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    Banana biomass estimation and yield forecasting from non-destructive measurements for two contrasting cultivars and water regimes

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    Journal Article (1.560Mb)
    Authors
    Stevens, B.
    Diels, J.
    Brown, A.
    Bayo, S.
    Ndakidemi, P. A.
    Swennen, Rony L.
    Date
    2020-09
    Language
    en
    Type
    Journal Article
    Review status
    Peer Review
    ISI journal
    Accessibility
    Open Access
    Usage rights
    CC-BY-4.0
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    Citation
    Stevens, B., Diels, J., Brown, A., Bayo, S., Ndakidemi, P. A., & Swennen, R. (2020). Banana biomass estimation and yield forecasting from non-destructive measurements for two contrasting cultivars and water regimes. Agronomy, 10(9): 1435, 1-26.
    Permanent link to cite or share this item: https://hdl.handle.net/10568/109897
    DOI: https://doi.org/10.3390/agronomy10091435
    Abstract/Description
    The largest abiotic constraint threatening banana (Musa spp.) production is water stress, impacting biomass buildup and yields; however, so far no studies have investigated the effects of water stress on allometric equations in banana. Weighted least square regression models were built for (i) estimating aboveground vegetative dry biomass (ABGVD) and corm dry biomass (cormD) and (ii) forecasting bunch fresh weight (bunchF), based on non-destructive parameters for two cultivars, Mchare Huti-Green Bell (HG, AA) and Cavendish Grande Naine (GN, AAA), under two irrigation regimes: full irrigation (FI) and rainfed (RF). FI affected growth, yield, and phenological parameters in the field (p < 0.05) depending on the onset of moisture stress. Pseudostem volume (Vpseudo) proved a good predictor for estimating ABGVD (R2adj = 0.88–0.92; RRMSE = 0.14–0.19), but suboptimal for cormD (R2adj = 0.90–0.89, RRMSE = 0.21–0.26 for HG; R2adj = 0.34–0.57, RRMSE = 0.38–0.43 for GN). Differences between RF and FI models (p < 0.05) were small as 95%CI overlapped. Vpseudo at flowering predicted bunchF in FI plots correctly (R2adj = 0.70 for HG, R2adj = 0.43 for GN; RRMSE = 0.12–0.15 for HG and GN). Differences between FI and RF models were pronounced as 95%CI did not overlap (p < 0.05). Bunch allometry was affected by irrigation, proving bunchF forecasting needs to include information on moisture stress during bunch filling or information on bunch parameters. Our allometric relationships can be used for rapid and non-destructive aboveground vegetative biomass (ABGVD) assessment over time and to forecast bunch potentials based on Vpseudo at flowering.
    CGIAR Author ORCID iDs
    Allen Brownhttps://orcid.org/0000-0002-4468-5932
    Rony Swennenhttps://orcid.org/0000-0002-5258-9043
    Notes
    Open Access Journal
    Other CGIAR Affiliations
    Agriculture for Nutrition and Health; Roots, Tubers and Bananas
    AGROVOC Keywords
    allometry; biomass; forecasting; regression analysis; water stress; drought stress; abiotic factors
    Subjects
    AGRONOMY; BANANA; CLIMATE CHANGE; PLANT BREEDING; PLANT PRODUCTION
    Countries
    Nigeria; Tanzania
    Regions
    Africa; Eastern Africa; Western Africa
    Organizations Affiliated to the Authors
    Katholieke Universiteit Leuven; International Institute of Tropical Agriculture; Nelson Mandela Africa Institution of Science and Technology
    Investors/sponsors
    Flemish Inter-university Council – University Development Co-operation, Belgium
    Collections
    • Alliance Bioversity CIAT Journal Articles [954]
    • IITA Journal Articles [4887]
    • Research Lever 4: Biodiversity for Food and Agriculture [505]
    • RTB Journal Articles [1330]

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