A global synthesis of genotypic variation in crop greenhouse gas emissions under variable nitrogen fertilisation

Abstract

Targeted crop selection offers a promising potential pathway to reduce greenhouse gas (GHG) emissions from global croplands. Yet, the influence of crop genotypes on GHG emissions remains poorly studied, limiting our ability to understand its global potential. To address this challenge, we conducted a global synthesis of GHG and crop yield data from 42 field experiments across 180 genotypes of major cereal (predominantly rice) and oilseed crops (soybeans and canola) and nitrogen (N) fertilisation rates (40kg ha-1 to 390kg ha-1) (n =390). To test the influence of genotype, we removed measurements from genotypes with fewer than three independent replicates (n = 97) and apply linear mixed-effects models to control for study and latitude effects. Across a range of environmental and experimental conditions, we analysed the influence of N application rate on crop nitrous oxide (N2O) and methane (CH4) emissions, alongside yield. We found significant differences in N2O-N cumulative fluxes between crop types and mean annual precipitation ranges. When expressed per unit of crop yield, N2O-N and CH4-C cumulative fluxes revealed a significant difference between N application rate groups (a = < 50, b = 50-100, c = 100-150, d = 150-200, e = 200-250, f = 250-300, g = > 300), with a positive yield response to N fertilisation. While yield-scaled N2O-N cumulative fluxes declined with N application rate, yield-scaled CH4-C cumulative fluxes increased; however, all CH4 measurements were derived from rice systems. Regression relationships between cumulative N2O, CH4, crop yield and N application rate were consistent with previous global syntheses, showing that N2O and CH4 emissions increased exponentially with N application, while crop yield exhibited a quadratic response. Our results indicate that N application rate was the primary driver of N2O emissions and crop yield, while genotypic differences significantly influenced CH4 emissions. These findings underscore the importance of integrating genotype selection with nitrogen management to improve GHG mitigation while optimising crop productivity.