Search

Optimizing the canopy nitrogen (N) distribution by matching the available light resources to construct a light-N matching canopy structure of summer maize is important to improve yield and narrow the yield gap (YG). A field experiment with four integrated agronomic management practice systems [a control treatment (T1), an improved management system (T2), a super high-yield management system (T3), and an optimized management system (T4)] was conducted at Da Wenkou Town, Tai'an, China, from June to October in -2018–2020 to study the canopy light and N distribution and photosynthetic N use efficiency of summer maize. The results showed that optimized integrated agronomic management practices could coordinate canopy light and N distributions to increase the yield, thus narrowing the YG between T1 and yield potential by 1.9–5.2 Mg ha-1. In addition, the T4 treatment intercepted more radiation by adjusting the leaf area. Furthermore, the leaf N content of T4 in the middle canopy was significantly increased. The coordination of canopy light and N distributions of T4 was increased significantly, which was conducive to maximizing the use of N and solar radiation and increasing photosynthetic N use efficiency significantly by 9.4–41.4%, compared to that of T1. As a result, the yield of T4 was increased by 37.0% compared to that of T1. And T4 narrowed the YG by 3.4 Mg ha-1. Therefore, the T4 was the best choice for achieving a high-yield and high-efficiency production of summer maize in this study. • Optimized agronomic management improved leaf nitrogen vertical distribution. • Optimized agronomic management increased canopy light interception. • Optimized agronomic management narrowed yield gap by regulating canopy structure. [ABSTRACT FROM AUTHOR]

In the North China Plain (NCP), the deployment of sub-optimal crop management methods has resulted in low maize grain yields and significant environmental costs arising from a low N partial factor productivity (NPFP) and a rampant greenhouse gas emission intensity (GHG i). We hypothesize that in-situ analysis of the grain yield, NPFP and GHG i at local farms might contribute to improving the crop yield, as well as the environmental sustainability of maize production systems. In this study, we investigated the maize production systems deployed at 1574 local farms in the NCP, and quantified the total yield gap (defined as the difference between the yield potential as simulated by the DSSAT-CERES-Maize model and the actual yield achieved by farmers) and the exploitable yield gap (defined as the difference between the attainable yield as calculated by using the Boundary Line Function (BLF) analysis and the average actual yield achieved by farmers). By combining the results from crop modelling, farmer survey data, and on-farm trials, we were able to identify the dominant factors driving the variability in summer maize yield, NPFP, and GHG i. The results revealed that the average grain yield for summer maize in the NCP was 8.3 t ha−1, and that the total and exploitable yield gaps were 4.9 t ha−1 and 3.0 t ha−1, respectively. The average NPFP was 41 kg kg−1, which amounts to 54% of the attainable NPFP. The average GHG i was 463 kg CO 2 eq t−1 grain, which constitutes an increase of 119% over the attainable GHG i. The main factors driving yield include the harvest date and the planting density, and the main factors driving NPFP and GHG i include the N, P and K fertilization rate, where it should be noted that these factors exhibit regional differences. After testing our optimized integrated agronomic management measures in the field experiments, we could confirm that it is possible to narrow the yield gap by 2.7 t ha−1, increase NPFP by 38%, and reduce GHG i by 28%. Obviously, optimizing integrated agronomic management has a great potential for narrowing the yield gap and improving the sustainability of agricultural production. • The total and exploitable yield gaps of maize in the NCP are 4.9 and 3.0 t ha−1. • The main factors driving yield include the harvest date and the planting density. • The N, P and K fertilization rate driving the variability in NPFP and GHG i. • Agronomic optimizations can improve the yield and sustainability of farms in the NCP. [ABSTRACT FROM AUTHOR]