Performance of the SunScan canopy analysis system in estimating leaf area index of maize.

Rapid and reliable estimates of leaf area index (LAI) are important for studies of exchanges of energy and gases in the biosphere-atmosphere continuum. This paper evaluates the field performance of SunScan canopy analysis system for rapid estimation of LAI. Direct and indirect measurements of LAI were made in a maize (Zea mays L.) field at four phenological stages (emergence, vegetative, flowering and physiological maturity) at a tropical site in Ghana during the Glowa Vota Project field campaign (www.glowa-volta.de). Similar measurements were repeated in early and late planting seasons with similar crop management practices. The result showed a generally good performance of this sensor at all the phenological stages. Average LAI from the sensor (LAIS), ranged from 0.40-4.45, and was consistently higher than the actual LAI, which varied from 0.31-4.22, respectively for both seasons. Regression between LAI and LAIS showed a range of significant correlations with R² > 0.74 for all the stages and seasons. With combined datasets for all stages and the two plantings, a simple regression model was fitted to estimate LAI from LAIS with R² = 0.97 and standard error of 0.23 (P < 0.0001). The evaluated sensor yielded a good and reliable LAI estimates under maize canopy. [ABSTRACT FROM AUTHOR]