Estimation of Dry Matter and N Nutrient Status of Choy Sum by Analyzing Canopy Images and Plant Height Information

Abstract

The estimation accuracy of plant dry matter by spectra- or remote sensing-based methods tends to decline when canopy coverage approaches closure; this is known as the saturation problem. This study aimed to enhance the estimation accuracy of plant dry matter and subsequently use the critical nitrogen dilution curve (CNDC) to diagnose N in Choy Sum by analyzing the combined information of canopy imaging and plant height. A three-year experiment with different N levels (0, 25, 50, 100, 150, and 200 kg∙ha−1) was conducted on Choy Sum. Variables of canopy coverage (CC) and plant height were used to build the dry matter and N estimation model. The results showed that the yields of N0 and N25 were significantly lower than those of high-N treatments (N50, N100, N150, and N200) for all three years. The variables of CC × Height had a significant linear relationship with dry matter, with R2 values above 0.87. The good performance of the CC × Height-based model implied that the saturation problem of dry matter prediction was well-addressed. By contrast, the relationship between dry matter and CC was best fitted by an exponential function. CNDC models built based on CC × Height information could satisfactorily differentiate groups of N deficiency and N abundance treatments, implying their feasibility in diagnosing N status. N application rates of 50–100 kgN/ha are recommended as optimal for a good yield of Choy Sum production in the study region.

Plant phenotyping relevance

キャノピー画像と草丈を統合して乾物量・窒素状態を推定する手法を構築し、飽和問題への対処と精度評価を行っており、表現型取得・推定が研究の中心である。

Code and data availability

The paper describes canopy image collection and a Matlab image-analysis program for Choy Sum phenotyping, but no public dataset, image repository, or code deposit is provided. The Data Availability Statement explicitly says 'Not applicable', and no author URL or repository for data or code appears anywhere in the text.

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