Image‐Assisted Gap Estimation, a Simple Method for Measuring Grapevine Leaf Canopy Density

Abstract

ABSTRACTThis study compared an image analysis method of leaf canopy density measurement, image‐assisted gap estimation (ImAGE), with the commonly used point quadrat (PQ) analysis. For ImAGE, a blue background (plastic tarpaulin) was placed behind the grapevine (Vitis vinifera L.) row and digitally photographed and the image was analyzed using application‐specific software to calculate the area ratio of background to vine canopy. This was used as an estimate of the percentage area of gaps in the leaf canopy. Relationships among PQ leaf layer number (LLN), ImAGE gap area percentage (GAP), and fruit exposure were investigated in New Zealand vineyards during the 2008–2009 season in Hawke's Bay and in the 2008–2009 and 2009–2010 seasons at Pukekohe (Auckland region).. Gap area percentage was closely related (R2 = 0.87) to LLN. Significant relationships (p < 0.01) were also found between canopy density (measured by either method) and percentage severity of botrytis bunch rot at harvest. Image‐assisted gap estimation provides an alternative method to PQ analysis for measuring canopy density that is quicker, less subjective, and nondamaging. Image‐assisted gap estimation would primarily be useful as a low‐cost research tool as it could provide practical and rapid assessments without a significant investment in equipment. It may also help viticulturists achieve target leaf canopy densities for management of disease risk.