Evidence map›Paper›PMID 30555523›Full record

ArticlePlant methods2018

Methodological approach for predicting and mapping the phenological adaptation of tropical maize (

Henri E Z Tonnang, Dan Makumbi, Peter Craufurd

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Article in Plant methods, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

3 authors.

Henri E Z Tonnang1International Institute of Tropical Agriculture (IITA), 08 BP 0932 Abomey Calavi, Cotonou, Benin.ORCID 0000-0002-9424-9186
Dan MakumbiInternational Maize and Wheat Improvement Center (CIMMYT), ICRAF House, United Nations, Avenue, Gigiri, P. O. Box 1041-00621, Nairobi, Kenya.
Peter CraufurdInternational Maize and Wheat Improvement Center (CIMMYT), ICRAF House, United Nations, Avenue, Gigiri, P. O. Box 1041-00621, Nairobi, Kenya.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe phenological development of the maize crop from emergence through flowering to maturity, usually expressed as a rate (i.e. 1/duration), is largely controlled by temperature in the tropics. Maize plant phenological responses vary between varieties and quantifying these responses can help in predicting the timing and duration of critical periods for crop growth that affect the quality and quantity of seed. We used routine multi-environment trials data of diverse tropical maize varieties to: (1) fit 82 temperature dependent phenology models and select the best model for an individual variety, (2) develop a spatial framework that uses the phenology model to predict at landscape level the length of the vegetative and reproductive phases of diverse varieties of maize in different agro-ecologies. Multi-environment trial data of 22 maize varieties from 16 trials in Kenya, Ethiopia, and Sudan was analyzed and the Levenberg-Marquardt algorithm combined with statistical criteria was applied to determine the best temperature-dependent model.

resultsThe Briere model, which is not often used in plant phenology, provided the best fit, with observed and predicted days to flowering showing good agreement. Linking the model with temperature and scaling out through mapping gave the duration from emergence to maturity of different maize varieties in areas where maize could potentially be grown.

conclusionThe methodology and framework used in the study provides an opportunity to develop tools that enhance farmers' ability to predict stages of maize development for efficient crop management decisions and assessment of climate change impacts. This methodology could contribute to increase maize production if used to identify varieties with desired maturity for a specific agro-ecology in in the targeted regions.

Indexed as

Environmental variablesLandscapeLength of growing periodTemperature dependent model

Identifiers

PMID30555523
PMCPMC6284281

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.