Impact of Sowing Space and Depth on Canopy Architecture and Vertical Leaf Traits in Dryland Wheat

Abstract

Sowing space and depth critically influence wheat canopy architecture, yet their layer-specific effects remain poorly understood. This two-year field study evaluated the effects of three sowing spaces (1.5, 3.0, 4.5 cm) and three sowing depths (2, 3, 6 cm) on canopy projection area, leaf inclination angle, leaf area distribution, and leaf area index (LAI) of dryland wheat (Triticum aestivum ‘Ningmai 13’) in Luhe, Nanjing, China, using image-based phenotyping with manual validation. Narrow spacing (1.5 cm) with intermediate depth (3 cm) produced the largest canopy projection area (0.239–0.245 m2) and an increase in leaf erectness in the middle canopy layer (+23% above average). The highest LAI values (4.23–4.28 m2 m−2) were achieved with narrow spacing (A1B1, A1B2), demonstrating that dense canopies can be established under dryland conditions. Grain yield (g/plant) was measured as a supporting agronomic indicator; the highest yield per plant (14.36 g/plant) was observed in A3B1. Image-based measurements showed excellent agreement with manual methods (R2 > 0.97 for all traits), validating the phenotyping pipeline. These findings contribute to a deeper understanding of how sowing parameters shape wheat canopies in dryland systems.

Plant phenotyping relevance

画像ベースの表現型測定パイプラインを用いてキャノピー形態・葉形質を抽出し、手動測定との一致性も検証しており、フェノタイピング手法が中心的です。

Code and data availability

The supplied blocks describe a MATLAB image-based phenotyping pipeline and R statistical analysis for wheat canopy traits, but contain no data availability statement, no public deposit of phenotype datasets, images, code, or models, and no author-provided public URLs. The only URLs present are the article DOI and a PLo

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