Evaluation of Image-Based Phenotyping Methods for Measuring Water Yam ( Dioscorea alata L.) Growth and Nitrogen Nutritional Status under Greenhouse and Field Conditions

Abstract

Management practices must be developed to improve yam production sustainability. Image-based phenotyping techniques could help developing such practices based on non-destructive analyses of important plant traits. Our objective was to determine the potential of image-based phenotyping methods to assess traits relevant for tuber yield formation in yam grown in glasshouse and field. We took plant and leaf pictures with consumer cameras. We used the numbers of image pixels to derive the shoot biomass and the total leaf surface and calculated the ‘triangular greenness index’ (TGI) which is an indicator of the plant nitrogen (N) nutritional status. Under glasshouse conditions, the number of pixels obtained from nadir view (image taken top down) was positively correlated to the shoot biomass, and the total leaf surface, while the TGI was negatively correlated to the N content of diagnostic leaves. Under field conditions, pictures taken from the nadir view showed an increase in soil surface cover and a decrease in TGI with time. TGI was negatively correlated to SPAD measured on specific leaves but was not correlated to the N content of these leaves. In conclusion, these phenotyping techniques deliver relevant results but need to be further developed and validated for application in yam.

Plant phenotyping relevance

画像ベース表現型解析によりヤムのバイオマス、葉面積、窒素栄養状態を推定し、温室・圃場で相関評価と妥当性検証を行っており、表現型取得法が中心である。

Code and data availability

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