Research Article
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Year 2023, Volume: 10 Issue: 1, 51 - 66, 19.03.2023

Metin Aydoğdu Hakan Yıldız Hüdaverdi Gürkan Belgin Alsancak Sırlı Murat Güven Tuğaç

https://doi.org/10.30897/ijegeo.1087591

Abstract

Supporting Institution

T.C. TARIM VE ORMAN BAKANLIĞI Tarımsal Araştırmalar Genel Müdürlüğü

Project Number

“Ulusal Ürün İzleme ve Verim Tahmini Ülkesel Projesi TAGEM /TSKA/ 16/ A13 /P08/ 01/ A.P.8/(Alt Uygulama İş Paketi A.P.İ.P.8.3

Thanks

Bu Araştırma 01.01.2016-31.12.2021 Yılları arası TAGEM Tarafından koordine edilen ve Tarla Bitkileri Merkez Araştırma Enstitüsü Coğrafi Bilgi Sistemleri Merkezi tarafından “Ulusal Ürün İzleme ve Verim Tahmini Ülkesel Projesi TAGEM /TSKA/ 16/ A13 /P08/ 01/ A.P.8” kapsamında Bitki Gelişim Modelleri ve CBS, UA Teknikleri ile Verim Tahmini ve Ürün İzleme) alt projesi (A.P.8) altında yürütülen DSSAT Modeli İle Buğday Verim Tahmini ve Ürün İzleme Haymana Örneği (Alt Uygulama İş Paketi A.P.İ.P.8.3) verilerinden faydalanılarak hazırlanmıştır.

References

  • Akalın, A., (1997). İklim Verilerinden Yararlanarak Türkiye Buğday Üretiminin Tahmini, TC. Devlet İstatistik Enstitüsü Uzmanlık Tezi. Ankara.
  • Balaghi, R., B. Tychon, H. Eerens, M. Jlibene. 2008. Empirical regression models using NDVI, rainfall and temperature data for the early prediction of wheat grain yields in Morocco. International Journal of Applied Earth Observation and Geoinformation 10 (2008) 438–452.
  • Booltink, H. W. G., & Verhagen, J. (1997). Using decision support systems to optimize barley management on spatial variable soil. In Applications of systems approaches at the field level (pp. 219-233). Springer, Dordrecht.
  • Booltink, H. W. G., Van Alphen, B. J., Batchelor, W. D., Paz, J. O., Stoorvogel, J. J., & Vargas, R. (2001). Tools for optimizing management of spatially-variable fields. Agricultural Systems, 70(2-3), 445-476.
  • Castrignano A, Katerji N, Karam F, Mastrorilli M, Hamdy A (1998). A modified version of CERES-Maize model for predicting crop response to salinity stress. Ecol. Modell. 111: 107-120.
  • Gabrielle B, Kengni L (1996). Analysis and field-evaluation of the CERES models’ soil components: nitrogen transfer and transformations. Soil Sci. Soc. Am. J. 60: 142-149.
  • Gabrielle B, Denoroy P, Gosse G, Justes E, Andersen MN (1998). Development and evaluation of a CERES-type model for winter oilseed rape. Field Crops Res. 57: 95-111.
  • Godwin DC, Ritchie JT, Singh U, Hunt L (1989). A user’s guide to CERES-Wheat v2. p. 10.
  • Gürkan, H.., 2019 Konya Havzasında İklim Değişikliğinin Ayçiçeği (Helianthus Annuus L.) Verimine Olası Etkilerinin Tahmin Edilmesi (Doktora Tezi).Ankara Üniversitesi Fen Bilimleri Enstitüsü.
  • Gürkan, H., Shelia, V., Bayraktar, N., Ersoy Yıldırım, Y., Yesilekin, N., Gunduz, A., Boote, K., Porter, C., Hoogenboom, G. 2021. Estimating the Potential Impact of Climate Change on Sunflower Yield in the Konya Province of Turkey. The Journal of Agricultural Science, 158(10), 806-818. https://doi.org/10.1017/S0021859621000101.
  • Güler, M. 1987. Orta Anadoluda Yıllık Meteorolojik Verilerin Buğday verimi İle İlişkileri ve Bu İlişkilerin VerimTahminlerinde Kullanılması. Türkiye Tahıl Simpozyumu. S: 271-278, 6-9 Ekim 1987, Bursa.
  • Hoffmann F, Ritchie JT (1993). Model for slurry and manure in CERES and similar models. J. Agron. Crop Sci. 170: 330-340.
  • Hoogenboom, G. (2000). Contribution of agrometeorology to the simulation of crop production and its applications. Agricultural and forest meteorology, 103(1-2), 137-157.
  • Hoogenboom, G., Jones, JW, Porter CH, Wilkens PW, Boote KJ,Batchelor WD, Hunt LA,Tsuji GY (2003). DSSAT v4 vol. 1 Univ.of Hawaii,Honolulu,HI.
  • Hoogenboom,G.,Porter,C.H.,Shelia,V.,Boote,K.J.,Singh,U.,White,J.W.,Hunt,L.A,Ogoshi,R.,Lizaso,J.I.,Koo,J.,Asseng,S.,Singels,A.,Moreno,L.P. and Jones,J.W.2019.Decision Support System for AgrotechnologyTransfer(DSSAT)Version4.7.DSSATFoundation,Gainesville,FL.Available at: www.DSSAT.net.
  • Hunkár M (1994). Validation of crop simulation model CERES-Maize. Quarterly J. Hungarian Meteorology Series 98: 37-46. Hunt, L.A., 1993. Designing improved plant types: a breeder’s viewpoint. In: Penning de Vries, F., Teng, P., Metselaar, K. (Eds.), Systems Approaches for Agricultural Development. Kluwer Academic Press, Boston, pp. 3 /17.
  • Iglesias, A., Rosenzweig, C., & Pereira, D. (2000). Agricultural impacts of climate change in Spain: developing tools for a spatial analysis. Global Environmental Change, 10(1), 69-80.
  • Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., & Ritchie, J. T. (2003). The DSSAT cropping system model. European journal of agronomy, 18(3-4), 235-265.
  • Landau S, Mitchell RAC, Barnett V, Colls JJ, Craigon J, Moore KL, Payne RW (1998).Testing winter wheat simulation models’ predictions against observed UK grain yields. Agric. For. Meteorol.89: 85-99.
  • Lobell B. L. (2013). The Use of satellit data for crop yield gap analysis. Field Crops Research 143 (2013) 56-64.
  • Loague K, Green RE (1991). Statistical and graphical methods for evaluating solute transport models: overview and application. J Contam Hydrol 7: 51-73.
  • Müjdeci M., A. Sarıyev, V. Polat. 2005. Buğday (Triticum aestivum L.) Veriminin Matematiksel Modellenmesi. Tarım Bilimleri Dergisi 2005, 11 (4) 349-353.
  • Nouna, B. B., Katerji, N., & Mastrorilli, M. (2000). Using the CERES-Maize model in a semi-arid Mediterranean environment. Evaluation of model performance. European Journal of Agronomy, 13(4), 309-322.
  • Özkan, B., ve Akçaöz, H., 2002. Impacts of Climate Factors on Yields for Selected Crops in Southern Turkey. Mitigation and Adaptation Strategies for Global Change, 7: 367-380.
  • Pecetti L., Hollington P.A., 1997. Application of the CERES-Wheat simulation model to durum wheat in two diverse mediterranean environments. European Journal of Agronomy.Volume 6, Issues 1–2, March 1997, Pages 125-139.
  • Raes, D., Steduto, P., Hsiao, T. C., Fereres, E., 2009, Chapter One: AquaCrop – The FAO crop model to simulate yield response to water, FAO, 1-10.
  • Ritchie JT (1991). Wheat Phasic Development. In: Hanks, J., Ritchie,J.T (eds), Modeling Plant and Soil Systems. ASA, CSSA, SSSA,Madison, WI, pp.31-54.
  • Ruiz-Nogueira B, Boote KJ, Sau F (2001). Calibration and use of CROPGRO-soybean model for improving soybean management under rainfed conditions in Galicia, Northwest Spain. Agric. Syst. 68: 151-173.
  • Saarikko RA (2000). Applying a site based crop model to estimate regional yields under current and changed climates. Ecol. Modell. 131: 191-206.
  • Saseendran SA, Nielsen DC, Ma L, Ahuja LR, Halvorson AD (2004). Modelling nitrogen management effects on winter wheat production using RZWQM and CERES-Wheat. Agron. J. 96: 615-630.
  • Şaylan, L., M. Durak ve B. Çaldağ. 1998. Dünya’da ve Türkiye’de Bitki-İklim (Bitki Gelişimi Simülasyonu) Modelleri. Tarım ve Orman Meteorolojisi’98 Sempozyumu, 1998, İstanbul Teknik Üniv. 275-283.
  • Schulthess, U., Timsina, J., Herrera, J. M., & McDonald, A. (2013). Mapping field-scale yield gaps for maize: An example from Bangladesh. Field Crops Research, 143, 151-156.
  • Semenov, M. A., Wolf, J., Evans, L. G., Eckersten, H., & Iglesias, A. (1996). Comparison of wheat simulation models under climate change. II. Application of climate change scenarios. Climate Research, 7(3), 271-281.
  • Sıbley A.M, Grassını P., Thomas N.E., Cassman K.G., Lobell, D.B. (2014) Testing Remote Sensing Approaches for Assessing Yield Variability among Maize Fields. Agron. J. Vol. 106: 24-32. Issue 1 2014.
  • Ursayev, O., A.J. Gijsman, J.W. Jones, G. Hoogenboom 2003. DSSAT V4 Soil Data Editing Program (Sbuild) A Decision Support System for Agrotechnology Transfer Version 4. Volume 2. p.81.
  • Willmott CJ, Ackleson SG, Davis RE, Feddema JJ, Klink KM, et al. (1985) Statistics for the evaluation and comparison of models. J Geophys Res 90: 8995-9005.Zalud Z, Stralkova R, Pokorny E, Podesvova J (2001). Estimation of winter wheat nitrogen stress using the CERES crop model. Rostl Vyroba. 47: 253-259.
  • Yang Y, Watanabe M, Zhang X, Hao X, Zhang J (2006). Estimation of groundwater use by crop production simulated by DSSAT-wheat and DSSAT-maize models in the piedmont region of the North China Plain.Hydrol. Process. 20: 2787-2802.
  • Zhang W. , Liu, W., Xue, Q., Chen, J., and Han, X., 2013, Evaluation of the AquaCrop model for simulating yield response of winter wheat to water on the southern Loess Plateau of China, Water Science & Technology 68,4.

Evaluation of Yield Prediction Performance of DSSAT CSM-CERES-Wheat Model in Some Bread Wheat Varieties

Year 2023, Volume: 10 Issue: 1, 51 - 66, 19.03.2023

Metin Aydoğdu Hakan Yıldız Hüdaverdi Gürkan Belgin Alsancak Sırlı Murat Güven Tuğaç

https://doi.org/10.30897/ijegeo.1087591

Abstract

Product simulation programs with DSSAT are based on the principle of predicting the potentials of yield and other phenological parameters of wheat varieties with different fertilizer application doses in different climatic and soil conditions. For this purpose, different wheat varieties (Bayraktar, Tosunbey) were used in order to test the use of the DSSAT simulation model in semi-arid conditions in the Ikizce experimental area of the Haymana District of Ankara Province, Field Crops Central Research Institute, during the 2017-2018 and 2018-2019 periods. The aim of this study is to predict yield in wheat varieties (Bayraktar, Tosunbey) using CERES and CROPGRO sub-models of DSSAT v.4.7.5 simulation model. In the study, the model was run at different nitrogen application doses (0, 6, 12, 18 kg/da) to reveal the yield prediction potential of the wheat cultivars in semi-arid conditions. For the calibration of the model, the grain yield, plant height and Leaf area index (LAI) data obtained were used in the first year of wheat development stage.The accuracy of the model, which was calibrated with the first year data, was tested with the second year data. For Bayraktar variety, the average measured yield obtained from different nitrogen dose applications (N0,N6,N18) for the 2017-2018 period is 373.3 kg/da, the simulated yield is 373.7 kg/da (N12 dose is neglected), the measured yield for 2018-2019 300. 5 kg/da, the simulated yield was found to be 291.3 kg/da.For the Tosunbey variety, the average yield measured for the 2017-2018 period was 370.0 kg/da, the simulated yield was 338.0 kg/da, the measured yield for the 2018-2019 year was 217.58 kg/da, and the estimated yield was 237.83 kg/da.

Keywords

Crop Simulation Modelling DSSAT CSM-CERES Fertilization Wheat Yield Estimate

Project Number

“Ulusal Ürün İzleme ve Verim Tahmini Ülkesel Projesi TAGEM /TSKA/ 16/ A13 /P08/ 01/ A.P.8/(Alt Uygulama İş Paketi A.P.İ.P.8.3

References

  • Akalın, A., (1997). İklim Verilerinden Yararlanarak Türkiye Buğday Üretiminin Tahmini, TC. Devlet İstatistik Enstitüsü Uzmanlık Tezi. Ankara.
  • Balaghi, R., B. Tychon, H. Eerens, M. Jlibene. 2008. Empirical regression models using NDVI, rainfall and temperature data for the early prediction of wheat grain yields in Morocco. International Journal of Applied Earth Observation and Geoinformation 10 (2008) 438–452.
  • Booltink, H. W. G., & Verhagen, J. (1997). Using decision support systems to optimize barley management on spatial variable soil. In Applications of systems approaches at the field level (pp. 219-233). Springer, Dordrecht.
  • Booltink, H. W. G., Van Alphen, B. J., Batchelor, W. D., Paz, J. O., Stoorvogel, J. J., & Vargas, R. (2001). Tools for optimizing management of spatially-variable fields. Agricultural Systems, 70(2-3), 445-476.
  • Castrignano A, Katerji N, Karam F, Mastrorilli M, Hamdy A (1998). A modified version of CERES-Maize model for predicting crop response to salinity stress. Ecol. Modell. 111: 107-120.
  • Gabrielle B, Kengni L (1996). Analysis and field-evaluation of the CERES models’ soil components: nitrogen transfer and transformations. Soil Sci. Soc. Am. J. 60: 142-149.
  • Gabrielle B, Denoroy P, Gosse G, Justes E, Andersen MN (1998). Development and evaluation of a CERES-type model for winter oilseed rape. Field Crops Res. 57: 95-111.
  • Godwin DC, Ritchie JT, Singh U, Hunt L (1989). A user’s guide to CERES-Wheat v2. p. 10.
  • Gürkan, H.., 2019 Konya Havzasında İklim Değişikliğinin Ayçiçeği (Helianthus Annuus L.) Verimine Olası Etkilerinin Tahmin Edilmesi (Doktora Tezi).Ankara Üniversitesi Fen Bilimleri Enstitüsü.
  • Gürkan, H., Shelia, V., Bayraktar, N., Ersoy Yıldırım, Y., Yesilekin, N., Gunduz, A., Boote, K., Porter, C., Hoogenboom, G. 2021. Estimating the Potential Impact of Climate Change on Sunflower Yield in the Konya Province of Turkey. The Journal of Agricultural Science, 158(10), 806-818. https://doi.org/10.1017/S0021859621000101.
  • Güler, M. 1987. Orta Anadoluda Yıllık Meteorolojik Verilerin Buğday verimi İle İlişkileri ve Bu İlişkilerin VerimTahminlerinde Kullanılması. Türkiye Tahıl Simpozyumu. S: 271-278, 6-9 Ekim 1987, Bursa.
  • Hoffmann F, Ritchie JT (1993). Model for slurry and manure in CERES and similar models. J. Agron. Crop Sci. 170: 330-340.
  • Hoogenboom, G. (2000). Contribution of agrometeorology to the simulation of crop production and its applications. Agricultural and forest meteorology, 103(1-2), 137-157.
  • Hoogenboom, G., Jones, JW, Porter CH, Wilkens PW, Boote KJ,Batchelor WD, Hunt LA,Tsuji GY (2003). DSSAT v4 vol. 1 Univ.of Hawaii,Honolulu,HI.
  • Hoogenboom,G.,Porter,C.H.,Shelia,V.,Boote,K.J.,Singh,U.,White,J.W.,Hunt,L.A,Ogoshi,R.,Lizaso,J.I.,Koo,J.,Asseng,S.,Singels,A.,Moreno,L.P. and Jones,J.W.2019.Decision Support System for AgrotechnologyTransfer(DSSAT)Version4.7.DSSATFoundation,Gainesville,FL.Available at: www.DSSAT.net.
  • Hunkár M (1994). Validation of crop simulation model CERES-Maize. Quarterly J. Hungarian Meteorology Series 98: 37-46. Hunt, L.A., 1993. Designing improved plant types: a breeder’s viewpoint. In: Penning de Vries, F., Teng, P., Metselaar, K. (Eds.), Systems Approaches for Agricultural Development. Kluwer Academic Press, Boston, pp. 3 /17.
  • Iglesias, A., Rosenzweig, C., & Pereira, D. (2000). Agricultural impacts of climate change in Spain: developing tools for a spatial analysis. Global Environmental Change, 10(1), 69-80.
  • Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., & Ritchie, J. T. (2003). The DSSAT cropping system model. European journal of agronomy, 18(3-4), 235-265.
  • Landau S, Mitchell RAC, Barnett V, Colls JJ, Craigon J, Moore KL, Payne RW (1998).Testing winter wheat simulation models’ predictions against observed UK grain yields. Agric. For. Meteorol.89: 85-99.
  • Lobell B. L. (2013). The Use of satellit data for crop yield gap analysis. Field Crops Research 143 (2013) 56-64.
  • Loague K, Green RE (1991). Statistical and graphical methods for evaluating solute transport models: overview and application. J Contam Hydrol 7: 51-73.
  • Müjdeci M., A. Sarıyev, V. Polat. 2005. Buğday (Triticum aestivum L.) Veriminin Matematiksel Modellenmesi. Tarım Bilimleri Dergisi 2005, 11 (4) 349-353.
  • Nouna, B. B., Katerji, N., & Mastrorilli, M. (2000). Using the CERES-Maize model in a semi-arid Mediterranean environment. Evaluation of model performance. European Journal of Agronomy, 13(4), 309-322.
  • Özkan, B., ve Akçaöz, H., 2002. Impacts of Climate Factors on Yields for Selected Crops in Southern Turkey. Mitigation and Adaptation Strategies for Global Change, 7: 367-380.
  • Pecetti L., Hollington P.A., 1997. Application of the CERES-Wheat simulation model to durum wheat in two diverse mediterranean environments. European Journal of Agronomy.Volume 6, Issues 1–2, March 1997, Pages 125-139.
  • Raes, D., Steduto, P., Hsiao, T. C., Fereres, E., 2009, Chapter One: AquaCrop – The FAO crop model to simulate yield response to water, FAO, 1-10.
  • Ritchie JT (1991). Wheat Phasic Development. In: Hanks, J., Ritchie,J.T (eds), Modeling Plant and Soil Systems. ASA, CSSA, SSSA,Madison, WI, pp.31-54.
  • Ruiz-Nogueira B, Boote KJ, Sau F (2001). Calibration and use of CROPGRO-soybean model for improving soybean management under rainfed conditions in Galicia, Northwest Spain. Agric. Syst. 68: 151-173.
  • Saarikko RA (2000). Applying a site based crop model to estimate regional yields under current and changed climates. Ecol. Modell. 131: 191-206.
  • Saseendran SA, Nielsen DC, Ma L, Ahuja LR, Halvorson AD (2004). Modelling nitrogen management effects on winter wheat production using RZWQM and CERES-Wheat. Agron. J. 96: 615-630.
  • Şaylan, L., M. Durak ve B. Çaldağ. 1998. Dünya’da ve Türkiye’de Bitki-İklim (Bitki Gelişimi Simülasyonu) Modelleri. Tarım ve Orman Meteorolojisi’98 Sempozyumu, 1998, İstanbul Teknik Üniv. 275-283.
  • Schulthess, U., Timsina, J., Herrera, J. M., & McDonald, A. (2013). Mapping field-scale yield gaps for maize: An example from Bangladesh. Field Crops Research, 143, 151-156.
  • Semenov, M. A., Wolf, J., Evans, L. G., Eckersten, H., & Iglesias, A. (1996). Comparison of wheat simulation models under climate change. II. Application of climate change scenarios. Climate Research, 7(3), 271-281.
  • Sıbley A.M, Grassını P., Thomas N.E., Cassman K.G., Lobell, D.B. (2014) Testing Remote Sensing Approaches for Assessing Yield Variability among Maize Fields. Agron. J. Vol. 106: 24-32. Issue 1 2014.
  • Ursayev, O., A.J. Gijsman, J.W. Jones, G. Hoogenboom 2003. DSSAT V4 Soil Data Editing Program (Sbuild) A Decision Support System for Agrotechnology Transfer Version 4. Volume 2. p.81.
  • Willmott CJ, Ackleson SG, Davis RE, Feddema JJ, Klink KM, et al. (1985) Statistics for the evaluation and comparison of models. J Geophys Res 90: 8995-9005.Zalud Z, Stralkova R, Pokorny E, Podesvova J (2001). Estimation of winter wheat nitrogen stress using the CERES crop model. Rostl Vyroba. 47: 253-259.
  • Yang Y, Watanabe M, Zhang X, Hao X, Zhang J (2006). Estimation of groundwater use by crop production simulated by DSSAT-wheat and DSSAT-maize models in the piedmont region of the North China Plain.Hydrol. Process. 20: 2787-2802.
  • Zhang W. , Liu, W., Xue, Q., Chen, J., and Han, X., 2013, Evaluation of the AquaCrop model for simulating yield response of winter wheat to water on the southern Loess Plateau of China, Water Science & Technology 68,4.
There are 38 citations in total.

Details

Primary Language English
Subjects Photogrammetry and Remote Sensing
Journal Section Research Articles
Authors

Metin Aydoğdu 0000-0001-6920-1976

Hakan Yıldız 0000-0002-7627-7503

Hüdaverdi Gürkan 0000-0003-1799-0090

Belgin Alsancak Sırlı 0000-0002-7779-6778

Murat Güven Tuğaç 0000-0001-5941-5487

Project Number “Ulusal Ürün İzleme ve Verim Tahmini Ülkesel Projesi TAGEM /TSKA/ 16/ A13 /P08/ 01/ A.P.8/(Alt Uygulama İş Paketi A.P.İ.P.8.3
Publication Date March 19, 2023
Published in Issue Year 2023 Volume: 10 Issue: 1

Cite

APA Aydoğdu, M., Yıldız, H., Gürkan, H., Alsancak Sırlı, B., et al. (2023). Evaluation of Yield Prediction Performance of DSSAT CSM-CERES-Wheat Model in Some Bread Wheat Varieties. International Journal of Environment and Geoinformatics, 10(1), 51-66. https://doi.org/10.30897/ijegeo.1087591

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