大豆产量与有机质呈正相关,但播种日期影响更大

Lindsay Chamberlain Malone, Matthew D. Ruark, Rachel Atwell Vann, Maninder P. Singh, W. Jeremy Ross, Shawn P. Conley
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摘要

建立土壤健康指标与作物表现之间的联系将有助于确保向农民推荐的测试与相关结果相关联。本研究评估了大豆 [Glycine max (L.) Merr] 产量与三种常见土壤健康指标的关系:土壤有机质 (SOM)、高锰酸盐可氧化碳 (POXC) 和高压灭菌柠檬酸提取氮 (ACE-N)。这些测试与其他因素(土壤测试磷、土壤测试钾 [STK]、映射粘土、种植日期、夏季降水量和地点)一起进行评估。在 2019 年至 2021 年期间,从阿肯色州、密歇根州、北卡罗来纳州和威斯康星州的 457 块生产者管理的田地中采集了土壤样本。种植日期和产量由生产者报告,而绘图粘土和降雨量则通过公开数据确定。简单线性回归用于评估土壤健康指标与产量之间的关系:SOM 和 POXC 的自然对数与大豆产量呈正相关(R2 = 0.07,p < 0.001;R2 = 0.03,p < 0.001),而 ACE-N 与此无关(p = 0.872)。多元线性回归用于进一步检验 SOM 和 POXC 与产量的关系,同时考虑到其他影响大豆产量的因素。模型解释了 27% 的产量变化,其中重要的因素包括 SOM 或 POXC、大豆播种日期、STK 和绘图粘土。根据标准化系数,播种日期是对产量影响最大的因素。总体而言,我们的研究结果表明,产量的提高与较高的 SOM 有关,但早播等管理决策对实现高产至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Soybean yield is positively linked to organic matter, but planting date remains more influential

Establishing connections between soil health indicators and crop performance will help ensure that tests recommended to farmers relate to outcomes of interest. This study assessed the relationship of soybean [Glycine max (L.) Merr] yield with three common soil health indicators: soil organic matter (SOM), permanganate oxidizable carbon (POXC), and autoclaved citrate extractable nitrogen (ACE-N). These tests were assessed alongside other factors (soil test phosphorus, soil test potassium [STK], mapped clay, planting date, summer precipitation, and location). Soil samples were collected from 457 producer-managed fields between 2019 and 2021 in Arkansas, Michigan, North Carolina, and Wisconsin. Planting date and yield were reported by producers, while mapped clay and rainfall were determined using publicly available data. Simple linear regression was used to assess the relationship between soil health indicators and yield: the natural log of SOM and POXC were positively associated with soybean yield (R2 = 0.07, p < 0.001; R2 = 0.03, p < 0.001), while ACE-N was not (p = 0.872). Multiple linear regression was used to further test the relationship of SOM and POXC with yield, while accounting for other factors that contribute to soybean yield. Models explained 27% of variation in yield, with significant factors including SOM or POXC, soybean planting date, STK, and mapped clay. Based on standardized coefficients, planting date was the most influential factor associated with yield. Broadly, our results indicate that improvements in yield are linked to higher SOM, but management decisions like planting early are critical for achieving high yields.

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