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Modeling growth, development and yield of cassava: a review

dc.contributor.authorMoreno-Cadena, L.P.
dc.contributor.authorHoogenboom, G.
dc.contributor.authorCock, J.H.
dc.contributor.authorRamirez-Villegas, J.
dc.contributor.authorPypers, P.
dc.contributor.authorKreye, C.
dc.contributor.authorTariku, M.
dc.contributor.authorEzui, K.S.
dc.contributor.authorLopez-Lavalle, L.A.
dc.contributor.authorAsseng, S.
dc.date.accessioned2022-09-28T10:48:28Z
dc.date.available2022-09-28T10:48:28Z
dc.date.issued2021-06-15
dc.identifier.citationMoreno-Cadena, L.P., Hoogenboom, G., Cock, J.H., Ramirez-Villegas, J., Pypers, P., Kreye, C., ... & Asseng, S. (2021). Modeling growth, development and yield of cassava: a review. Field Crops Research, 267: 108140, 1-13.
dc.identifier.issn0378-4290
dc.identifier.urihttps://hdl.handle.net/20.500.12478/7820
dc.description.abstractCassava is an important crop in the developing world. The goal of this study was to review published cassava models (18) for their capability to simulate storage root biomass and to categorize them into static and dynamic models. The majority (14) are dynamic and capture within season growth dynamics. Most (13) of the dynamic models consider environmental factors such as temperature, solar radiation, soil water and nutrient restrictions. More than half (10) have been calibrated for a distinct genotype. Only one of the four static models includes environmental variables. While the static regression models are useful to estimate final yield, their application is limited to the locations or varieties used for their development unless recalibrated for distinct conditions. Dynamic models simulate growth process and provide estimates of yield over time with, in most cases, no fixed maturity date. The dynamic models that simulate the detailed development of nodal units tend to be less accurate in determining final yield compared to the simpler dynamic and statistic models. However, they can be more safely applied to novel environmental conditions that can be explored in silico. Deficiencies in the current models are highlighted including suggestions on how they can be improved. None of the current dynamic cassava models adequately simulates the starch content of fresh cassava roots with almost all models based on dry biomass simulations. Further studies are necessary to develop a new module for existing cassava models to simulate cassava quality.
dc.description.sponsorshipBill & Melinda Gates Foundation
dc.format.extent1-13
dc.language.isoen
dc.subjectStorage
dc.subjectRoots
dc.subjectDecision Support Systems
dc.subjectFood Security
dc.subjectCassava
dc.titleModeling growth, development and yield of cassava: a review
dc.typeJournal Article
cg.contributor.crpRoots, Tubers and Bananas
cg.contributor.affiliationUniversity of Florida
cg.contributor.affiliationAlliance of Bioversity International and International Center for Tropical Agriculture
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.contributor.affiliationCGIAR Research Program on Climate Change, Agriculture and Food Security
cg.contributor.affiliationAfrican Plant Nutrition Institute, Kenya
cg.coverage.hubCentral Africa Hub
cg.coverage.hubHeadquarters and Western Africa Hub
cg.researchthemeNatural Resource Management
cg.identifier.bibtexciteidMORENOCADENA:2021
cg.isijournalISI Journal
cg.authorship.typesCGIAR and developing country institute
cg.iitasubjectAgronomy
cg.iitasubjectCassava
cg.iitasubjectFood Security
cg.iitasubjectPlant Breeding
cg.iitasubjectPlant Production
cg.journalField Crops Research
cg.notesPublished Online : 12 April 2021
cg.accessibilitystatusOpen Access
cg.reviewstatusPeer Review
cg.usagerightslicenseCreative Commons Attribution 4.0 (CC BY 0.0)
cg.targetaudienceScientists
cg.identifier.doihttps://dx.doi.org/10.1016/j.fcr.2021.108140
cg.iitaauthor.identifierPieter Pypers: 0000-0001-8913-0589
cg.iitaauthor.identifierChristine Kreye: 0000-0001-6090-2856
cg.futureupdate.requiredNo
cg.identifier.volume267
cg.contributor.acknowledgementsThis research is supported by the International Center for Tropical Agriculture (CIAT) and the International Institute of Tropical Agriculture (IITA) as part of the African Cassava Agronomy Initiative (ACAI, http://acai-project.org/) project funded by the Bill & Melinda Gates Foundation [grant number OPP1130649]. The first author acknowledges the Department of Agricultural and Biological Engineering of the University of Florida for providing a Latin America-Caribbean (LAC) scholarship. JR-V acknowledges support from the Climate Change, Agriculture and Food Security (CCAFS), under the project Agroclimas (http://bit.ly/2i3V0Nh). CCAFS is carried out with support from CGIAR Trust Fund Donors and through bilateral funding agreements. For details, please visit https://ccafs.cgiar.org/donors. The views expressed in this paper cannot be taken to reflect the official opinions of these organizations. We acknowledge the immense contribution by the late Myles J. Fisher helping us to understand plant models, and in guiding and mentoring the first author of this manuscript.


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