Prediction models for estimating available fodder of two savanna tree species (Acacia dudgeoni and Balanites aegyptiaca) based on field and image analysis measures
AbstractBrowse production is difficult to measure non-destructively without some level of subjectivity combined with a lack of accuracy and reproducibility. This study examined the possibility of using ground-based photographs to estimate browse production. Thirty five sample trees of Acacia dudgeoni and Balanites aegyptiaca were selected. Tree crown area (CA) was measured from twodimensional images using computer-based image analysis. Browse biomass from destructive sampling was correlated with CA and measured tree variables. The results from the regression analysis indicated that all models were significant (all p values < 0.05) for the two species but the predictive power was low for Acacia (r2 < 0.50) compared to Balanites (r2 > 0.75). The establishment of a relationship between browse and crown area (CA) estimated from photographs or the field measured crown area (PCA) indicated that the fit of the relationship was better for PCA (r2 adjusted = 0.75) compared to CA (r2 adjusted = 0.73) for Balanites. For Acacia, regression coefficients for CA and PCA were 45% and 33%, respectively. The image analysis technique could offer an objective method for estimating biomass changes by browsing, lopping and seasonal leaf fall when coupled with dendrometric measures.
Keywords: available browse, binary image, biomass equations, carrying capacity, dry savanna
African Journal of Range & Forage Science 2007, 24(2): 63–71