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Visual, semi-quantitative assessments allow accurate estimates of leafminer population densities: an example comparing image processing and visual evaluation of damage by the horse chestnut leafminer Cameraria ohridella (Lep., Gracillariidae)


Author's address: M. Gilbert (corresponding author), Laboratoire de Biologie animale et cellulaire, CP 160/12, Université Libre de Bruxelles, 50 av. F. D. Roosevelt, B-1050 Brussels, Belgium. E-mail:


Abstract: Qualitative or semi-quantitative visual assessments are most often used for estimating population size of herbivorous insects. The precision of these estimates, however, is often difficult to establish. A ‘simulation game’ with the horse chestnut leafminer, Cameraria ohridella Deschka & Dimic (Lep., Gracillariidae) shows that visual, semi-quantitative assessments can provide accurate information. Damaged areas of 411 horse chestnut leaves collected in 100 sites were closely related to mine numbers despite some variability in mine and leaf size (R2 = 0.915; n = 411; P < 0.001). On the basis of this relationship, two methods of population assessment are compared: (i) digital image processing of leaf damage and (ii) visual assessment using a damage key reflecting the relative infested area on each leaf (0, 0%; 1, 0–2%; 2, 2–5%; 3, 5–10%; 4, 10–25%; 5, 25–50%; 6, 50–75%; 7, 75–100%). Both methods used to estimate damage presented a similar, close relationship to the ‘real’ numbers of mines (R2 = 0.858; n = 777; P < 0.001 for image processing and R2 = 0.905; n = 777; P < 0.001 for visual assessment). The potential of using visual assessments as an accurate and fast method in situ at the tree scale is discussed.