NDAVI Improves Genotypic Discrimination in Dense Bread Wheat Canopies under Moderate Nitrogen Contrast
Makaleler > Tam Makale · 2026
Yazarlar: Deniz İŞTİPLİLER, Aliye YILDIRIM KESKİNOĞLU
Akademik Ziraat Dergisi, Uluslararası, 2026, cilt 15
DOI: 10.29278/azd.1972563
Özet
Objective: Rapid and non-destructive assessment of wheat canopy status is important for improving nitrogen management and field-based phenotyping. This study evaluated the ability of UAV-derived multispectral vegetation indices to detect canopy spectral variation associated with a moderate, non-zero nitrogen contrast and to discriminate among commercial bread wheat genotypes under dense canopy conditions during the reproductive stage. Materials and Methods: A field experiment was conducted during the 2024–2025 growing season in Bornova, İzmir, Türkiye, using ten commercial bread wheat cultivars grown under low-nitrogen (LN) and high-nitrogen (HN) treatments in a split-plot randomized complete block design with four replications. Multispectral imagery was acquired after heading and before anthesis using a DJI Matrice 350 RTK UAV equipped with a MicaSense RedEdge-P sensor. Four canopy vegetation indices, NDVI, GNDVI, CLRED, and NDAVI, were calculated from plot-level reflectance data. Each index was analyzed using linear mixed models, and index consistency was further evaluated using coefficient of variation, repeatability, and genotype-specific plasticity.Conclusion: Nitrogen treatment significantly affected NDVI, GNDVI, and NDAVI, with higher index values under HN than LN, whereas CLRED was not significantly affected by nitrogen. Among the evaluated indices, NDVI showed the strongest nitrogen response, indicating its usefulness for detecting overall nitrogen-related canopy differences. However, genotype effects were significant only for NDAVI, while NDVI, GNDVI, and CLRED did not provide reliable genotypic discrimination. NDAVI also showed the highest repeatability (0.791) and the lowest coefficient of variation (1.14%), supporting its superior consistency and discriminatory ability. UAV-derived multispectral indices successfully detected canopy spectral responses to moderate nitrogen differences in bread wheat, but nitrogen sensitivity and genotype discrimination differed substantially among indices. Among the evaluated indices, NDAVI appears to be the most promising index for detecting differences among wheat genotypes, particularly when conventional indices such as NDVI may be constrained by saturation.