TY - JOUR
T1 - Optimizing biochar application for enhanced cotton and sugar beet production in Xinjiang
T2 - a comprehensive study
AU - Wang, Shibin
AU - Wang, Chunli
AU - Xie, Lulu
AU - Li, Yi
AU - Siddique, Kadambot H.M.
AU - Qi, Xingyun
AU - Luo, Honghai
AU - Yang, Guang
AU - Hou, Zhenan
AU - Wang, Xiaofang
AU - Liang, Jiaping
AU - Xie, Xiangwen
AU - Liu, De Li
AU - Zhang, Fucang
N1 - Publisher Copyright:
© 2024 Society of Chemical Industry.
PY - 2024/3
Y1 - 2024/3
N2 - 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.
AB - 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.
KW - biochar management
KW - cotton
KW - evaluation
KW - production
KW - sugar beet
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U2 - 10.1002/jsfa.13487
DO - 10.1002/jsfa.13487
M3 - Article
C2 - 38523343
AN - SCOPUS:85189970954
SN - 0022-5142
SP - 6626
EP - 6639
JO - Journal of the Science of Food and Agriculture
JF - Journal of the Science of Food and Agriculture
ER -