Pulse Brain · Growing Health Evidence Index
Tier 1 — Meta-analysis / systematic reviewPeer-reviewed

Global meta-analysis and machine learning show that deep fertilization produces more grain with lower environmental costs, especially in lower latitude areas

Peng Wu, Hua Huang, Nanhai Zhang, Ji Liu, Tie Cai, Zhikuan Jia, Ji Chen, Enke Liu, Chuangyun Wang, Zhiqiang Gao, Peng Zhang

Field Crops Research · 2025

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Summary

This global meta-analysis integrates published evidence on deep fertiliser placement to evaluate its agronomic and environmental trade-offs in grain production. The findings indicate that deep placement enhances grain yield whilst reducing nutrient losses, with particularly pronounced benefits at lower latitudes, suggesting that optimal fertilisation strategy varies by climatic zone and local soil conditions. The work contributes to context-specific recommendations for balancing productivity gains with environmental stewardship in cereal systems.

UK applicability

The meta-analysis includes temperate and higher-latitude systems, though deep fertilisation benefits appear strongest in warmer climates. UK farmers operating at higher latitudes may observe more modest environmental and yield gains from deep placement than those in lower-latitude regions; applicability depends on local soil properties, weather patterns, and nitrogen dynamics in temperate soils.

Key measures

Grain yield (as affected by deep placement); environmental losses (nitrogen, phosphorus leaching and volatilisation); latitude and climate variables as moderators of response; machine learning model performance

Outcomes reported

The study synthesised evidence on grain yield responses and environmental losses (nutrient runoff, ammonia volatilisation) associated with deep versus surface fertiliser placement across diverse climatic and agronomic contexts. Machine learning models were employed to identify geographic and climatic predictors of deep fertilisation effectiveness.

Theme
Farming systems, soils & land use
Subject
Soil fertility & nutrient management
Study type
Meta-analysis
Study design
Meta-analysis
Source type
Peer-reviewed study
Status
Published
Geography
Global
System type
Arable cereals
DOI
10.1016/j.fcr.2025.110267
Catalogue ID
SNmoht1ytf-vjxq4p

Topic tags

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