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Su Kısıtı Koşullarında Ayçiçeği Veriminin Optimizasyonu: Sulama Stratejileri, Tohum Çeşitleri ve Simülasyon Modellerinin Karşılaştırmalı Analizi

Year 2025, Volume: 22 Issue: 2, 496 - 512, 26.05.2025
https://doi.org/10.33462/jotaf.1567064

Abstract

Bu çalışma, iklim değişikliğinin neden olduğu artan su kısıtlamalarının ayçiçeği verimi üzerindeki etkisini ve farklı tohum çeşitlerinin bu zorlayıcı koşullara uyumunu incelemiştir. Üç sulama stratejisi uygulanmıştır: S0 (sulamadan), S1 (kısmi sulama) ve S2 (tam sulama). Ayrıca, iki ayçiçeği çeşidi olan Sanay ve Pioneer kullanılarak sulama ve tohum çeşitlerinin yaprak alan indeksi (LAI), normalize edilmiş fark bitki indeksi (NDVI), bitki boyu ve verim gibi temel parametreler üzerindeki etkileri değerlendirilmiştir. Sonuçlar, Pioneer çeşidinin genel olarak Sanay'a kıyasla daha yüksek LAI ve verim değerleri sergilediğini ortaya koymuştur. En yüksek LAI değeri olan 4.43, Temmuz ayında tam sulama (S2) altında kaydedilmiştir. NDVI sonuçları, tam sulanan Pioneer bitkilerinin daha yüksek fotosentetik aktivite gösterdiğini ve su stresine daha iyi uyum sağladığını göstermektedir. Sanay çeşidi ise sulama olmaksızın (S0) bile daha uzun bitkiler ve nispeten yüksek biyokütle üretimi ile dikkat çekmiştir. Ancak, Pioneer çeşidi optimum su koşulları altında en yüksek verim performansını sağlamıştır. Her iki çeşit de en yüksek verim değerlerini S2 sulama stratejisinde elde etmiş olup, etkili su yönetiminin ayçiçeği üretimi için önemini vurgulamaktadır. Deneysel verileri desteklemek amacıyla AquaCrop, DSSAT ve WOFOST olmak üzere üç farklı ürün simülasyon modeli kullanılarak verim tahminleri yapılmıştır. Bu modeller arasında, AquaCrop en doğru tahminleri sağlamış ve özellikle tam sulama koşullarında gözlemlenen verim değerleri ile güçlü bir uyum göstermiştir. Ancak, modeller arasında gözlemlenen tahmin farklılıkları, bu araçların farklı çevresel koşullara göre dikkatle değerlendirilmesi gerektiğini ortaya koymaktadır. Sonuç olarak, uygun tohum çeşitlerinin seçimi ve optimize edilmiş sulama stratejilerinin geliştirilmesi, iklim değişikliğinin neden olduğu su kıtlığı koşullarında tarımsal sürdürülebilirliğin sağlanması açısından kritik öneme sahiptir. Farklı sulama rejimleri altında ürün verimlerinin doğru bir şekilde simüle edilmesi, karar verme süreçlerini destekleyebilir; ancak model çıktılarındaki değişkenlik, modellerin çevresel faktörler göz önüne alınarak doğrulanmasının gerekliliğini göstermektedir.

Ethical Statement

Bu çalışma için etik kuruldan izin alınmasına gerek yoktur.

Supporting Institution

TAGEM (Tarımsal Araştırmalar ve Politikalar Genel Müdürlüğü)

Project Number

TAGEM/TSKA/16/A13/P08/01/A.P-7

References

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Optimizing Sunflower Yield Under Water Constraints: A Comparative Analysis of Irrigation Strategies, Seed Varieties, and Simulation Models

Year 2025, Volume: 22 Issue: 2, 496 - 512, 26.05.2025
https://doi.org/10.33462/jotaf.1567064

Abstract

This study explored the impact of increasing water restrictions, driven by climate change, on sunflower yield and assessed the adaptability of different seed varieties to these challenging conditions. Three irrigation strategies were applied: S0 (no irrigation), S1 (semi-irrigation), and S2 (full irrigation). Two sunflower cultivars, Sanay and Pioneer, were tested to evaluate how irrigation and seed variety influence key parameters such as leaf area index (LAI), normalized difference vegetation index (NDVI), plant height, and yield. The results indicated that the Pioneer variety generally exhibited higher LAI and yield values compared to Sanay. The maximum LAI value of 4.43 was observed in July under full irrigation (S2). NDVI results further supported these findings, showing that fully irrigated Pioneer plants had higher photosynthetic activity, indicating better adaptation to water stress. While Sanay produced taller plants and relatively high biomass even without irrigation (S0), Pioneer achieved superior yield performance under optimal water conditions. Both cultivars recorded their highest yields under the S2 treatment, highlighting the significance of effective water management for sunflower production. To complement the experimental data, yield predictions were performed using three crop simulation models: AquaCrop, DSSAT, and WOFOST. Among these, AquaCrop provided the most accurate predictions, especially under full irrigation, showing strong alignment with observed yield values. However, the variability observed in model predictions emphasizes the need for careful assessment of these tools across different environmental conditions. In conclusion, selecting appropriate seed varieties and developing optimized irrigation strategies are critical for maintaining agricultural sustainability under water-limited conditions driven by climate change. The accurate simulation of crop yields under different irrigation regimes can further support decision-making processes, but variability in model outputs highlights the importance of model validation based on environmental factors.

Ethical Statement

There is no need to obtain permission from the ethics committee for this study.

Supporting Institution

TAGEM (General Directorate of Agricultural Research and Policies)

Project Number

TAGEM/TSKA/16/A13/P08/01/A.P-7

References

  • Abedinpour, M. (2021). The Comparison of DSSAT-CERES and AquaCrop Models for Wheat Under Water–Nitrogen Interactions. Communications in Soil Science and Plant Analys, 52: 2002-2017. https://doi.org/10.1080/00103624.2021.1908323
  • Anonymous (2022a). Meteoroloji Genel Müdürlüğü (MGM) Türkiye climate. https://www.mgm.gov.tr/iklim/turkiye-iklimi.aspx. Accessed Date: 10.05.2023.
  • Anonymous (2022b) Tekirdağ Ticaret ve Sanayi Odaso (TTSO). Agriculture. http://www.tekirdagtso.org.tr/tr/tarim-16 (Accessed Date: 10.08.2022).
  • Aydoğdu, M., Yıldız, H., Gürkan, H., Sırlı, B. A., and Tuğaç, M. G. (2023). Evaluation of yield prediction performance of DSSAT CSM-CERES-Wheat model in some bread wheat varieties. International Journal of Environmental and Geoinformatics, 10(1): 51-66.
  • Begna, T. (2020). Effects of drought stress on crop production and productivity. International Journal of Research Studies in Agricultural Sciences, 6(9): 34-43.
  • Bingham, F. and Martin, J. (1956). Effects of soil phosphorus on growth and minor element nutrition of citrus. Soil Science Society of America Journal, 20(3): 382-385. https://doi.org/10.2136/SSSAJ1956.03615995002000030023X
  • Blake, G. R. and Hartge, K. H. (1986). Bulk density. In: Klute, A. (Ed.), Methods of soil analysis: Part 1 Physical and mineralogical methods, 5: 363-375.
  • Blum, A. (2009). Effective use of water (EUW) and not water-use efficiency (WUE) is the target of crop yield improvement under drought stress. Field Crops Research, 112: 119-123. https://doi.org/10.1016/j.fcr.2009.03.009
  • Boote, K. J., Jones, J. W. and Hoogenboom, G. (2018). Simulation of crop growth: CROPGRO model. In: Peart, R.M. (Ed.), Agricultural systems modeling and simulation (pp. 651-692). CRC Press.
  • Castañeda-Vera, A., Leffelaar, P. A., Álvaro-Fuentes, J., Cantero-Martínez, C. and Mínguez, M. I. (2015). Selecting crop models for decision making in wheat insurance. European Journal of Agronomy, 68: 97-116.
  • Connor, D. J. and Hall, A. J. (1997). Sunflower physiology. In: Sunflower Technology and Production, Ed(s): Schneiter, A. A. pp. 113-182. https://doi.org/10.2134/agronmonogr35.c4
  • Debaeke, P., Bedoussac, L., Bonnet, C., Bret-Mestries, E., Seassau, C., Gavaland, A. and Justes, E. (2017). Sunflower crop: Environmental-friendly and agroecological. Oilseeds and Fats, Crops and Lipids, 24(3): D304.
  • Dewenam, L., Er-raki, S., Ezzahar, J. and Chehbouni, A. (2021). Performance evaluation of the WOFOST model for estimating evapotranspiration, soil water content, grain yield and total above-ground biomass of winter wheat in Tensift Al Haouz (Morocco): Application to yield gap estimation. Agronomy, 11(12): 2480. https://doi.org/10.3390/agronomy11122480
  • Elsadek, E., Zhang, K., Mousa, A., Ezaz, G. T., Tola, T. L., Shaghaleh, H. and Alhaj Hamoud, Y. (2023). Study on the in-field water balance of direct-seeded rice with various irrigation regimes under arid climatic conditions in Egypt using the AquaCrop model. Agronomy, 13(2): 609.
  • Eltarabily, M., Burke, J. and Bali, K. (2020). Impact of deficit irrigation on shallow saline groundwater contribution and sunflower productivity in the Imperial Valley, California. Water, 12(2): 571. https://doi.org/10.3390/w12020571
  • Fahad, S., Bajwa, A., Nazir, U., Anjum, S., Farooq, A., Zohaib, A., Sadia, S., Nasim, W., Adkins, S., Saud, S., Ihsan, M., Alharby, H., Wu, C., Wang, D. and Huang, J. (2017). Crop production under drought and heat stress: Plant responses and management options. Frontiers in Plant Science, 8: 1147. https://doi.org/10.3389/fpls.2017.01147
  • Farooq, M., Wahid, A., Kobayashi, N., Fujita, D. and Basra, S. (2011). Plant drought stress: Effects, mechanisms and management. Agronomy for Sustainable Development, 29: 185-212. https://doi.org/10.1051/agro:2008021
  • Fulda, S., Mikkat, S., Stegmann, H. and Horn, R. (2011). Physiology and proteomics of drought stress acclimation in sunflower (Helianthus annuus L.). Plant Biology, 13(4): 632-642. https://doi.org/10.1111/j.1438-8677.2010.00426.x
  • Garofalo, P. and Rinaldi, M. (2015). Leaf gas exchange and radiation use efficiency of sunflower (Helianthus annuus L.) in response to different deficit irrigation strategies: From solar radiation to plant growth analysis. European Journal of Agronomy, 64: 88-97. https://doi.org/10.1016/j.eja.2014.12.010
  • Gee, G. W., and Bauder, J. W. (1986). Particle Size Analysis. In: Methods of Soil Analysis: Part 1 Physical And Mineralogical Methods. Ed(s): Klute, A., pp. 383-411, ASA-SSSA.
  • Gomez, K. A. and Gomez, A. A. (1984). Statistical Procedures for Agricultural Research. John Wiley & Sons, New York, U.S.A.
  • Gürkan, H. (2023). Evaluation of the impacts of climate change on sunflower with AquaCrop model. Tekirdağ Journal of Agricultural Faculty, 20(4): 933-947.
  • Hsiao, T. C., Heng, L., Steduto, P., Rojas‐Lara, B., Raes, D. and Fereres, E. (2009). AquaCrop—the FAO crop model to simulate yield response to water: III. Parameterization and testing for maize. Agronomy Journal, 101(3): 448-459.
  • Hussain, M., Farooq, S., Hasan, W., Ul-Allah, S., Tanveer, M., Farooq, M. and Nawaz, A. (2018). Drought stress in sunflower: Physiological effects and its management through breeding and agronomic alternatives. Agricultural Water Management, 201: 152-166. https://doi.org/10.1016/j.agwat.2018.01.028
  • Hussain, M., Rauf, S., Riaz, M., Al-Khayri, J. and Monneveux, P. (2017). Determination of drought tolerance related traits in Helianthus argophyllus, Helianthus annuus, and their hybrids. Breeding Science, 67: 257-267. https://doi.org/10.1270/jsbbs.16095
  • Jackson, M. L. (1979). Soil Chemical Analysis: Advanced Course. Department of Soil Science, University of Wisconsin, Madison, WI, U.S.A.
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There are 56 citations in total.

Details

Primary Language English
Subjects Irrigation Systems
Journal Section Articles
Authors

Ozan Öztürk 0000-0001-8329-2739

Erdem Bahar 0000-0002-2579-5060

Selçuk Özer 0000-0002-6055-4377

Cantekin Kıvrak 0000-0002-6221-2469

Mehmet Gür 0000-0001-7752-1910

Fatih Bakanoğulları 0000-0001-6329-5422

Volkan Atav 0000-0003-2719-8398

Project Number TAGEM/TSKA/16/A13/P08/01/A.P-7
Early Pub Date May 8, 2025
Publication Date May 26, 2025
Submission Date October 15, 2024
Acceptance Date April 16, 2025
Published in Issue Year 2025 Volume: 22 Issue: 2

Cite

APA Öztürk, O., Bahar, E., Özer, S., Kıvrak, C., et al. (2025). Optimizing Sunflower Yield Under Water Constraints: A Comparative Analysis of Irrigation Strategies, Seed Varieties, and Simulation Models. Tekirdağ Ziraat Fakültesi Dergisi, 22(2), 496-512. https://doi.org/10.33462/jotaf.1567064
AMA Öztürk O, Bahar E, Özer S, Kıvrak C, Gür M, Bakanoğulları F, Atav V. Optimizing Sunflower Yield Under Water Constraints: A Comparative Analysis of Irrigation Strategies, Seed Varieties, and Simulation Models. JOTAF. May 2025;22(2):496-512. doi:10.33462/jotaf.1567064
Chicago Öztürk, Ozan, Erdem Bahar, Selçuk Özer, Cantekin Kıvrak, Mehmet Gür, Fatih Bakanoğulları, and Volkan Atav. “Optimizing Sunflower Yield Under Water Constraints: A Comparative Analysis of Irrigation Strategies, Seed Varieties, and Simulation Models”. Tekirdağ Ziraat Fakültesi Dergisi 22, no. 2 (May 2025): 496-512. https://doi.org/10.33462/jotaf.1567064.
EndNote Öztürk O, Bahar E, Özer S, Kıvrak C, Gür M, Bakanoğulları F, Atav V (May 1, 2025) Optimizing Sunflower Yield Under Water Constraints: A Comparative Analysis of Irrigation Strategies, Seed Varieties, and Simulation Models. Tekirdağ Ziraat Fakültesi Dergisi 22 2 496–512.
IEEE O. Öztürk, E. Bahar, S. Özer, C. Kıvrak, M. Gür, F. Bakanoğulları, and V. Atav, “Optimizing Sunflower Yield Under Water Constraints: A Comparative Analysis of Irrigation Strategies, Seed Varieties, and Simulation Models”, JOTAF, vol. 22, no. 2, pp. 496–512, 2025, doi: 10.33462/jotaf.1567064.
ISNAD Öztürk, Ozan et al. “Optimizing Sunflower Yield Under Water Constraints: A Comparative Analysis of Irrigation Strategies, Seed Varieties, and Simulation Models”. Tekirdağ Ziraat Fakültesi Dergisi 22/2 (May 2025), 496-512. https://doi.org/10.33462/jotaf.1567064.
JAMA Öztürk O, Bahar E, Özer S, Kıvrak C, Gür M, Bakanoğulları F, Atav V. Optimizing Sunflower Yield Under Water Constraints: A Comparative Analysis of Irrigation Strategies, Seed Varieties, and Simulation Models. JOTAF. 2025;22:496–512.
MLA Öztürk, Ozan et al. “Optimizing Sunflower Yield Under Water Constraints: A Comparative Analysis of Irrigation Strategies, Seed Varieties, and Simulation Models”. Tekirdağ Ziraat Fakültesi Dergisi, vol. 22, no. 2, 2025, pp. 496-12, doi:10.33462/jotaf.1567064.
Vancouver Öztürk O, Bahar E, Özer S, Kıvrak C, Gür M, Bakanoğulları F, Atav V. Optimizing Sunflower Yield Under Water Constraints: A Comparative Analysis of Irrigation Strategies, Seed Varieties, and Simulation Models. JOTAF. 2025;22(2):496-512.