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Needle/electrode insertion mechanism for measuring plant electrical signals

Springer Science and Business Media LLC · 14 May 2024 · 10.21203/rs.3.rs-4351307/v1

Abstract

Abstract Plants generate electrical signals in response to mild and severe environmental stimuli to transmit physiological information and ultimately trigger defensive responses during stressful events. It has been proposed that detecting and characterizing such signals could allow researchers to mimic specific electrical stimuli and provoke desirable responses in crops. Nevertheless, manually inserting electrodes in plant tissues leads to irregular data records due to a lack of uniformity across insertion events. For this reason, we manufactured a prototype of an electrode/needle insertion mechanism built in aluminum and acrylic and used it to measure electrical signals caused by drought in Capsicum annum plants. As results the mechanism had a more consistent performance in the characteristics of the insertion as depth, alignment between electrodes and with plant stem. As well, the mechanism was used for obtaining electrical signals (ES) related to drought, which, through a convolutional neural network (CNN) could be differentiated from control ES´s with an 84.91% recognition rate. It was concluded that the mechanism reduced variations in the characteristics of the electrode insertion and that it could be implemented for ES´s analysis.

Plant phenotyping relevance

植物への電極挿入を標準化する機構を開発・評価し、乾燥ストレスに伴う植物電気シグナルの取得と分類に用いており、表現型取得法が中心的です。

abstractwe manufactured a prototype of an electrode/needle insertion mechanism built in aluminum and acrylic and used it to measure electrical signals caused by drought in Capsicum annum plants.
abstractthe mechanism reduced variations in the characteristics of the electrode insertion and that it could be implemented for ES´s analysis.

Code and data availability

The supplied preprint blocks describe plant electrical signal measurements (Capsicum annuum, drought vs control) and a CNN classifier, but contain no data availability statement, no public dataset deposit, no author code/model release, and no repository or identifier. All URLs in the text are citations to prior work, i

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