Many citrus groves in Florida were affected by hurricanes in Summer 2004. A commercial 42-acre `Valencia' sweet orange (Citrus sinensis) grove of 2980 trees was routinely scanned with an automated ultrasonic system to measure and map tree canopy volumes. We estimated tree damage by comparing canopy volumes measured before and after the hurricanes of 2004. Ultrasonically sensed tree canopy volume was mapped and the relative tree canopy volume loss percentage (TCVL%) for each tree was calculated and classified into six categories [≤0 (no damage), 1% to 24%, 25% to 49%, 50% to 74%, 75% to 99%, and 100%]. Authenticity of the ultrasonically sensed missing trees was established by ground truthing or matching visually observed and georeferenced missing tree locations with ultrasonically sensed missing trees in the grove. Ninety-one trees were found missing during ground inspections after hurricanes and they exactly matched with ultrasonically sensed missing tree locations throughout the grove. All of the missing trees were in TCVL% categories 5 and 6 (≥75% damage). Some canopy volume was still detected with ultrasonics at the missing tree locations because of the presence of tall grass, weeds, or branches of large adjacent trees. More than 50% of trees in the grove were damaged (completely or partially) and generally larger trees (>100 m3) were damaged more by the hurricanes than small or medium size trees in each tree canopy volume loss category. The automated ultrasonic system could be used to rapidly identify missing trees (completely damaged) and to estimate partial tree canopy volume loss after hurricanes.
Q.U. Zaman, A.W. Schumann, and H.K. Hostler
Kirandeep K. Mann, Arnold W. Schumann, Thomas A. Obreza, and Jerry B. Sartain
Citrus production in Florida is commonly affected by a high degree of spatial variability of soils. Therefore, this study developed rapid indicator crop bioassays to evaluate the relationships between indicator crops and citrus production at various soil depths. A citrus grove was divided into five productivity zones based on existing tree canopy volume using GIS software (“very poor,” “poor,” “medium,” “good,” and “very good”). Visual ratings of percentage cover were collected from each zone using a 1-m2 quadrant. Six random soil samples were collected between the tree rows from each productivity zone at four depths (0 to 15, 15 to 30, 30 to 45, and 45 to 60 cm). Greenhouse bioassay experiments used sorghum and radish crops grown in soil sampled from four depths. Overhead photographs of potted radish plants were captured periodically with a SLR digital camera to calculate leaf area by image processing. Shoot weights, shoot length, root weights, and leaf nutrient concentrations were measured at harvest (56 and 21 days after germination for sorghum and radish, respectively). Germination, shoot length, and shoot weight of sorghum and radish were significantly affected by the productivity zone. Sorghum (0 to 30 cm), radish (0 to 45 and 0 to 60 cm) and weed cover were strongly correlated (r ≈0.50 to 0.60***) with citrus yield and canopy volume at the lower two depths. The strong relationships (r > 0.50***) of sorghum and radish shoot weights and weed cover with soil properties at greater depths demonstrated the important role of cumulative root zone depth of 60 cm in differentiating citrus productivity. These results revealed that citrus production in poor areas of the grove was limited by the shallow depth of productive soil, and citrus productivity could be successfully mapped using indicator crop bioassays with soil samples taken at multiple depths.