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Source:sink imbalance detected with leaf‐ and canopy‐level spectroscopy in a field‐grown crop

Plant, Cell & Environment · 21 Apr 2021 · 10.1111/pce.14056

Abstract

Abstract The finely tuned balance between sources and sinks determines plant resource partitioning and regulates growth and development. Understanding and measuring metabolic indicators of source or sink limitation forms a vital part of global efforts to increase crop yield for future food security. We measured metabolic profiles of Cucurbita pepo (zucchini) grown in the field under carbon sink limitation and control conditions. We demonstrate that these profiles can be measured non‐destructively using hyperspectral reflectance at both leaf and canopy scales. Total non‐structural carbohydrates (TNC) increased 82% in sink‐limited plants; leaf mass per unit area (LMA) increased 38% and free amino acids increased 22%. Partial least‐squares regression (PLSR) models link these measured functional traits with reflectance data, enabling high‐throughput estimation of traits comprising the sink limitation response. Leaf‐ and canopy‐scale models for TNC had R 2 values of 0.93 and 0.64 and %RMSE of 13 and 38%, respectively. For LMA, R 2 values were 0.91 and 0.60 and %RMSE 7 and 14%; for free amino acids, R 2 was 0.53 and 0.21 with %RMSE 20 and 26%. Remote sensing can enable accurate, rapid detection of sink limitation in the field at the leaf and canopy scale, greatly expanding our ability to understand and measure metabolic responses to stress.

Plant phenotyping relevance

葉・キャノピーのハイパースペクトル反射からTNC、LMA、遊離アミノ酸などの植物機能形質をPLSRで非破壊・高スループット推定する方法が中心であり、技術性能も定量評価している。

abstractWe demonstrate that these profiles can be measured non‐destructively using hyperspectral reflectance at both leaf and canopy scales.
abstractPartial least‐squares regression (PLSR) models link these measured functional traits with reflectance data, enabling high‐throughput estimation of traits comprising the sink limitation response.
abstractLeaf‐ and canopy‐scale models for TNC had R 2 values of 0.93 and 0.64 and %RMSE of 13 and 38%, respectively.

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