IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i19p12520-d930858.html
   My bibliography  Save this article

Potassium Determines Sugar Beets’ Yield and Sugar Content under Drip Irrigation Condition

Author

Listed:
  • Xiangwen Xie

    (College of Water Resource and Civil Engineering, China Agricultural University, Beijing 100083, China
    Institute of Soil Fertilizer and Agricultural Water Saving, Xinjiang Academy of Agricultural Sciences, Urumqi 830091, China
    Key Laboratory of Northwest Oasis Water-Saving Agriculture, Ministry of Agriculture and Rural Affairs, Shihezi 832000, China
    The authors contributed equally to this work.)

  • Qianqian Zhu

    (Institute of Soil Fertilizer and Agricultural Water Saving, Xinjiang Academy of Agricultural Sciences, Urumqi 830091, China
    The authors contributed equally to this work.)

  • Yongmei Xu

    (Institute of Soil Fertilizer and Agricultural Water Saving, Xinjiang Academy of Agricultural Sciences, Urumqi 830091, China
    The authors contributed equally to this work.)

  • Xiaopeng Ma

    (Institute of Soil Fertilizer and Agricultural Water Saving, Xinjiang Academy of Agricultural Sciences, Urumqi 830091, China)

  • Feng Ding

    (Institute of Soil Fertilizer and Agricultural Water Saving, Xinjiang Academy of Agricultural Sciences, Urumqi 830091, China)

  • Guangyong Li

    (College of Water Resource and Civil Engineering, China Agricultural University, Beijing 100083, China)

Abstract

Sugar beet is one of the main sugar crops and an important cash crop in the three northern regions of China (Northeast China, North China, and Northwest China). As an arid region, Xinjiang lacks water resources. The establishment of a reasonable drip-irrigation system for sugar beet in Xinjiang can not only achieve the goal of high quality and high yield, but is also crucial for the efficient utilization of water and fertilizer. This research was implemented in the experimental field of the Xinjiang Academy of Agricultural Sciences’ Sugar Beet Improvement Center in Manas County, Xinjiang, from the year 2019. Taking ST 15140 sugar beet as the experimental variety, a field study was conducted to investigate the effects of different irrigation and fertilization methods on the yield and sugar content of sugar beets. Ten treatments of two irrigation levels (W1: 4500 m 3 ha −1 , W2: 5400 m 3 ha −1 ) and five fertilization methods (F1, F2, F3, F4, and F5) were carried out in a randomized block design with three replications. The yield and sugar content; growth indicators such as leaf photosynthetic rate, stomatal conductance, chlorophyll content and intercellular CO 2 concentration; and fertilizer-use efficiency (nitrogen-use efficiency (NUE), phosphorus-use efficiency (PUE), and potassium-use efficiency (KUE)) during the sugar beet growing seasons were determined. The results indicated that the W1F3 (4500 m 3 ha −1 , N 229.5 kg ha −1 + P 2 O 5 180 kg ha −1 + K 2 O 202.5 kg ha −1 + hydroquinone 229.5 g ha −1 ) treatment had the highest yield and sugar content of 132.20 Mg ha−1 and 15.61%, respectively. For crop growth indicators, the photosynthetic rate (33.27 μmol m −2 s −1 ) and the stomatal conductance (252.67 mmol m −2 s −1 ) under W1F3 were both the highest among all of the treatments. The fertilizer-use efficiency in W1F3 was in the following order: KUE > NUE > PUE. The highest KUE (128.10%) and NUE (65.49%) occurred under W1F3 at the sugar accumulation stage of the crop growing season. In addition, K determined the yield and sugar content of sugar beet by influencing growth factors such as the photosynthetic rate, chlorophyll content, intercellular CO 2 concentration, along with the KUE, which explained 30.2%, 5.1%, 10%, and 14.7% of the variation in yield and sugar content, respectively. The results of this study indicated that the application of an inhibitor with optimized-minus-N fertilization under lower irrigation (W1F3) was the optimal treatment. Above all, K determined the yield and sugar contents of sugar beets, emphasizing the pivotal role of K in the growth, physiological processes, and output of sugar beets.

Suggested Citation

  • Xiangwen Xie & Qianqian Zhu & Yongmei Xu & Xiaopeng Ma & Feng Ding & Guangyong Li, 2022. "Potassium Determines Sugar Beets’ Yield and Sugar Content under Drip Irrigation Condition," Sustainability, MDPI, vol. 14(19), pages 1-13, September.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12520-:d:930858
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/19/12520/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/19/12520/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chen, Jinliang & Kang, Shaozhong & Du, Taisheng & Qiu, Rangjian & Guo, Ping & Chen, Renqiang, 2013. "Quantitative response of greenhouse tomato yield and quality to water deficit at different growth stages," Agricultural Water Management, Elsevier, vol. 129(C), pages 152-162.
    2. Sofia Hadir & Thomas Gaiser & Hubert Hüging & Miriam Athmann & Daniel Pfarr & Roman Kemper & Frank Ewert & Sabine Seidel, 2020. "Sugar Beet Shoot and Root Phenotypic Plasticity to Nitrogen, Phosphorus, Potassium and Lime Omission," Agriculture, MDPI, vol. 11(1), pages 1-20, December.
    3. Vazifedoust, M. & van Dam, J.C. & Feddes, R.A. & Feizi, M., 2008. "Increasing water productivity of irrigated crops under limited water supply at field scale," Agricultural Water Management, Elsevier, vol. 95(2), pages 89-102, February.
    4. Li, Xiaoliang & Liu, Fulai & Li, Guitong & Lin, Qimei & Jensen, Christian R., 2010. "Soil microbial response, water and nitrogen use by tomato under different irrigation regimes," Agricultural Water Management, Elsevier, vol. 98(3), pages 414-418, December.
    5. Topak, Ramazan & Acar, Bilal & Uyanöz, Refik & Ceyhan, Ercan, 2016. "Performance of partial root-zone drip irrigation for sugar beet production in a semi-arid area," Agricultural Water Management, Elsevier, vol. 176(C), pages 180-190.
    6. Yavuz, Duran & Seymen, Musa & Yavuz, Nurcan & Türkmen, Önder, 2015. "Effects of irrigation interval and quantity on the yield and quality of confectionary pumpkin grown under field conditions," Agricultural Water Management, Elsevier, vol. 159(C), pages 290-298.
    7. Rahil, M.H. & Antonopoulos, V.Z., 2007. "Simulating soil water flow and nitrogen dynamics in a sunflower field irrigated with reclaimed wastewater," Agricultural Water Management, Elsevier, vol. 92(3), pages 142-150, September.
    8. Kiymaz, Sultan & Ertek, Ahmet, 2015. "Yield and quality of sugar beet (Beta vulgaris L.) at different water and nitrogen levels under the climatic conditions of Kırsehir, Turkey," Agricultural Water Management, Elsevier, vol. 158(C), pages 156-165.
    9. Gencoglan, Cafer & Altunbey, Hasibe & Gencoglan, Serpil, 2006. "Response of green bean (P. vulgaris L.) to subsurface drip irrigation and partial rootzone-drying irrigation," Agricultural Water Management, Elsevier, vol. 84(3), pages 274-280, August.
    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. Qu, Zhaoming & Chen, Qi & Feng, Haojie & Hao, Miao & Niu, Guoliang & Liu, Yanli & Li, Chengliang, 2022. "Interactive effect of irrigation and blend ratio of controlled release potassium chloride and potassium chloride on greenhouse tomato production in the Yellow River Basin of China," Agricultural Water Management, Elsevier, vol. 261(C).
    2. Shu, Liang-Zuo & Liu, Rui & Min, Wei & Wang, Yao-sheng & Hong-mei, Yu & Zhu, Peng-fei & Zhu, Ji-rong, 2020. "Regulation of soil water threshold on tomato plant growth and fruit quality under alternate partial root-zone drip irrigation," Agricultural Water Management, Elsevier, vol. 238(C).
    3. Li, Huanhuan & Liu, Hao & Gong, Xuewen & Li, Shuang & Pang, Jie & Chen, Zhifang & Sun, Jingsheng, 2021. "Optimizing irrigation and nitrogen management strategy to trade off yield, crop water productivity, nitrogen use efficiency and fruit quality of greenhouse grown tomato," Agricultural Water Management, Elsevier, vol. 245(C).
    4. Liu, Minguo & Wu, Xiaojuan & Yang, Huimin, 2022. "Evapotranspiration characteristics and soil water balance of alfalfa grasslands under regulated deficit irrigation in the inland arid area of Midwestern China," Agricultural Water Management, Elsevier, vol. 260(C).
    5. Yavuz, Duran & Seymen, Musa & Yavuz, Nurcan & Çoklar, Hacer & Ercan, Muhammet, 2021. "Effects of water stress applied at various phenological stages on yield, quality, and water use efficiency of melon," Agricultural Water Management, Elsevier, vol. 246(C).
    6. Wang, Chenxia & Gu, Feng & Chen, Jinliang & Yang, Hui & Jiang, Jingjing & Du, Taisheng & Zhang, Jianhua, 2015. "Assessing the response of yield and comprehensive fruit quality of tomato grown in greenhouse to deficit irrigation and nitrogen application strategies," Agricultural Water Management, Elsevier, vol. 161(C), pages 9-19.
    7. Jeet Chand & Guna Hewa & Ali Hassanli & Baden Myers, 2020. "Evaluation of Deficit Irrigation and Water Quality on Production and Water Productivity of Tomato in Greenhouse," Agriculture, MDPI, vol. 10(7), pages 1-18, July.
    8. Khozaei, Maryam & Kamgar Haghighi, Ali Akbar & Zand Parsa, Shahrokh & Sepaskhah, Ali Reza & Razzaghi, Fatemeh & Yousefabadi, Vali-allah & Emam, Yahya, 2020. "Evaluation of direct seeding and transplanting in sugar beet for water productivity, yield and quality under different irrigation regimes and planting densities," Agricultural Water Management, Elsevier, vol. 238(C).
    9. Rahil, M.H. & Qanadillo, A., 2015. "Effects of different irrigation regimes on yield and water use efficiency of cucumber crop," Agricultural Water Management, Elsevier, vol. 148(C), pages 10-15.
    10. Yang, Hui & Du, Taisheng & Qiu, Rangjian & Chen, Jinliang & Wang, Feng & Li, Yang & Wang, Chenxia & Gao, Lihong & Kang, Shaozhong, 2017. "Improved water use efficiency and fruit quality of greenhouse crops under regulated deficit irrigation in northwest China," Agricultural Water Management, Elsevier, vol. 179(C), pages 193-204.
    11. Kang, Jian & Hao, Xinmei & Zhou, Huiping & Ding, Risheng, 2021. "An integrated strategy for improving water use efficiency by understanding physiological mechanisms of crops responding to water deficit: Present and prospect," Agricultural Water Management, Elsevier, vol. 255(C).
    12. Zare Abyaneh, Hamid & Jovzi, Mehdi & Albaji, Mohammad, 2017. "Effect of regulated deficit irrigation, partial root drying and N-fertilizer levels on sugar beet crop (Beta vulgaris L.)," Agricultural Water Management, Elsevier, vol. 194(C), pages 13-23.
    13. Kiymaz, Sultan & Ertek, Ahmet, 2015. "Water use and yield of sugar beet (Beta vulgaris L.) under drip irrigation at different water regimes," Agricultural Water Management, Elsevier, vol. 158(C), pages 225-234.
    14. Yang, Xin & Bornø, Marie Louise & Wei, Zhenhua & Liu, Fulai, 2021. "Combined effect of partial root drying and elevated atmospheric CO2 on the physiology and fruit quality of two genotypes of tomato plants with contrasting endogenous ABA levels," Agricultural Water Management, Elsevier, vol. 254(C).
    15. Keikha, Mahdi & Darzi- Naftchali, Abdullah & Motevali, Ali & Valipour, Mohammad, 2023. "Effect of nitrogen management on the environmental and economic sustainability of wheat production in different climates," Agricultural Water Management, Elsevier, vol. 276(C).
    16. Du, Shaoqing & Kang, Shaozhong & Li, Fusheng & Du, Taisheng, 2017. "Water use efficiency is improved by alternate partial root-zone irrigation of apple in arid northwest China," Agricultural Water Management, Elsevier, vol. 179(C), pages 184-192.
    17. Segovia-Cardozo, Daniel Alberto & Rodríguez-Sinobas, Leonor & Zubelzu, Sergio, 2019. "Water use efficiency of corn among the irrigation districts across the Duero river basin (Spain): Estimation of local crop coefficients by satellite images," Agricultural Water Management, Elsevier, vol. 212(C), pages 241-251.
    18. Yamaç, Sevim Seda, 2021. "Artificial intelligence methods reliably predict crop evapotranspiration with different combinations of meteorological data for sugar beet in a semiarid area," Agricultural Water Management, Elsevier, vol. 254(C).
    19. Baoying Shan & Ping Guo & Shanshan Guo & Zhong Li, 2019. "A Price-Forecast-Based Irrigation Scheduling Optimization Model under the Response of Fruit Quality and Price to Water," Sustainability, MDPI, vol. 11(7), pages 1-21, April.
    20. Cai, Ximing & Yang, Yi-Chen E. & Ringler, Claudia & Zhao, Jianshi & You, Liangzhi, 2011. "Agricultural water productivity assessment for the Yellow River Basin," Agricultural Water Management, Elsevier, vol. 98(8), pages 1297-1306, May.

    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:jsusta:v:14:y:2022:i:19:p:12520-:d:930858. 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.