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Rapid acquisition, management, and analysis of spatial maize (Zea mays L.) phenological data—Towards ‘Big Data’ for agronomy transformation in Africa

Creator: Tonnang, H.
Creator: Balemi, T.
Creator: Masuki, K.
Creator: Mohammed, I.B.
Creator: Adewopo, J.
Creator: Adnan, A.A.
Creator: Mudereri, B.T.
Creator: Vanlauwe, B.
Creator: Craufurd, P.
Year: 2020
URI: https://hdl.handle.net/10883/21346
Language: English
Publisher: MDPI
Copyright: CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose
Type: Article
Country focus: Africa
Place of Publication: Basel (Switzerland)
Issue: 9
Volume: 10
DOI: 10.3390/agronomy10091363
Keywords: Apps
Keywords: Growing Degree Days
Keywords: Open Data Kit
Keywords: Servers
Keywords: Smartphones
Description: Mobile smartphones, open-source set tools, and mobile applications have provided vast opportunities for timely, accurate, and seamless data collection, aggregation, storage, and analysis of agricultural data in sub-Saharan Africa (SSA). In this paper, we advanced and demonstrated the practical use and application of a mobile smartphone-based tool, i.e., the Open Data Kit (ODK), to assemble and keep track of real-time maize (Zea mays L.) phenological data in three SSA countries. Farmers, extension agents, researchers, and other stakeholders were enlisted to participate in an initiative to demonstrate the applicability of mobile smartphone-based apps and open-source servers for rapid data collection and management. A pre-installed maize phenology data application based on the ODK architecture was provided to the participants (n = 75) for maize data collection and management over the maize growing season period in 2015–2017. The application structure was custom designed based on maize developmental stages such as planting date, date of emergence, date of first flowering, anthesis, grain filling, and maturity. Results showed that in Ethiopia, early maturing varieties took 105 days from sowing to maturity in low altitudes, whereas late-maturing varieties took up to 190 days to complete developmental stages in high altitude areas. In Tanzania, a similar trend was observed, whereas in Nigeria, most existing varieties took an average of 100 days to complete their developmental stages. Furthermore, the data showed that the durations from sowing to emergence, emergence to flowering, flowering to maturity were mainly dependent on temperature. The values of growing degree for each phase of development obtained from different planting dates were almost constant for each maize variety, which showed that temperature and planting time are the main elements affecting the rate of maize development. The data aggregation approach using the ODK and on-farm personnel improved efficiency and convenience in data collection and visualization. Our study demonstrates that this system can be used in crop management and research on many spatial scales, i.e., local, regional, and continental, with relatively high data collation accuracy.
Agrovoc: COMPUTER APPLICATIONS
Agrovoc: MAIZE
Agrovoc: OPEN DATA
ISSN: 2073-4395
Journal: Agronomy
Article number: 1363


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  • Sustainable Intensification
    Sustainable intensification agriculture including topics on cropping systems, agronomy, soil, mechanization, precision agriculture, etc.

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