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Current IssueEditorial BoardOnline First ArticlesArchive

Research Article

volume 39 issue 3 (september 2018) : 234-240,   Doi: 10.18805/ag.R-1691

Use of WOFOST model in agriculture- A review 

N
Nilesh J. Hadiya
N
Neeraj Kumar
B
B.M. Mote
1Agricultural Meteorological Cell, N. M. College of Agriculture, Navsari Agricultural University, Navsari-396 450, Gujarat, India.
Cite article:- Hadiya J. Nilesh, Kumar Neeraj, Mote B.M. (2018). Use of WOFOST model in agriculture- A review. Agricultural Reviews. 39(3): 234-240. doi: 10.18805/ag.R-1691.

ABSTRACT

To full fill the demands of increasing population for agricultural products, increases pressure on land, water, and other natural resources, to fulfils this demands and to take decision about agricultural product requires information about production, productivity  of crop also for proper management and carried out intercultural operations  need advanced information about crop phenology, pest and diseases presently it is possible to generate such advanced information through well validated crop growth simulation models such as CERES, WOFOST, SUCROS, and APSIM. These models provided such advanced information based on integrate the effects of different factors viz., increasing temperature, soil productivity, also consider changes in climatic on productivity. The present paper describes the review of research work done on crop simulation model as well as covers detailed information about WOFOST model. 

REFERENCES

  1. B. M. Mote and Neeraj Kumar (2016). Calibration and validation of CERES-rice model for different rice cultivars at Navsari. Journal of Agrometeorology.18, 1: 156-157.
  2. B. M. Mote, M. J. Vasani, H. K. Ahir, S. B. Yadav and Vyas Pandey. (2016). Simulation of Phenology and Yield Attributing Characters of Legume Crops Using DSSAT and InfoCrop Model. Advances in Life Sciences 5 (13): 5265-5271.
  3. Boogaard, H. L., Van Diepen, C. A., Rötter, R. P., Cabrera, J. C. M. A., Van Laar, H. H., 1998, “User guide for the WOFOST 7.1 crop growth simulation model and WOFOST Control Center 5.1”. Techn. Doc. 52, Alterra, WUR, Wageningen, the Netherlands.
  4. Boogaard, H., Wolf, J., Supit, I., Niemeyer, S. and van Ittersum, M. A. (2013). “Regional implementation of WOFOST for calculating yield gaps of autumn-sown wheat across the European Union”. Field Crops Research, 143: 130–142.
  5. Cheng, Z., Meng, and Wang, Yiming. (2016). “Improving Spring Maize Yield Estimation at Field Scale by Assimilating Time-Series HJ-1 CCD Data into the WOFOST Model Using a New Method with Fast Algorithms”. Remote Sensing, 8: 4, 303.
  6. Das, P., Samantaray, S. and Rout, G. R. (1997). “Studies on cadmium toxicity in plants: a review”. Environmental Pollution, 98, 1: 29–36.
  7. Dias, M. C., Monteiro, C., Moutinho-Pereira, J., Correia, C., Goncalves, B. and Santos, C. (2012). “Cadmium toxicity affects photosynthesis and plant growth at different levels”. ActaPhysiologiaePlantarum, 35, 4: 1281–1289.
  8. Driessen, P. M. (1986). “The collection and treatment of basic data Introduction”, In: Van Keulen and Wolf, 1986, 203-207.
  9. Hengsdijk, H., Meijerink, G. W., and Mosugu, M. E. (2005). “Modeling the effect of three soil and water conservation practices in Tigray, Ethiopia”.Agriculture, Ecosystem and Environment, 105, 29–40.
  10. Jin, M., Liu, X., Wu, L. and Liu, M., 2015, “An improved assimilation method with stress factors incorporated in the WOFOST model for the efficient assessment of heavy metal stress levels in rice”.International Journal of Applied Earth Observation and Geoinformation, 41, 118-129.
  11. Jones, J. W., Hoogenboom, G., Porter, C., Boote, K. J., Batchelor, W. D., Hunt, L.A., Wilkens, P., Singh, U., Gijsman, A., Ritchie, J. T., 2003, “DSSAT cropping system model”.Europian Journal of Agronomy, 18, 235-265.
  12. Kropff, M. J., Van Laar H. H. and Ten Berge H. F. M., (Eds.), 1993, “ORYZA1 A basic model for irrigated lowland rice production”. IRRI, Los Banos, The Philippines.
  13. Krupa, Z., Siedlecka, A. and Kleczkowski, L. A., 1999, “Cadmium-affected level of inorganic phosphate in rye leaves influences Rubisco subunits”. ActaPhysiologiaePlantarum,21, 3, 257–261.
  14. Liu, F., Liu, X., Ding, C. and Wu, L., (2015), “The dynamic simulation of rice growth parameters under cadmium stress with the assimilation of multi-period spectral indices and crop model”. Field Crop Research, 183, 225-234.
  15. Liu, F., Liu, X., Zhao, L., Ding, C., Jiang, J. and Wu, L., 2015, “The dynamic assessment model for monitoring cadmium stress levels in rice based on the assimilation of remote sensing and the WOFOST model”. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8, 1330–1338.
  16. Lu, C. and Fan, L. (2013). “Winter wheat yield potentials and yield gaps in the North China Plain”.Field Crops Research, 143, 98–105.
  17. Ma, G. N., Huang, J. X., Wu, W. B., Fan, J. L., Zou, J. Q. and Wu, S. J. (2013). “Assimilation of MODIS-LAI into the WOFOST model for forecasting regional winter wheat yield”. Math.Comput. Model, 58, 634–643.
  18. Macdonald, R. B. and Hall, F. G., (1980) “Global crop forecasting”. Science,208: 670–679.
  19. Matthews, R. B., and Stephens, W., (2002), “Crop-soil Simulation Models. Applications in Developing Countries”, CABI Publishing, pp. 277.
  20. Monteiro, M. S., Santos, C., Soares, A. M. V. M. and Mann, R. M., 2009, “Assessment of biomarkers of cadmium stress in lettuce”.    Ecotoxicology and Environmental Safety, 72, 3, 811–818.
  21. Passioura, J. B., 1996, “Simulation Models: Science, Snake oil, Education,or Engineering?” Agronomy Journal, 88, 690-704.
  22. Penning de Vries, F. W. T., Jansen, D. M., ten Berge, H. F. M. and Bakema, A., (1989), “Simulation of ecophysiological processes of growth in several annual crops”.Simulation Monographs,29, Pudoc, Wageningen.
  23. Rabbinge, R. and. de Wit, C. T. (1989). Systems, models and simulation, 3-15.
  24. Rahman, A. M., Hasegawa, H., Rahman, M. M., Islam, N. M., Miah, M. M. A. and Tasmen, A. (2007). “Effect of arsenic on photosynthesis, growth and yield of five widely cultivated rice (Oryzasativa L.)varieties in Bangladesh”. Chemosphere, 67, 6, 1072–1079.
  25. Ren, J. Q., Chen, Z. X., Tang, H. J., Zhou, Q. B. and Qin, J. (2011). “Regional crop yield simulation based on crop growth model and remote sensing data”. Trans. CSAE, 27, 8, 257–264.
  26. Spitter, C. J. T., van Keulen, H. and van Kraalingen, D. W. G. (1989). “A simple and universal crop growth simulator: SUCROS87. In: Simulation and Systems Management in Crop Protection”. Eds: R. Rabbinge; S. A. Ward and H. H. van Laar. Simulation Monographs 32.Pudoc, Wageningen. pp. 147-181.
  27. Supit, I., Diepen, V. C. A., de Wit, A. J. W., Wolf, J., Kabat, P., Baruth, B and Ludwig, F. (2010). “Recent changes in the climatic yield potential of various crops in Europe”. Agricultural System. 683–694.
  28. Supit, I., Diepen, V. C. A., de Wit, A. J. W., Wolf, J., Kabat, P., Baruth, B and Ludwig, F. (2012). “Assessing climate change effects on European crop yields using the crop growth monitoring system and a weather generator”. Agricultural and Forest Meteorology, 164, 96–111.
  29. Supit, I., Hooijer, A. A., van, C. A. and Diepen (eds.). (1994). “System description of the WOFOST 6.0 crop simulation model implemented in CGMS”, European Communities, 1, 8-10.
  30. Tao, S., Shen, Shuanghe., Li, Y. and Mugume, I. (2016). “Projected Crop Production under Regional Climate Change Using Scenario Data and Modeling: Sensitivity to Chosen Sowing Date and Cultivar”. Sustainability, 8, 3, 214.
  31. Van Diepen, C. A., Van Keulen, H., Penning de Vries, F. W. T., Noij, I. G. A. M. and Goudriaan, J. (1987). “Simulated variability of wheat and rice in current weather conditions and in future weather when ambient CO2 has doubled. Simulation Reports CABO-TT 14. CABO-DLO, WAU-TPE, Wageningen: 40p
  32. Van Ittersum, M. K., Leffelaar, P. A., Van Keulen, H., Kropff, M. J., Bastiaans, L., Goudriaan, J., (2003). “On approaches and applications of the Wageningen crop models”, European Journal of Agronomy, 18, 201-234.
  33. Van Keulen, H. and Van Diepen, C. A., (1990). “Crop growth models and agro-ecological characterization” In: Scaife, A. (Ed.): Proceedings of the first congress of the European society of agronomy, 5-7 December 1990, Paris. CEC, ESA, INRA. session 2:1-16.
  34. Van Keulen, H. and Wolf, J. (1986). “Modeling of agricultural production: weather, soils and crops, Simulation Monographs, Pudoc, Wageningen.
  35. Van Laar, H. H., Goudriaan J. and van Keulen, H. (1992). “Simulation of crop growth for potential and water limited production situations (as applied to spring wheat)”.Department of TheoreticalProduction Ecology (TPE-WAU) and DLO-Centre for Agrobiological Research (CABO-DLO),Wageningen, The Netherlands. 78 pp.
  36. Wolf, J. and Van Diepen, C. A. (1991). Effects of climate change on crop production in the Rhine basin. Report 52. RIZA, SC-DLO, Wageningen: 144p.
  37. Wolf, J. and Van Diepen, C. A. (1994). Effects of climate change on silage maize production potential in the European Community. Agr Forest Meteorol 71(1/2): 33-60.
  38. Wolf, J. and Van Diepen, C. A. (1995). Effects of climate change on grain maize yield potential in the European community. Climatic Change 29: 299-3.
  39. Wu, L., Liu, X. N., Wang, P., Zhou, B. T., Liu, M. L. and Li, X. Q. (2013). “The assimilation of spectral sensing and the WOFOST model for the dynamic simulation of cadmium accumulation in rice tissues”. International Journal of Applied Earth Observation 25, 66–75.
  40. Wu, L., Liu, X. N., Zhou, B. T., Li, L. F. and Tan, Z. (2012). “Spatial-time continuous changes simulation of crop growth parameters with multi-source remote sensing data and crop growth model”, Journal of Remote Sensing. 1173–1191.
  41. Yadav, S. B., Misra, A. K., Mishra, S. K. and Pandey V. (2018). Crop growth simulation models (InfoCrop v.2.1, DSSATv4.5, WOFOSTv1.5 and Cropsytv 4.19) software, Water and Energy Security in The Arena of Climate Change. 34, 456-469.
  42. Zhao, Y. X., Chen, S. N. and Shen, S. H. (2013). “Assimilating remote sensing information with crop model using Ensemble Kalman Filter for improving LAI monitoring and yield estimation”. Ecological Model. 270: 30–42. 
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    Research Article

    volume 39 issue 3 (september 2018) : 234-240,   Doi: 10.18805/ag.R-1691

    Use of WOFOST model in agriculture- A review 

    N
    Nilesh J. Hadiya
    N
    Neeraj Kumar
    B
    B.M. Mote
    1Agricultural Meteorological Cell, N. M. College of Agriculture, Navsari Agricultural University, Navsari-396 450, Gujarat, India.
    Cite article:- Hadiya J. Nilesh, Kumar Neeraj, Mote B.M. (2018). Use of WOFOST model in agriculture- A review. Agricultural Reviews. 39(3): 234-240. doi: 10.18805/ag.R-1691.

    ABSTRACT

    To full fill the demands of increasing population for agricultural products, increases pressure on land, water, and other natural resources, to fulfils this demands and to take decision about agricultural product requires information about production, productivity  of crop also for proper management and carried out intercultural operations  need advanced information about crop phenology, pest and diseases presently it is possible to generate such advanced information through well validated crop growth simulation models such as CERES, WOFOST, SUCROS, and APSIM. These models provided such advanced information based on integrate the effects of different factors viz., increasing temperature, soil productivity, also consider changes in climatic on productivity. The present paper describes the review of research work done on crop simulation model as well as covers detailed information about WOFOST model. 

    REFERENCES

    1. B. M. Mote and Neeraj Kumar (2016). Calibration and validation of CERES-rice model for different rice cultivars at Navsari. Journal of Agrometeorology.18, 1: 156-157.
    2. B. M. Mote, M. J. Vasani, H. K. Ahir, S. B. Yadav and Vyas Pandey. (2016). Simulation of Phenology and Yield Attributing Characters of Legume Crops Using DSSAT and InfoCrop Model. Advances in Life Sciences 5 (13): 5265-5271.
    3. Boogaard, H. L., Van Diepen, C. A., Rötter, R. P., Cabrera, J. C. M. A., Van Laar, H. H., 1998, “User guide for the WOFOST 7.1 crop growth simulation model and WOFOST Control Center 5.1”. Techn. Doc. 52, Alterra, WUR, Wageningen, the Netherlands.
    4. Boogaard, H., Wolf, J., Supit, I., Niemeyer, S. and van Ittersum, M. A. (2013). “Regional implementation of WOFOST for calculating yield gaps of autumn-sown wheat across the European Union”. Field Crops Research, 143: 130–142.
    5. Cheng, Z., Meng, and Wang, Yiming. (2016). “Improving Spring Maize Yield Estimation at Field Scale by Assimilating Time-Series HJ-1 CCD Data into the WOFOST Model Using a New Method with Fast Algorithms”. Remote Sensing, 8: 4, 303.
    6. Das, P., Samantaray, S. and Rout, G. R. (1997). “Studies on cadmium toxicity in plants: a review”. Environmental Pollution, 98, 1: 29–36.
    7. Dias, M. C., Monteiro, C., Moutinho-Pereira, J., Correia, C., Goncalves, B. and Santos, C. (2012). “Cadmium toxicity affects photosynthesis and plant growth at different levels”. ActaPhysiologiaePlantarum, 35, 4: 1281–1289.
    8. Driessen, P. M. (1986). “The collection and treatment of basic data Introduction”, In: Van Keulen and Wolf, 1986, 203-207.
    9. Hengsdijk, H., Meijerink, G. W., and Mosugu, M. E. (2005). “Modeling the effect of three soil and water conservation practices in Tigray, Ethiopia”.Agriculture, Ecosystem and Environment, 105, 29–40.
    10. Jin, M., Liu, X., Wu, L. and Liu, M., 2015, “An improved assimilation method with stress factors incorporated in the WOFOST model for the efficient assessment of heavy metal stress levels in rice”.International Journal of Applied Earth Observation and Geoinformation, 41, 118-129.
    11. Jones, J. W., Hoogenboom, G., Porter, C., Boote, K. J., Batchelor, W. D., Hunt, L.A., Wilkens, P., Singh, U., Gijsman, A., Ritchie, J. T., 2003, “DSSAT cropping system model”.Europian Journal of Agronomy, 18, 235-265.
    12. Kropff, M. J., Van Laar H. H. and Ten Berge H. F. M., (Eds.), 1993, “ORYZA1 A basic model for irrigated lowland rice production”. IRRI, Los Banos, The Philippines.
    13. Krupa, Z., Siedlecka, A. and Kleczkowski, L. A., 1999, “Cadmium-affected level of inorganic phosphate in rye leaves influences Rubisco subunits”. ActaPhysiologiaePlantarum,21, 3, 257–261.
    14. Liu, F., Liu, X., Ding, C. and Wu, L., (2015), “The dynamic simulation of rice growth parameters under cadmium stress with the assimilation of multi-period spectral indices and crop model”. Field Crop Research, 183, 225-234.
    15. Liu, F., Liu, X., Zhao, L., Ding, C., Jiang, J. and Wu, L., 2015, “The dynamic assessment model for monitoring cadmium stress levels in rice based on the assimilation of remote sensing and the WOFOST model”. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8, 1330–1338.
    16. Lu, C. and Fan, L. (2013). “Winter wheat yield potentials and yield gaps in the North China Plain”.Field Crops Research, 143, 98–105.
    17. Ma, G. N., Huang, J. X., Wu, W. B., Fan, J. L., Zou, J. Q. and Wu, S. J. (2013). “Assimilation of MODIS-LAI into the WOFOST model for forecasting regional winter wheat yield”. Math.Comput. Model, 58, 634–643.
    18. Macdonald, R. B. and Hall, F. G., (1980) “Global crop forecasting”. Science,208: 670–679.
    19. Matthews, R. B., and Stephens, W., (2002), “Crop-soil Simulation Models. Applications in Developing Countries”, CABI Publishing, pp. 277.
    20. Monteiro, M. S., Santos, C., Soares, A. M. V. M. and Mann, R. M., 2009, “Assessment of biomarkers of cadmium stress in lettuce”.    Ecotoxicology and Environmental Safety, 72, 3, 811–818.
    21. Passioura, J. B., 1996, “Simulation Models: Science, Snake oil, Education,or Engineering?” Agronomy Journal, 88, 690-704.
    22. Penning de Vries, F. W. T., Jansen, D. M., ten Berge, H. F. M. and Bakema, A., (1989), “Simulation of ecophysiological processes of growth in several annual crops”.Simulation Monographs,29, Pudoc, Wageningen.
    23. Rabbinge, R. and. de Wit, C. T. (1989). Systems, models and simulation, 3-15.
    24. Rahman, A. M., Hasegawa, H., Rahman, M. M., Islam, N. M., Miah, M. M. A. and Tasmen, A. (2007). “Effect of arsenic on photosynthesis, growth and yield of five widely cultivated rice (Oryzasativa L.)varieties in Bangladesh”. Chemosphere, 67, 6, 1072–1079.
    25. Ren, J. Q., Chen, Z. X., Tang, H. J., Zhou, Q. B. and Qin, J. (2011). “Regional crop yield simulation based on crop growth model and remote sensing data”. Trans. CSAE, 27, 8, 257–264.
    26. Spitter, C. J. T., van Keulen, H. and van Kraalingen, D. W. G. (1989). “A simple and universal crop growth simulator: SUCROS87. In: Simulation and Systems Management in Crop Protection”. Eds: R. Rabbinge; S. A. Ward and H. H. van Laar. Simulation Monographs 32.Pudoc, Wageningen. pp. 147-181.
    27. Supit, I., Diepen, V. C. A., de Wit, A. J. W., Wolf, J., Kabat, P., Baruth, B and Ludwig, F. (2010). “Recent changes in the climatic yield potential of various crops in Europe”. Agricultural System. 683–694.
    28. Supit, I., Diepen, V. C. A., de Wit, A. J. W., Wolf, J., Kabat, P., Baruth, B and Ludwig, F. (2012). “Assessing climate change effects on European crop yields using the crop growth monitoring system and a weather generator”. Agricultural and Forest Meteorology, 164, 96–111.
    29. Supit, I., Hooijer, A. A., van, C. A. and Diepen (eds.). (1994). “System description of the WOFOST 6.0 crop simulation model implemented in CGMS”, European Communities, 1, 8-10.
    30. Tao, S., Shen, Shuanghe., Li, Y. and Mugume, I. (2016). “Projected Crop Production under Regional Climate Change Using Scenario Data and Modeling: Sensitivity to Chosen Sowing Date and Cultivar”. Sustainability, 8, 3, 214.
    31. Van Diepen, C. A., Van Keulen, H., Penning de Vries, F. W. T., Noij, I. G. A. M. and Goudriaan, J. (1987). “Simulated variability of wheat and rice in current weather conditions and in future weather when ambient CO2 has doubled. Simulation Reports CABO-TT 14. CABO-DLO, WAU-TPE, Wageningen: 40p
    32. Van Ittersum, M. K., Leffelaar, P. A., Van Keulen, H., Kropff, M. J., Bastiaans, L., Goudriaan, J., (2003). “On approaches and applications of the Wageningen crop models”, European Journal of Agronomy, 18, 201-234.
    33. Van Keulen, H. and Van Diepen, C. A., (1990). “Crop growth models and agro-ecological characterization” In: Scaife, A. (Ed.): Proceedings of the first congress of the European society of agronomy, 5-7 December 1990, Paris. CEC, ESA, INRA. session 2:1-16.
    34. Van Keulen, H. and Wolf, J. (1986). “Modeling of agricultural production: weather, soils and crops, Simulation Monographs, Pudoc, Wageningen.
    35. Van Laar, H. H., Goudriaan J. and van Keulen, H. (1992). “Simulation of crop growth for potential and water limited production situations (as applied to spring wheat)”.Department of TheoreticalProduction Ecology (TPE-WAU) and DLO-Centre for Agrobiological Research (CABO-DLO),Wageningen, The Netherlands. 78 pp.
    36. Wolf, J. and Van Diepen, C. A. (1991). Effects of climate change on crop production in the Rhine basin. Report 52. RIZA, SC-DLO, Wageningen: 144p.
    37. Wolf, J. and Van Diepen, C. A. (1994). Effects of climate change on silage maize production potential in the European Community. Agr Forest Meteorol 71(1/2): 33-60.
    38. Wolf, J. and Van Diepen, C. A. (1995). Effects of climate change on grain maize yield potential in the European community. Climatic Change 29: 299-3.
    39. Wu, L., Liu, X. N., Wang, P., Zhou, B. T., Liu, M. L. and Li, X. Q. (2013). “The assimilation of spectral sensing and the WOFOST model for the dynamic simulation of cadmium accumulation in rice tissues”. International Journal of Applied Earth Observation 25, 66–75.
    40. Wu, L., Liu, X. N., Zhou, B. T., Li, L. F. and Tan, Z. (2012). “Spatial-time continuous changes simulation of crop growth parameters with multi-source remote sensing data and crop growth model”, Journal of Remote Sensing. 1173–1191.
    41. Yadav, S. B., Misra, A. K., Mishra, S. K. and Pandey V. (2018). Crop growth simulation models (InfoCrop v.2.1, DSSATv4.5, WOFOSTv1.5 and Cropsytv 4.19) software, Water and Energy Security in The Arena of Climate Change. 34, 456-469.
    42. Zhao, Y. X., Chen, S. N. and Shen, S. H. (2013). “Assimilating remote sensing information with crop model using Ensemble Kalman Filter for improving LAI monitoring and yield estimation”. Ecological Model. 270: 30–42. 
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