Determining leaf stomatal properties in citrus trees utilizing machine vision and artificial intelligence
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Determining leaf stomatal properties in citrus trees utilizing machine vision and artificial intelligence Lucas Costa1 · Leigh Archer2 · Yiannis Ampatzidis1 · Larissa Casteluci3 · Glauco A. P. Caurin3 · Ute Albrecht2 Accepted: 7 November 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Identifying and quantifying the number and size of stomata on leaf surfaces is useful for a wide range of plant ecophysiological studies, specifically those related to water-use efficiency of different plant species or agricultural crops. The time-consuming nature of manually counting and measuring stomata have limited the utility of manual methods for large-scale precision agriculture applications. A deep learning segmentation network was developed to automate the analysis of stomatal density and size and to distinguish between open and closed stomata using citrus trees grafted on different rootstocks as a model system. A novel method was developed utilizing the Mask-RCNN algorithm, which allows identification, quantification, and characterization of stomata from leaf epidermal peel microscopic images with an accuracy of up to 99%. Moreover, this method permits the differentiation of open and closed stomata with 98% precision and measurement of individual stomata size. In the citrus model system, significant differences in the size and density of stomata and diurnal regulation patterns were detected that were associated with the rootstock cultivar on which the trees were grafted. Nearly 9000 individual stomata were analyzed, which would have been impractical using manual methods. The novel automated method presented here is not only accurate, but also rapid and low-cost, and can be applied to a variety of crop and non-crop plant species. Keywords Machine learning · Deep learning · CNN · Stomata · Precision agriculture
Lucas Costa and Leigh Archer have contributed equally. * Yiannis Ampatzidis [email protected] * Ute Albrecht [email protected] 1
Agricultural and Biological Engineering Department, Southwest Florida Research and Education Center, University of Florida, IFAS, 2685 SR 29 North, Immokalee, FL 34142, USA
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Horticultural Sciences Department, Southwest Florida Research and Education Center, University of Florida, IFAS, 2685 SR 29 North, Immokalee, FL 34142, USA
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Aeronautical Engineering Department ‑ SAA, Sao Carlos School of Engineering‑EESC, University of São Paulo-USP, Avenida João Dagnone 1100, Sao Carlos, SP 13563‑120, Brazil
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Precision Agriculture
Introduction Stomata are pores found on the lower (abaxial) surface of leaves. Under normal conditions stomata open during the day in the presence of light to allow the exchange of carbon dioxide and water between the leaf and the atmosphere to drive photosynthesis. Stomata close at night and under unfavorable conditions, such as drought, when preserving cellular water is more critical to survival than photosynthesis. Stomatal regulation determines the photosynthetic capacity (Tanaka et al. 2013) and
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