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

Author

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
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