Estimation of stem and leaf dry biomass using a non-destructive method applied to African Coffea species

Abstract : The coffee tree is an important economic plant for several developing countries. Stem and leaf dry biomass, which are key traits of plant production, are used in functional-structural plant models to simulate plant growth and predict yield. These values are difficult to obtain since they classically rely on time-consuming protocols and require destructive measurements. Measuring stem and leaf dimensions (length and width) to estimate them provides a non-destructive and rapid approach for use in the field. In this study we sought the best allometric relationships existing between stem and leaf dimensions and their corresponding dry mass in order to avoid destructive measurements which are also time-consuming. This was investigated in three coffee species: Coffea canephora, Coffea liberica var. liberica and Coffea liberica var. dewevrei in Ivory Coast. For each species, the internodes and leaves of three axis categories (stem, branch and branchlet) comprising the main compartments were sampled. Two different equations were found to estimate the stem and leaf dry mass whatever the species and the axis categories: (1) a linear equation for the relation between the stem volume (V) and its corresponding dry mass (IWe), IWe = 0.70 × V and (2) a power law for the relation between the leaf area [as the product of length (LL) and width (Wi)] and its dry mass (LWe), LWe = 0.007 (LL × LWi)1.02. Finally, stem and leaf dry mass could be easily obtained without destructive measurements. This method could be applied to estimate the plant total leaf area and the total stem and leaf biomass of a plant in an agroforestry system.
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Michelle Okoma, S. Akaffou, Philippe de Reffye, P. Hamon, S. Hamon, et al.. Estimation of stem and leaf dry biomass using a non-destructive method applied to African Coffea species. Agroforestry Systems, Springer Verlag, 2018, 92 (3), pp.667 - 675. ⟨10.1007/s10457-016-0031-z⟩. ⟨hal-01823899⟩

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