A digital interactive decision dashboard for crop yield trials

IF 7.7 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Computers and Electronics in Agriculture Pub Date : 2025-02-01 DOI:10.1016/j.compag.2025.110037

Pedro Cisdeli , Gustavo Nocera Santiago , Carlos Hernandez , Ana Carcedo , P.V. Vara Prasad , Michael Stamm , Jane Lingenfelser , Ignacio Ciampitti

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引用次数: 0

Abstract

Globally, farmers face many challenges when taking rapid decisions related to crop management. Therefore, to serve as a decision-support tool, the outputs from research trials should be communicated near real-time (immediately after harvest) to avoid the lag time between data collection and publication in printed or electronic formats. Historically, crop yield trials provided invaluable information to farmers to help them decide the best crop genotypes based on their specific geographic locations. The aim of this application note is to highlight the development of a digital interactive decision dashboard for sharing crop yield trial data, in addition to functioning as a data repository. The current testing dataset involves yield trials for multiple crops in Kansas (within the United States, US) and winter canola across multiple US states. The development of the user interface involved Python programming with the Dash framework, while data manipulations were executed via the Pandas library. The tool empowers users to rapidly assess genotype yield trends year-to-year, incorporating location data for informed decision-making. The user-friendly interface facilitates data input, enabling non-programmers to analyze personal data effortlessly. The database is open to be expanded to include more trials around the globe, developing a comprehensive and more relevant yield data repository.

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来源期刊

Computers and Electronics in Agriculture 工程技术-计算机：跨学科应用

CiteScore

15.30

自引率

14.50%

发文量

800

审稿时长

62 days

期刊介绍： Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.