Evaluation of Vine’s Annual Carbon Stocks by Means of LiDAR-Based 3D Reconstruction

Abstract

Climate change significantly impacts viticulture by harming plant and fruit growth, resulting in lower quality and storage issues. Therefore, there is growing scientific interest in the carbon fluxes of vineyard management activities, including efforts to measure carbon capture and storage in annual biomass. Precision Viticulture and Machine Vision techniques can help assess variations in vines’ biomass, which relate to the vines’ carbon balance. The present study examined the feasibility of a light detection and ranging (LiDAR) for vines’ (Vitis vinifera L. cv. Riesling) annual biomass reconstruction and its role in the annual carbon cycle. The leaves dry weight showed a high correlation coefficient of R² = 0.87 with the LiDAR-based leaf area estimation. Thus, making the proposed sensing system reliable for biomass elemental carbon assessment. Nevertheless, no significant correlation was found for the monitoring of leaf area/fruit ratio. The proposed study showcases the potential and the limits of LiDAR-based vine biomass assessment.

Plant phenotyping relevance

LiDARによるブドウ樹の葉面積・年間バイオマス再構成を評価し、乾物重との相関でセンシング手法の信頼性を検証しているため、植物形質取得法が中心である。

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