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 .
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.
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http://dx.doi.org/10.1002/aps3.11346 | DOI Listing |
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State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
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CNRS, Syensqo, LOF, UMR 5258, Université de Bordeaux, 178 Av. Schweitzer, 33600 Pessac, France.
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Department of Life Sciences, Yeungnam University, Gyeongsan, Korea.
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View Article and Find Full Text PDFEcology
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Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, California, USA.
The dataset contains leaf venation architecture and functional traits for a phylogenetically diverse set of 122 plant species (including ferns, basal angiosperms, monocots, basal eudicots, asterids, and rosids) collected from the living collections of the University of California Botanical Garden at Berkeley (37.87° N, 122.23° W; CA, USA) from February to September 2021.
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