Straw-derived biochar optimizes water consumption, shoot and root characteristics to improve water productivity of maize under reduced nitrogen

Agricultural Water Management, Journal Year: 2024, Volume and Issue: 294, P. 108722 - 108722

Published: Feb. 15, 2024

Optimizing water and nitrogen (N) utilization to enhance crop yields under resource constraints is crucial. Straw its biochar, combined with N fertilizer, are commonly used improve soil carbon storage growth. However, the effects of straw fertilizer management on consumption, root shoot characteristics, uptake, maize productivity remain unclear. To address this knowledge gap, a three-year (2019–2021) field experiment was conducted in Northwest China. We compared two incorporation methods [straw (SI) straw-derived biochar (BI)] removal (NI) at four application rates [0 (N0), 225 (N225), 300 (N300), 375 kg ha–1 (N375)]. Results indicated that NI, both SI BI significantly increased grain yield (GY), (WP) (SI < BI; P 0.05). The maximum GYs were achieved SIN300 BIN225, respectively. Notably, SIN300, BIN225 enhanced GY by 10.8% 5.8% improved WP 19.2% 9.9% (P This improvement mainly attributed consumption after tasseling transpiration (T) evapotranspiration (ET). Furthermore, resulted distribution shallow layers (0–0.3 m). Under roots exhibited longer, thinner deeper profile, minimizing redundancy enhancing efficiency absorption during reproductive stage maize. In contrast, shorter, thicker, shallower roots, leading reduced shoot-root ratio 12.2% Based normalization fitting curves, (240 ha–1) 24.5%, achieving 98.7% for drip-irrigated (16.98 Mg kg–1). Overall, these findings provide novel strategy sustainable arid irrigation agriculture similar ecosystems.

Language: Английский

Predictive Modeling Study on the Critical Nitrogen Concentration and Nitrogen Accumulation in Cut Chrysanthemum Based on the Cumulative Photo-Thermal Effect

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 10, 2024

Background and aims Critical nitrogen (N) concentration (N_c) critical accumulation (N_a) are essential for N status diagnosis precise fertilization in crops. However, efficient prediction models N_c N_a cut Chrysanthemum remains scarce, limiting precision management. Methods Five experiments with varying gradients were conducted from May 2021 to August 2022 using the ‘Nannong Xiaojinxing’ cultivar. We developed validated dry matter various growth developmental driver variables, established as model driving variable, created optimal variable identified predictions. Results Among Chrysanthemum, incorporating cumulative photo-thermal effect (PTE) demonstrated superior accuracy stability. variable. When above-ground was 1 g·plant^{− 1}, 4.5295% 45.30 mg·plant^{− respectively. At flower picking stage, reached 236.50 1}. The PTE-driven high accuracy, R² at 0.9687 1.0019, RMSEs 0.2105% 17.47 n-RMSEs 7.31% 12.72%, Conclusions These can dynamically predict based on light temperature factors, providing a scientific basis diagnostics fertilizer management chrysanthemum. Moreover, methodology herein could be extrapolated other crops, contributing sustainable agriculture mitigating excessive application.

Language: Английский