 217-224.
  • Roman, E.S., Thomas, A.G., Murphy, S.D., Swanton, C.J. (1999). Modelling germination and seedling elongation of common lambsquarters (Chenopodium album). Weed Science, 47, 149-155.
  • Rötter, R., Dreiser C. (1994). Extrapolation of maize fertiliser trial results by using crop-growth simulation: results for Murang'a District, Kenya. L.O. Fresco, L. Stroosnijder, J. Bouma, H. van Keulen (Eds.). The future of the li: mobilising and integrating knowledge for li use options, John Wiley & Sons Ltd, West Sussex, UK.
  • Ungar, E.D. (1990). Management of agropastoral systems in a semiarid region Simulation Monographs. PUDOC, Wageningen, The Netherlis.
  • Weir, A.H., Braggs, P.L., Porter, J.R., Rayner, J.H. (1984). A winter wheat crop simulation model without water or nutrient limitations. The Journal of Agricultural Science, 102, 371-382.
Typ dokumentu
Bibliografia
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Identyfikator YADDA
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