Optimizing biochar application for enhanced cotton and sugar beet production in Xinjiang: a comprehensive study

Shibin Wang, Chunli Wang, Lulu Xie, Yi Li, Kadambot H.M. Siddique, Xingyun Qi, Honghai Luo, Guang Yang, Zhenan Hou, Xiaofang Wang, Jiaping Liang, Xiangwen Xie, De Li Liu, Fucang Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

BACKGROUND: Optimizing biochar application is vital for enhancing crop production and ensuring sustainable agricultural production. A 3-year field experiment was established to explore the effects of varying the biochar application rate (BAR) on crop growth, quality, productivity and yields. BAR was set at 0, 10, 50 and 100 t ha−1 in 2018; 0, 10, 25, 50 and 100 t ha−1 in 2019; and 0, 10, 25 and 30 t ha−1 in 2020. Crop quality and growth status and production were evaluated using the dynamic technique for order preference by similarity to ideal solution with the entropy weighted method (DTOPSIS-EW), principal component analysis (PCA), membership function analysis (MFA), gray relation analysis (GRA) and the fuzzy Borda combination evaluation method. RESULTS: Low-dose BAR (≤ 25 t ha−1 for cotton; ≤ 50 t ha−1 for sugar beet) effectively increased biomass, plant height, leaf area index (LAI), water and fertility (N, P and K) productivities, and yield. Biochar application increased the salt absorption and sugar content in sugar beet, with the most notable increases being 116.45% and 20.35%, respectively. Conversely, BAR had no significant effect on cotton fiber quality. The GRA method was the most appropriate for assessing crop growth and quality. The most indicative parameters for reflecting cotton and sugarbeet growth and quality status were biomass and LAI. The 10 t ha−1 BAR consistently produced the highest scores and was the most economically viable option, as evaluated by DTOPSIS-EW. CONCLUSION: The optimal biochar application strategy for improving cotton and sugar beet cultivation in Xinjiang, China, is 10 t ha−1 biochar applied continuously.

Original languageEnglish
Pages (from-to)6626-6639
Number of pages14
JournalJournal of the Science of Food and Agriculture
DOIs
Publication statusE-pub ahead of print - Mar 2024

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