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Purpose <p>Within-row plant spacing, defined as the distance between adjacent plants in a crop row, is widely regarded as a key determinant of corn (<i>Zea mays</i> L.) grain yield. Uniformity in plant spacing, which is commonly associated with improved grain yield, is thought to be influenced by planter settings including planting speed and applied downforce. However, traditional descriptors of plant spacing—based on moments around the mean—can mask important differences in spatial irregularities, as rows with similar SD or CV may exhibit distinct patterns of non-uniformity. To address this limitation, we applied Lorenz curves and the Gini coefficient as a complementary approach to quantify spacing variability and its relationship to yield outcomes. The objectives of this study were to evaluate spacing inequality across planter settings, assess its relationship with corn yield at the plant level, and examine these associations using quantile regression.</p> Methods <p>Two field experiments were conducted in 2022 and 2023 in north-central Kansas, on no till Crete clay loam soil. A split-plot randomized complete block design was used to test combinations of planter downforce (445 to 1446 N) and planting speed (8.1 to 16.1 km h<sup>−1</sup>), with target spacings of 24 cm and 19.3 cm.</p> Results <p>Spacing uniformity differed across operational configurations, with low speed and moderate downforce yielding the most consistent within-row placement. Greater spatial variability was linked to lower average yield and increased inequality, while uniform spacing produced narrower and more equitable yield distributions. Yield responses to spacing variability were more pronounced in lower-yielding plants, revealing uneven sensitivity across the yield distribution.</p> Conclusion <p>Optimizing planting speed and downforce to improve spacing uniformity enhances grain yield while reducing yield inequality across the field. The Lorenz–Gini framework adds diagnostic detail for selecting planter configurations that promote consistent crop performance.</p>

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Assessing inequality in corn plant spacing and yield using Lorenz curves and the Gini coefficient

  • 期刊论文

  • 发表日期：

    2026年2月12日

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  • Bhaskar Aryal,
  • Ajay Sharda,
  • Andres Patrignani,
  • Trevor Hefley,
  • Ignacio Ciampitti

摘要

Purpose

Within-row plant spacing, defined as the distance between adjacent plants in a crop row, is widely regarded as a key determinant of corn (Zea mays L.) grain yield. Uniformity in plant spacing, which is commonly associated with improved grain yield, is thought to be influenced by planter settings including planting speed and applied downforce. However, traditional descriptors of plant spacing—based on moments around the mean—can mask important differences in spatial irregularities, as rows with similar SD or CV may exhibit distinct patterns of non-uniformity. To address this limitation, we applied Lorenz curves and the Gini coefficient as a complementary approach to quantify spacing variability and its relationship to yield outcomes. The objectives of this study were to evaluate spacing inequality across planter settings, assess its relationship with corn yield at the plant level, and examine these associations using quantile regression.

Methods

Two field experiments were conducted in 2022 and 2023 in north-central Kansas, on no till Crete clay loam soil. A split-plot randomized complete block design was used to test combinations of planter downforce (445 to 1446 N) and planting speed (8.1 to 16.1 km h−1), with target spacings of 24 cm and 19.3 cm.

Results

Spacing uniformity differed across operational configurations, with low speed and moderate downforce yielding the most consistent within-row placement. Greater spatial variability was linked to lower average yield and increased inequality, while uniform spacing produced narrower and more equitable yield distributions. Yield responses to spacing variability were more pronounced in lower-yielding plants, revealing uneven sensitivity across the yield distribution.

Conclusion

Optimizing planting speed and downforce to improve spacing uniformity enhances grain yield while reducing yield inequality across the field. The Lorenz–Gini framework adds diagnostic detail for selecting planter configurations that promote consistent crop performance.