Please use this identifier to cite or link to this item: https://cris.library.msu.ac.zw//handle/11408/5468
Title: PPMaP: Reproducible and extensible Open-Source Software for plant phenological phase duration prediction and mapping in Sub-Saharan Africa
Authors: Henri E. Z. Tonnang
Ritter A. Guimapi
Anani Y. Bruce
Dan Makumbi
Bester T. Mudereri
Tesfaye Balemi
Peter Craufurd
International Maize and Wheat Improvement Center (CIMMYT), off UN Avenue, Gigiri, ICRAF House, Nairobi P.O. Box 1041-0062, Kenya; International Centre of Insect Physiology and Ecology (icipe), Nairobi P.O. Box 30772-00100, Kenya
Biotechnology and Plant Health Division, Norwegian Institute of Bioeconomy Research (NIBIO), P.O. Box 115, 1433 Ås, Norway
International Maize and Wheat Improvement Center (CIMMYT), off UN Avenue, Gigiri, ICRAF House, Nairobi P.O. Box 1041-0062, Kenya
International Maize and Wheat Improvement Center (CIMMYT), off UN Avenue, Gigiri, ICRAF House, Nairobi P.O. Box 1041-0062, Kenya
International Centre of Insect Physiology and Ecology (icipe), Nairobi P.O. Box 30772-00100, Kenya; Department of Animal and Wildlife Science, Midlands State University, P. Bag., Gweru 9055, Zimbabwe
Ethiopian Institute of Agricultural Research, Addis Ababa P.O. Box 2003, Ethiopia
International Maize and Wheat Improvement Center (CIMMYT), off UN Avenue, Gigiri, ICRAF House, Nairobi P.O. Box 1041-0062, Kenya
Keywords: Plant development rate
Temperature-dependent
Landscape
Multi-location trials
Issue Date: 30-Oct-2020
Publisher: MDPI
Abstract: Understanding the detailed timing of crop phenology and their variability enhances grain yield and quality by providing precise scheduling of irrigation, fertilization, and crop protection mechanisms. Advances in information and communication technology (ICT) provide a unique opportunity to develop agriculture-related tools that enhance wall-to-wall upscaling of data outputs from point-location data to wide-area spatial scales. Because of the heterogeneity of the worldwide agro-ecological zones where crops are cultivated, it is unproductive to perform plant phenology research without providing means to upscale results to landscape-level while safeguarding field-scale relevance. This paper presents an advanced, reproducible, and open-source software for plant phenology prediction and mapping (PPMaP) that inputs data obtained from multi-location field experiments to derive models for any crop variety. This information can then be applied consecutively at a localized grid within a spatial framework to produce plant phenology predictions at the landscape level. This software runs on the ‘Windows’ platform and supports the development of process-oriented and temperature-driven plant phenology models by intuitively and interactively leading the user through a step-by-step progression to the production of spatial maps for any region of interest in sub-Saharan Africa. Maize (Zea mays L.) was used to demonstrate the robustness, versatility, and high computing efficiency of the resulting modeling outputs of the PPMaP. The framework was implemented in R, providing a flexible and easy-to-use GUI interface. Since this allows for appropriate scaling to the larger spatial domain, the software can effectively be used to determine the spatially explicit length of growing period (LGP) of any variety.
URI: https://cris.library.msu.ac.zw//handle/11408/5468
Appears in Collections:Research Papers

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