Collaborative management measures of subsurface drainage and bio-organic fertilizer application for coastal sunflower (Helianthus annuus L.) based on TOPSIS entropy weight method

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Abstract

Soil salinization has become a global resource and ecological issue, and sunflower planting has had a good improvement effect on saline-alkali land. The study explores the collaborative management measures of subsurface drainage and bio-organic fertilization with high-yield, high-quality, and environmentally friendly sunflowers through experiments. We designed three subsurface pipe spacings (10, 15, and 20 m) and six methods of combined application of organic fertilizer (organic fertilizer nitrogen 100%, organic fertilizer nitrogen 75% + inorganic fertilizer nitrogen 25%, organic fertilizer nitrogen and inorganic fertilizer nitrogen each 50%, organic fertilizer nitrogen 25% + inorganic fertilizer nitrogen 75%, 100% inorganic fertilizer nitrogen, and no fertilizer treatment). Nine evaluation indexes were selected for the four aspects of yield increase, quality improvement, soil improvement, and emission reduction, and an index system was constructed. In the evaluation model, the TOPSIS entropy weight method was calculated to compare and select the most suitable growth method of subsurface drainage and bio-organic fertilizer application for sunflower growth in saline-alkali land. The results showed that the best treatment was 75% organic fertilizer nitrogen + 25% inorganic fertilizer nitrogen, and the best spacing for the subsurface drainage was 10 m. Under this treatment, the relative application progress reached 0.574, and the yield, oleic acid content, soil organic matter content, soil salt reduction efficiency, and N2O emissions were 2.93 t/ha, 21.73%, 2.21%, 37.62%, and 9.86 kg/ha, respectively.

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Zhu, Q., Chen, J., Rui, H., Hamoud, Y. A., AlGarawi, A. M., Okla, M. K., … Shaghaleh, H. (2025). Collaborative management measures of subsurface drainage and bio-organic fertilizer application for coastal sunflower (Helianthus annuus L.) based on TOPSIS entropy weight method. PLoS ONE, 20(4 April). https://doi.org/10.1371/journal.pone.0318571

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