OpenPheno: an open-access, user-friendly, and smartphone-based software platform for instant plant phenotyping.

IF 4.4 2区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Plant Methods Pub Date : 2025-06-02 DOI:10.1186/s13007-025-01395-4

Tianqi Hu, Peng Shen, Yongshuai Zhang, Jiafei Zhang, Xin Li, Chuanzhen Xia, Ping Liu, Hao Lu, Tingting Wu, Zhiguo Han

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引用次数: 0

Abstract

Background: Plant phenotyping has become increasingly important for advancing plant science, agriculture, and biotechnology. Classic manual methods are labor-intensive and time-consuming, while existing computational tools often require advanced coding skills, high-performance hardware, or PC-based environments, making them inaccessible to non-experts, to resource-constrained users, and to field technicians.

Results: To respond to these challenges, we introduce OpenPheno, an open-access, user-friendly, and smartphone-based platform encapsulated within a WeChat Mini-Program for instant plant phenotyping. The platform is designed for ease of use, enabling users to phenotype plant traits quickly and efficiently with only a smartphone at hand. We currently instantiate the use of the platform with tools such as SeedPheno, WheatHeadPheno, LeafAnglePheno, SpikeletPheno, CanopyPheno, TomatoPheno, and CornPheno; each offering specific functionalities such as seed size and count analysis, wheat head detection, leaf angle measurement, spikelet counting, canopy structure analysis, and tomato fruit measurement. In particular, OpenPheno allows developers to contribute new algorithmic tools, further expanding its capabilities to continuously facilitate the plant phenotyping community.

Conclusions: By leveraging cloud computing and a widely accessible interface, OpenPheno democratizes plant phenotyping, making advanced tools available to a broader audience, including plant scientists, breeders, and even amateurs. It can function as a role in AI-driven breeding by providing the necessary data for genotype-phenotype analysis, thereby accelerating breeding programs. Its integration with smartphones also positions OpenPheno as a powerful tool in the growing field of mobile-based agricultural technologies, paving the way for more efficient, scalable, and accessible agricultural research and breeding.

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OpenPheno：一个开放获取、用户友好、基于智能手机的软件平台，用于即时植物表型分析。

背景：植物表型在推进植物科学、农业和生物技术方面变得越来越重要。传统的手工方法是劳动密集型和耗时的，而现有的计算工具通常需要高级编码技能、高性能硬件或基于pc的环境，这使得非专业人员、资源受限的用户和现场技术人员无法使用它们。结果：为了应对这些挑战，我们推出了OpenPheno，这是一个开放获取、用户友好、基于智能手机的平台，封装在微信迷你程序中，用于即时植物表型分析。该平台旨在方便使用，使用户能够快速有效地使用智能手机进行植物性状表型分析。目前，我们通过SeedPheno、WheatHeadPheno、LeafAnglePheno、SpikeletPheno、CanopyPheno、tomatpheno和CornPheno等工具实例化了该平台的使用；每个都提供特定的功能，如种子大小和计数分析，小麦穗检测，叶片角度测量，小穗计数，冠层结构分析和番茄果实测量。特别是，OpenPheno允许开发人员贡献新的算法工具，进一步扩展其功能，不断促进植物表型社区的发展。结论：通过利用云计算和广泛访问的界面，OpenPheno使植物表型民主化，使更广泛的受众（包括植物科学家、育种者甚至业余爱好者）可以使用先进的工具。它可以在人工智能驱动的育种中发挥作用，为基因型-表型分析提供必要的数据，从而加快育种计划。它与智能手机的集成也使OpenPheno成为基于移动农业技术不断发展的领域的强大工具，为更高效、可扩展和更容易获得的农业研究和育种铺平了道路。

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来源期刊

Plant Methods 生物-植物科学

CiteScore

9.20

自引率

3.90%

发文量

121

审稿时长

2 months

期刊介绍： Plant Methods is an open access, peer-reviewed, online journal for the plant research community that encompasses all aspects of technological innovation in the plant sciences. There is no doubt that we have entered an exciting new era in plant biology. The completion of the Arabidopsis genome sequence, and the rapid progress being made in other plant genomics projects are providing unparalleled opportunities for progress in all areas of plant science. Nevertheless, enormous challenges lie ahead if we are to understand the function of every gene in the genome, and how the individual parts work together to make the whole organism. Achieving these goals will require an unprecedented collaborative effort, combining high-throughput, system-wide technologies with more focused approaches that integrate traditional disciplines such as cell biology, biochemistry and molecular genetics. Technological innovation is probably the most important catalyst for progress in any scientific discipline. Plant Methods’ goal is to stimulate the development and adoption of new and improved techniques and research tools and, where appropriate, to promote consistency of methodologies for better integration of data from different laboratories.