Soil Acidification Reduces Flavonoids and Key Metabolites in Sugarcane Roots and Rhizosphere Leading to Yield Decline DOI
Ziqin Pang,

Lifang Mo,

Qiang Liu

et al.

Published: Jan. 1, 2024

Language: Английский

Effects of Long-Term Application of Nitrogen Fertilizer on Soil Acidification and Biological Properties in China: A Meta-Analysis DOI Creative Commons
L. Zhang, Zehang Zhao,

Bailing Jiang

et al.

Microorganisms, Journal Year: 2024, Volume and Issue: 12(8), P. 1683 - 1683

Published: Aug. 15, 2024

Soil acidification is a global environmental problem with significant impacts on agricultural production, protection, and ecosystem health. widespread in China, affecting crop yields, product quality, biodiversity. Since the 1980s, much work has been done acidic soils but it controversial whether excessive nitrogen fertilizer application can lead to soil mechanisms. To address above issues, we conducted meta-analysis of 115 published papers integrate analyze effects N biological properties from 1980 2024. We also quantified effect fertilization changes under different climatic conditions. The results showed that long-term fertilizers China 2024, pH decreased by an average 15.27%, activities urease, nitrate reductase, nitrite catalase, glutamate dehydrogenase, synthetase 9.82-22.37%. microbial community richness (Chao1 index) increased 6.53%, diversity (Shannon 15.42%. Among dominant microorganisms, relative abundance bacteria 9.67-29.38% gene expression

Language: Английский

Citations

7
Soil Acidification Reduces Flavonoids and Key Metabolites in Sugarcane Roots and Rhizosphere Leading to Yield Decline DOI Creative Commons
Ziqin Pang,

Lifang Mo,

Qiang Liu

et al.

Rhizosphere, Journal Year: 2025, Volume and Issue: unknown, P. 101028 - 101028

Published: Feb. 1, 2025

Language: Английский

Citations

0
Leveraging explainable AI to predict soil respiration sensitivity and its drivers for climate change mitigation DOI Creative Commons
Pierfrancesco Novielli, Michele Magarelli, Donato Romano

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 11, 2025

Global warming is one of the most pressing and critical problems facing world today. It mainly caused by increase in greenhouse gases atmosphere, such as carbon dioxide (CO2). Understanding how soils respond to rising temperatures for predicting release informing climate mitigation strategies. Q10, a measure soil microbial respiration, quantifies CO2 [Formula: see text] Celsius rise temperature, serving key indicator this sensitivity. However, Q10 across diverse types remains challenge, especially when considering complex interactions between biochemical, microbiome, environmental factors. In study, we applied explainable artificial intelligence (XAI) machine learning models predict respiration sensitivity (Q10) uncover factors driving process. Using SHAP (SHapley Additive exPlanations) values, identified glucose-induced proportion bacteria positively associated with influential predictors. Our achieved an accuracy text], precision AUC-ROC AUC-PRC ensuring robust reliable predictions. By leveraging t-SNE (t-distributed Stochastic Neighbor Embedding) clustering techniques, further segmented low into distinct subgroups, identifying higher probability transitioning high states. findings not only highlight potential XAI making model predictions transparent interpretable, but also provide actionable insights managing response change. This research bridges gap AI-driven modeling practical applications agriculture, offering new directions targeted management resilience

Language: Английский

Citations

0
Soil Acidification Reduces Flavonoids and Key Metabolites in Sugarcane Roots and Rhizosphere Leading to Yield Decline DOI
Ziqin Pang,

Lifang Mo,

Qiang Liu

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0