Araştırma Makalesi
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Estimation of Wheat Yield with DSSAT Crop Simulation Model

Yıl 2024, Cilt: 1 Sayı: 2, 87 - 97, 30.12.2024

Öz

In this study, the integration of wheat into the crop simulation model (CSM) was examined in order to determine the climatic changes that may occur in Mersin region conditions in the future between 2018-2019. In this sense, the possible usage of Ceres sub-model of DSSAT crop simulation model in wheat was determined. Plant height (cm), leaf area index (cm2 cm-2), biomass (kg ha-1) and yield (kg ha-1) values obtained in the field and estimated by the DSSAT model were compared and t test was applied at 5% significance level. In both years of the study, the parameters measured in the field and predicted by the model were not found to be statistically significant (P > 0.05), while the leaf area index values were significant. The DSSAT-Ceres crop simulation model estimated yield value of 584-397 kg ha-1 in 2018 and 2019, respectively, while field measurements were obtained as 622-380 kg ha-1. It was concluded that the DSSAT-CSM can predict wheat with the plant genetic coefficients obtained as a result of calibration.

Proje Numarası

TAGEM/TSKA/16/A13/P08/01

Kaynakça

  • Ahmed, M., Bilal, M., & Ahmad, S. (2024). Simulation of source sink partitioning in wheat under varying nitrogen regimes using DSSAT-CERES-wheat model. Agricultural Water Management, 303, 109028.
  • Asseng, S., Jamieson, P. D., Kimball, B. A., Pinter, P. J., Sayre, K. D., Bowden, J. W., & Howden, M. S. (2004). Simulated wheat growth affected by rising temperature, increased water deficit and elevated atmospheric CO2. Field Crops Research, 85(2–3), 85–102. https:// doi.org/10.1016/S0378-4290(03)00154-0
  • Attia, A., Rajan, N., Xue, Q., Nair, S., Ibrahim, A., & Hays, D. (2016). Application of DSSAT-CERES-Wheat model to simulate winter wheat response to irrigation management in the Texas High Plains. Agricultural Water Management, 165, 50-60.
  • Boote, K. J., Jones, J. W., Hoogenboom, G., Batchelor, W. D., Porter, C. H. (2004). Cropgro Plant Growth And Partitioning Module. Agricultural and Biological Engineering Department Research Report No 2000-1204. University of Florida, Gainesville, Florida.
  • Demelash, T., Amou, M., Gyilbag, A., Tesfay, G., Xu, Y. (2022). Adaptation Potential of Current Wheat Cultivars and Planting Dates under the Changing Climate in Ethiopia. Agronomy, 12(1):37. https://doi.org/10.3390/agronomy12010037
  • Ewert, F. (2004). Modelling plant responses to elevated CO2 : How important is leaf area index? Annals of Botany, 93(6), 619–627. https://doi.org/10.1093/aob/mch101
  • Gürkan, H. (2019). Konya Havzasında Iklim Değişikliğinin Ayçiçeği (Helianthus Annuus L) Verimine Olası Etkilerinin Tahmin Edilmesi. Ankara Üniversitesi Fen Bilimleri Enstitüsü, Doktora Tezi, Ankara.
  • Hoogenboom, G., Jones, J.W., Boote, K.J. (1991). A Decision Support System for Prediction of Corn Yield, Evapotranspiration and Irrigation Management. Irrigation And Drainage, 198-204 p.
  • IPCC, (2023). Summary for Policymakers. In: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (eds.)]. IPCC, Geneva, Switzerland, pp. 1-34, doi: 10.59327/IPCC/AR6-9789291691647.001
  • İKDB, (2024). T.C. Çevre, Şehircilik ve İklim Değişikliği Bakanlığı. İklim Değişikliği Başkanlığı. https://iklim.gov.tr/sss/temel-kavramlar. Erişim Tarihi: (05.11.2024). Kassie, B.T., Asseng, S., Porter, C.H., Royce, F.S. (2016). Performance of DSSAT-Nwheat across a wide range of current and future growing conditions. European Journal of Agronomy. 81:27-36. https://doi.org/10.1016/j.eja.2016.08.012
  • Kumar, K., Parihar, C.M., Nayak, H.S. et al. Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system. Scientific Reports 14, 11743. https://doi.org/10.1038/s41598-024-61976-6
  • Lal, D., & Niwas, R. (2024). Yield Predication by DSSAT Model of Wheat Crop: A Review. International Journal of Environment and Climate Change, 14(2), 519-524.
  • Liu, H., Liu, H., Lei, Q., Zhai, L., WANG, H., ZHANG, J., Zhu Y., Liu, S., Li, S., ZHANG, J., LIU, X. (2017). Using the DSSAT model to simulate wheat yield and soil organic carbon under a wheat-maize cropping system in the North China Plain. Journal of Integrative Agriculture. 16(10): 2300-2307. ISSN 2095-3119, https://doi.org/10.1016/S2095-3119(17)61678-2
  • Li, W., Liu, W., Huang, Y., Xiao, W., Xu, L., Pan, K., & Li, C. (2024). Modeling the Effects of Sowing Dates on Maize in Different Environments in the Tropical Area of Southwest China Using DSSAT. Agronomy, 14(12), 2819.
  • Mor, A. (2005). Bitki - İklim Modeli Dssat Kullanılarak Bursa’da Farklı Su Uygulama Düzeylerinin Analizi. Uludağ Üniversitesi Teknik Bilimler Meslek Yüksek Okulu-Doktora Tezi. Bursa.
  • Nargund, R., Bhatia, V. S., Sinha, N. K., Mohanty, M., Jayaraman, S., Dang, Y. P., Dalal, R. C. (2024). Assessing Soybean Yield Potential and Yield Gap in Different Agroecological Regions of India Using the DSSAT Model. Agronomy, 14(9), 1929.
  • Pouryazdankhah, H., Shahnazari, A., Ahmadi, M. Z., Khaledian, M., & Andersen, M. N. (2024). Development and validation of a sunflower crop growth module for the Daisy model. Frontiers in Sustainable Food Systems, 8, 1370063.
  • UNEP, (2021). Emissions Gap Report 2021, https://www.unep.org/resources/emissions-gap-report-2021. Erişim tarihi: (05.11.2024).
  • TEPGE, (2023). Durum ve Tahmin/Buğday. Tarımsal Ekonomi ve Politika Geliştirme Enstitüsü. https://arastirma.tarimorman.gov.tr/tepge/Belgeler/PDF%20DurumTahmin%20Raporlar%C4%B1/2023%20DurumTahmin%20Raporlar%C4%B1/Bu%C4%9Fday%20Durum%20Tahmin%20Raporu%202023 384%20TEPGE.pdf. Erişim tarihi: 06.11.2024.
  • TÜSİAD, (2020). Tarım ve Gıda 2020. Sürdürülebilir Büyüme Bağlamında Tarım ve Gıda Sektörününü Analizi. ISBN: 978-605-165-045-6.
  • Yang, Y.H., Masataka, W., Zhang, X.Y., Hao, X.H. & Zhang, J.Q. (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. Hydrological Process, 20, 2787–2802. https://doi.org/10.1002/hyp.6071
  • Zhang, L., Cao, Z., Gao, Y., Huang, W., Si, Z., Guo, Y., Wang, H., Wang, X. (2024). Soybean Yield Simulation and Sustainability Assessment Based on the DSSAT-CROPGRO-Soybean Model. Plants, 13(17), 2525.

DSSAT Bitki Simülasyon Modeli ile Buğday’da Verim Tahmini

Yıl 2024, Cilt: 1 Sayı: 2, 87 - 97, 30.12.2024

Öz

Bu çalışmada 2018-2019 yılları arasında Mersin yöresi koşullarında gelecek yıllarda oluşabilecek iklimsel değişikliklerin belirlenebilmesi amacıyla Buğday bitkisinin bitki simlasyon modeline olan entegrasyonu incelenmiştir. Bu anlamda DSSAT bitki simülasyon modeline ait Ceres alt modelinin buğday bitkisinde kullanım durumu belirlenmiştir. Arazide elde edilen ve model tarafından kestirilen bitki boyu (cm), yaprak alan indeksi (cm2 cm-2), biyokütle (kg ha-1) ile verim (kg ha-1) değerleri karşılatırılarak %5 önem seviyesinde t testi uygulanmıştır. Araştırmanın her iki yılında da arazide ölçülen ve modelin kestirdiği anılan parametrelerde %5 önem seviyesinde farklılıklar görülmemişken yaprak alan indeksi değeri farklılık göstermiştir. DSSAT-Ceres bitki simülasyon modeli 2018 ve 2019 yıllaında sırası ile 5840-3970 kg ha-1 verim değeri elde ederken arazi ölçümleri ise 6220-3800 kg ha-1 şeklinde elde edilmiştir. DSSAT bitki simülasyon modelinin kalibrasyon sonucu elde edilen bitki genetik katsayıları ile buğday tahmini yapabileceği sonucuna varılmıştır.

Proje Numarası

TAGEM/TSKA/16/A13/P08/01

Kaynakça

  • Ahmed, M., Bilal, M., & Ahmad, S. (2024). Simulation of source sink partitioning in wheat under varying nitrogen regimes using DSSAT-CERES-wheat model. Agricultural Water Management, 303, 109028.
  • Asseng, S., Jamieson, P. D., Kimball, B. A., Pinter, P. J., Sayre, K. D., Bowden, J. W., & Howden, M. S. (2004). Simulated wheat growth affected by rising temperature, increased water deficit and elevated atmospheric CO2. Field Crops Research, 85(2–3), 85–102. https:// doi.org/10.1016/S0378-4290(03)00154-0
  • Attia, A., Rajan, N., Xue, Q., Nair, S., Ibrahim, A., & Hays, D. (2016). Application of DSSAT-CERES-Wheat model to simulate winter wheat response to irrigation management in the Texas High Plains. Agricultural Water Management, 165, 50-60.
  • Boote, K. J., Jones, J. W., Hoogenboom, G., Batchelor, W. D., Porter, C. H. (2004). Cropgro Plant Growth And Partitioning Module. Agricultural and Biological Engineering Department Research Report No 2000-1204. University of Florida, Gainesville, Florida.
  • Demelash, T., Amou, M., Gyilbag, A., Tesfay, G., Xu, Y. (2022). Adaptation Potential of Current Wheat Cultivars and Planting Dates under the Changing Climate in Ethiopia. Agronomy, 12(1):37. https://doi.org/10.3390/agronomy12010037
  • Ewert, F. (2004). Modelling plant responses to elevated CO2 : How important is leaf area index? Annals of Botany, 93(6), 619–627. https://doi.org/10.1093/aob/mch101
  • Gürkan, H. (2019). Konya Havzasında Iklim Değişikliğinin Ayçiçeği (Helianthus Annuus L) Verimine Olası Etkilerinin Tahmin Edilmesi. Ankara Üniversitesi Fen Bilimleri Enstitüsü, Doktora Tezi, Ankara.
  • Hoogenboom, G., Jones, J.W., Boote, K.J. (1991). A Decision Support System for Prediction of Corn Yield, Evapotranspiration and Irrigation Management. Irrigation And Drainage, 198-204 p.
  • IPCC, (2023). Summary for Policymakers. In: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (eds.)]. IPCC, Geneva, Switzerland, pp. 1-34, doi: 10.59327/IPCC/AR6-9789291691647.001
  • İKDB, (2024). T.C. Çevre, Şehircilik ve İklim Değişikliği Bakanlığı. İklim Değişikliği Başkanlığı. https://iklim.gov.tr/sss/temel-kavramlar. Erişim Tarihi: (05.11.2024). Kassie, B.T., Asseng, S., Porter, C.H., Royce, F.S. (2016). Performance of DSSAT-Nwheat across a wide range of current and future growing conditions. European Journal of Agronomy. 81:27-36. https://doi.org/10.1016/j.eja.2016.08.012
  • Kumar, K., Parihar, C.M., Nayak, H.S. et al. Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system. Scientific Reports 14, 11743. https://doi.org/10.1038/s41598-024-61976-6
  • Lal, D., & Niwas, R. (2024). Yield Predication by DSSAT Model of Wheat Crop: A Review. International Journal of Environment and Climate Change, 14(2), 519-524.
  • Liu, H., Liu, H., Lei, Q., Zhai, L., WANG, H., ZHANG, J., Zhu Y., Liu, S., Li, S., ZHANG, J., LIU, X. (2017). Using the DSSAT model to simulate wheat yield and soil organic carbon under a wheat-maize cropping system in the North China Plain. Journal of Integrative Agriculture. 16(10): 2300-2307. ISSN 2095-3119, https://doi.org/10.1016/S2095-3119(17)61678-2
  • Li, W., Liu, W., Huang, Y., Xiao, W., Xu, L., Pan, K., & Li, C. (2024). Modeling the Effects of Sowing Dates on Maize in Different Environments in the Tropical Area of Southwest China Using DSSAT. Agronomy, 14(12), 2819.
  • Mor, A. (2005). Bitki - İklim Modeli Dssat Kullanılarak Bursa’da Farklı Su Uygulama Düzeylerinin Analizi. Uludağ Üniversitesi Teknik Bilimler Meslek Yüksek Okulu-Doktora Tezi. Bursa.
  • Nargund, R., Bhatia, V. S., Sinha, N. K., Mohanty, M., Jayaraman, S., Dang, Y. P., Dalal, R. C. (2024). Assessing Soybean Yield Potential and Yield Gap in Different Agroecological Regions of India Using the DSSAT Model. Agronomy, 14(9), 1929.
  • Pouryazdankhah, H., Shahnazari, A., Ahmadi, M. Z., Khaledian, M., & Andersen, M. N. (2024). Development and validation of a sunflower crop growth module for the Daisy model. Frontiers in Sustainable Food Systems, 8, 1370063.
  • UNEP, (2021). Emissions Gap Report 2021, https://www.unep.org/resources/emissions-gap-report-2021. Erişim tarihi: (05.11.2024).
  • TEPGE, (2023). Durum ve Tahmin/Buğday. Tarımsal Ekonomi ve Politika Geliştirme Enstitüsü. https://arastirma.tarimorman.gov.tr/tepge/Belgeler/PDF%20DurumTahmin%20Raporlar%C4%B1/2023%20DurumTahmin%20Raporlar%C4%B1/Bu%C4%9Fday%20Durum%20Tahmin%20Raporu%202023 384%20TEPGE.pdf. Erişim tarihi: 06.11.2024.
  • TÜSİAD, (2020). Tarım ve Gıda 2020. Sürdürülebilir Büyüme Bağlamında Tarım ve Gıda Sektörününü Analizi. ISBN: 978-605-165-045-6.
  • Yang, Y.H., Masataka, W., Zhang, X.Y., Hao, X.H. & Zhang, J.Q. (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. Hydrological Process, 20, 2787–2802. https://doi.org/10.1002/hyp.6071
  • Zhang, L., Cao, Z., Gao, Y., Huang, W., Si, Z., Guo, Y., Wang, H., Wang, X. (2024). Soybean Yield Simulation and Sustainability Assessment Based on the DSSAT-CROPGRO-Soybean Model. Plants, 13(17), 2525.
Toplam 22 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Biyosistem
Bölüm Araştırma Makalesi
Yazarlar

Alper Baydar 0000-0002-1426-466X

Mete Özfidaner 0000-0002-8453-8136

Engin Gönen 0000-0002-0471-9376

Burak Dalkiliç 0000-0002-5317-2186

Proje Numarası TAGEM/TSKA/16/A13/P08/01
Yayımlanma Tarihi 30 Aralık 2024
Gönderilme Tarihi 6 Kasım 2024
Kabul Tarihi 12 Aralık 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 1 Sayı: 2

Kaynak Göster

APA Baydar, A., Özfidaner, M., Gönen, E., Dalkiliç, B. (2024). DSSAT Bitki Simülasyon Modeli ile Buğday’da Verim Tahmini. Özal Tarım Ve Gıda Bilimleri Dergisi, 1(2), 87-97.