College of Agriculture and Forestry Science, Linyi University, Linyi, 276000, P. R. China.
Biogeochemistry Research Group, Department of Environmental and Biological Sciences, University of Eastern Finland, PO Box 1627, Kuopio, Finland.
Sci Rep. 2020 Jun 16;10(1):9699. doi: 10.1038/s41598-020-66613-6.
A major challenge in maize (Zea mays) production is to achieve high grain yield (yield hereafter) by improving resource use efficiency. Using a dataset synthesized from 83 peer-reviewed articles, this study mainly investigated the effects of water and/or nitrogen (N) input on maize yield, water productivity (WP), and N use efficiency (NUE); and evaluated the effects caused by planting density, environmental (temperature, soil texture), and managerial factors (water and/or N input). The input of water increased maize yield, WP, and NUE only when the input was less than 314, 709, and 311 mm, respectively; input of N increased maize yield, WP, and NUE until input was greater than 250, 128, and 196 kg ha, respectively. Additionally, results of the mixed-effects model and random forest analysis suggested that mean annual temperature (MAT) was the most critical factor for narrowing gaps (between the actual and attainable variable, which was indicated as response ratio of the treatment relative to the control) of yield (RR), WP (RR), and NUE (RR), respectively. Specifically, RR, RR, or RR were negatively correlated to MAT when MAT was higher than 15 °C. Additionally, the structural equation model showed that water input and RR with the higher coefficient were more important than N input and RR in improving RR. These findings provide new insights into the causes and limitations of global maize production and offer some guidances for water and/or N managements.
在玉米（Zea mays）生产中，一个主要的挑战是通过提高资源利用效率来实现高谷物产量（以下简称产量）。本研究主要利用 83 篇同行评议文章综合数据集，研究了水和/或氮（N）投入对玉米产量、水分生产率（WP）和 N 利用效率（NUE）的影响，并评估了种植密度、环境（温度、土壤质地）和管理因素（水和/或 N 投入）的影响。只有当水的投入量小于 314、709 和 311 mm 时，水的投入才会增加玉米的产量、WP 和 NUE；当 N 的投入量大于 250、128 和 196 kg/ha 时，N 的投入才会增加玉米的产量、WP 和 NUE。此外，混合效应模型和随机森林分析的结果表明，年平均温度（MAT）是缩小产量（RR）、WP（RR）和 NUE（RR）差距的最关键因素。具体来说，当 MAT 高于 15°C 时，RR、RR 或 RR 与 MAT 呈负相关。此外，结构方程模型表明，与 N 投入和 RR 相比，水投入和 RR 的系数更高，在提高 RR 方面更为重要。这些发现为全球玉米生产的原因和限制提供了新的见解，并为水和/或 N 管理提供了一些指导。
