IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i9p1515-d1470582.html
   My bibliography  Save this article

The Impact of Crop Year and Crop Density on the Production of Sunflower in Site-Specific Precision Farming in Hungary

Author

Listed:
  • János Nagy

    (Kerpely Kálmán Doctoral School, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi Street, H-4032 Debrecen, Hungary)

  • Mihály Zalai

    (Plant Protection Institute, Department of Integrated Plant Protection, Hungarian University of Agriculture and Life Sciences (MATE), 1 Páter Károly Street, H-2100 Gödöllő, Hungary)

  • Árpád Illés

    (Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi Street, H-4032 Debrecen, Hungary)

  • Szabolcs Monoki

    (Kerpely Kálmán Doctoral School, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi Street, H-4032 Debrecen, Hungary)

Abstract

Sunflower is considered a plant with extraordinary adaptability. However, the conditions of growing sunflower function as a limiting factor in its production. The hybrids used in production tolerate weather variability to a different level and utilise the nutrient and water resources of the soil, while the yield is also affected by the number of plants per hectare. In this study, the authors attempted to observe the environmental effects influencing sunflower cultivation, the heterogeneous productivity zones of the given production site and the correlation of the number of seeding plants used under various farm practices. The average rainfall of 2021 and the dry weather of 2022 created suitable conditions for examining the yearly weather effect. In the selected experimental areas, three distinguishable zones were defined in terms of productivity. In each productivity zone, three crop density steps were used in four replicates. Based on the performed comparative tests, the rainy year of 2021 resulted higher yield than the drier year of 2022 in the average- and high productivity zones, while in the low-productivity zone, higher yields were harvested under the drier conditions of 2022 than in the rainy year of 2021. In 2021, with the improvement in productivity, the obtained yield was also higher. However, in 2022, this clarity could not be demonstrated. In the zones with low productivity, identical yield results were observed in both weather conditions. Based on the examination of the obtained results, it was shown that the effect of weather conditions and the given number of plants have a smaller influence on the yield results of low-productivity zones, while these factors have a greater influence on the yields of high-productivity zones.

Suggested Citation

  • János Nagy & Mihály Zalai & Árpád Illés & Szabolcs Monoki, 2024. "The Impact of Crop Year and Crop Density on the Production of Sunflower in Site-Specific Precision Farming in Hungary," Agriculture, MDPI, vol. 14(9), pages 1-14, September.
  • Handle: RePEc:gam:jagris:v:14:y:2024:i:9:p:1515-:d:1470582
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/9/1515/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/14/9/1515/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Justin Sheffield & Eric F. Wood & Michael L. Roderick, 2012. "Little change in global drought over the past 60 years," Nature, Nature, vol. 491(7424), pages 435-438, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Linghui Guo & Yuanyuan Luo & Yao Li & Tianping Wang & Jiangbo Gao & Hebing Zhang & Youfeng Zou & Shaohong Wu, 2023. "Spatiotemporal Changes and the Prediction of Drought Characteristics in a Major Grain-Producing Area of China," Sustainability, MDPI, vol. 15(22), pages 1-19, November.
    2. Rengui Jiang & Jiancang Xie & Hailong He & Jungang Luo & Jiwei Zhu, 2015. "Use of four drought indices for evaluating drought characteristics under climate change in Shaanxi, China: 1951–2012," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(3), pages 2885-2903, February.
    3. Kaustubh Salvi & Subimal Ghosh, 2016. "Projections of Extreme Dry and Wet Spells in the 21st Century India Using Stationary and Non-stationary Standardized Precipitation Indices," Climatic Change, Springer, vol. 139(3), pages 667-681, December.
    4. Hongli Wang & Yongxiang Zhang & Xuemei Shao, 2021. "A tree-ring-based drought reconstruction from 1466 to 2013 CE for the Aksu area, western China," Climatic Change, Springer, vol. 165(1), pages 1-16, March.
    5. Ashenafi Yimam Kassaye & Guangcheng Shao & Xiaojun Wang & Shiqing Wu, 2021. "Quantification of drought severity change in Ethiopia during 1952–2017," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(4), pages 5096-5121, April.
    6. Youxin Wang & Tao Peng & Qingxia Lin & Vijay P. Singh & Xiaohua Dong & Chen Chen & Ji Liu & Wenjuan Chang & Gaoxu Wang, 2022. "A New Non-stationary Hydrological Drought Index Encompassing Climate Indices and Modified Reservoir Index as Covariates," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(7), pages 2433-2454, May.
    7. Luo, Erga & Yan, Ru & He, Yaping & Han, Zhen & Feng, Yiyu & Qian, Wenrong & Li, Jinkai, 2024. "Does biogas industrial policy promote the industrial transformation?," Resources Policy, Elsevier, vol. 88(C).
    8. Vladimir Marković & Imre Nagy & Andras Sik & Kinga Perge & Peter Laszlo & Maria Papathoma-Köhle & Catrin Promper & Thomas Glade, 2016. "Assessing drought and drought-related wildfire risk in Kanjiza, Serbia: the SEERISK methodology," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(2), pages 709-726, January.
    9. Mitter, Hermine & Schmid, Erwin, 2019. "Computing the economic value of climate information for water stress management exemplified by crop production in Austria," Agricultural Water Management, Elsevier, vol. 221(C), pages 430-448.
    10. Shahzada Adnan & Kalim Ullah, 2020. "Development of drought hazard index for vulnerability assessment in Pakistan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 2989-3010, September.
    11. Pere Quintana-Seguí & Anaïs Barella-Ortiz & Sabela Regueiro-Sanfiz & Gonzalo Miguez-Macho, 2020. "The Utility of Land-Surface Model Simulations to Provide Drought Information in a Water Management Context Using Global and Local Forcing Datasets," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(7), pages 2135-2156, May.
    12. Jagadish Padhiary & Kanhu Charan Patra & Sonam Sandeep Dash, 2022. "A Novel Approach to Identify the Characteristics of Drought under Future Climate Change Scenario," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(13), pages 5163-5189, October.
    13. Shan Jiang & Jian Zhou & Guojie Wang & Qigen Lin & Ziyan Chen & Yanjun Wang & Buda Su, 2022. "Cropland Exposed to Drought Is Overestimated without Considering the CO 2 Effect in the Arid Climatic Region of China," Land, MDPI, vol. 11(6), pages 1-21, June.
    14. L. Lin & A. Gettelman & Q. Fu & Y. Xu, 2018. "Simulated differences in 21st century aridity due to different scenarios of greenhouse gases and aerosols," Climatic Change, Springer, vol. 146(3), pages 407-422, February.
    15. Francisco José Del-Toro-Guerrero & Luis Walter Daesslé & Rodrigo Méndez-Alonzo & Thomas Kretzschmar, 2022. "Surface Reflectance–Derived Spectral Indices for Drought Detection: Application to the Guadalupe Valley Basin, Baja California, Mexico," Land, MDPI, vol. 11(6), pages 1-19, May.
    16. Zhang, Yuliang & Wu, Zhiyong & Singh, Vijay P. & Lin, Qingxia & Ning, Shaowei & Zhou, Yuliang & Jin, Juliang & Zhou, Rongxing & Ma, Qiang, 2023. "Agricultural drought characteristics in a typical plain region considering irrigation, crop growth, and water demand impacts," Agricultural Water Management, Elsevier, vol. 282(C).
    17. Hans Visser & Arthur Petersen & Willem Ligtvoet, 2014. "On the relation between weather-related disaster impacts, vulnerability and climate change," Climatic Change, Springer, vol. 125(3), pages 461-477, August.
    18. Ruperto Ortiz-Gómez & Roberto S. Flowers-Cano & Guillermo Medina-García, 2022. "Sensitivity of the RDI and SPEI Drought Indices to Different Models for Estimating Evapotranspiration Potential in Semiarid Regions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(7), pages 2471-2492, May.
    19. Zablon W. Shilenje & Victor Ongoma & Mercy Njagi, 2019. "Applicability of Combined Drought Index in drought analysis over North Eastern Kenya," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 99(1), pages 379-389, October.
    20. Sergio M. Vicente-Serrano & Miquel Tomas-Burguera & Santiago Beguería & Fergus Reig & Borja Latorre & Marina Peña-Gallardo & M. Yolanda Luna & Ana Morata & José C. González-Hidalgo, 2017. "A High Resolution Dataset of Drought Indices for Spain," Data, MDPI, vol. 2(3), pages 1-10, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:14:y:2024:i:9:p:1515-:d:1470582. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.