Variation within laminae: Semi-automated methods for quantifying leaf venation using phenoVein.

Abstract

Premise Physiological processes may vary within leaf laminae; however, the accompanying heterogeneity in leaf venation is rarely investigated because its quantification can be time consuming. Here we introduce accelerated protocols using existing software to increase sample throughput and ask whether laminae venation varies among three crop types and four subspecies of Brassica rapa . Methods FAA (formaldehyde, glacial acetic acid, and ethanol)-fixed samples were stored in ethanol. Without performing any additional clearing or staining, we tested two methods of image acquisition at three locations along the proximal-distal axis of the laminae and estimated the patterns of venation using the program phenoVein. We developed and made available an R script to handle the phenoVein output and then analyzed our data using linear mixed-effects models. Results Beyond fixation and storage, staining and clearing are not necessary to estimate leaf venation using phenoVein if the images are acquired using a stereomicroscope. All estimates of venation required some manual adjustment. We found a significant effect of location within the laminae for all aspects of venation. Discussion By removing the clearing and staining steps and utilizing the semi-automated program phenoVein, we quickly and cheaply acquired leaf venation data. Venation may be an important target for crop breeding efforts, particularly if intralaminar variation correlates with variation in physiological processes, which remains an open question.

Plant phenotyping relevance

葉脈という植物形態形質の画像取得・半自動定量法を開発・評価し、解析用Rスクリプトも提供しており、フェノタイピング手法が研究の中心である。

Code and data availability

The authors explicitly state that their custom R script for processing phenoVein output and all analyzed venation data are freely available on their public GitHub repository, making this a paper-specific, public, actionable asset.