TY  - SER
AU  - Suthima Homhual
AU  - Himanshu,Sushil Kumar
AU  - Datta,Avishek
AU  - Zulfiqar,Farhad
ED  - Her Majesty the Queen's Scholarship,
TI  - Assessment of leaf chlorophyll content in pangola grass (Digitaria eriantha) using UAV-derived vegetation indices and chlorophyll meter
T2  - Thesis
PY  - 2024///
CY  - Pathum Thani, Thailand
PB  - Asian Institute of Technology
KW  - Nitrogen
KW  - Vegetation mapping
KW  - Remote sensing
KW  - Chlorophyll
KW  - Analysis
KW  - Grasses
N1  - A Thesis submitted in partial fulfillment of the requirements for the degree of  Master of Engineering in Agricultural Systems and Engineering; Thesis (M. Eng.) - Asian Institute of Technology, 2024
N2  - Optimizing nitrogen (N) application in agricultural systems is crucial for enhancing  crop productivity and sustainability. This study delves into the impact of varying  nitrogen levels on plant health, specifically focusing on chlorophyll content and  vegetation higher nitrogen levels (60 kg/ha, 120 kg/ha, and 180 kg/ha) are associated  with increased plant height, larger leaf area, and higher yields in terms of fresh and dry  weight, indicating the positive effects of nitrogen on plant development indices as  indicators of plant vigor and nitrogen status. Through a comprehensive analysis  integrating field experiments and remote sensing techniques, we explore the intricate  relationships between nitrogen application, SPAD values, vegetation indices (NDVI,  NDRE, GNDVI) from UAVs and Plant-O-Meter, and total chlorophyll content. Higher  nitrogen levels consistently correlate with increased plant height, leaf area, and yields,  reflecting improved photosynthetic activity and overall plant health. Notably, SPAD  values and total chlorophyll content exhibit a strong positive correlation, with higher  SPAD values indicating greater chlorophyll concentration and enhanced photosynthetic  efficiency. Regression analyses reveal a precise relationship high coefficient of  determination (R² = 0.94), with every unit increase in SPAD values associated with a  significant rise in total chlorophyll content. Furthermore, the analysis of vegetation  indices (NDVI, NDRE, GNDVI) from UAVs and Plant-O-Meter shows consistent  positive correlations with total chlorophyll content, indicating the utility of remote  sensing data in assessing plant health and vigor. NDVI and GNDVI exhibit relatively  stronger associations compared to NDRE, explaining significant portions (51% to 74%)  of chlorophyll content variability, suggesting NDVI's and GNDVI's potential as a  powerful remote sensing tool for monitoring nitrogen-induced changes and evaluating  vegetation vigor remotely.
UR  - http://203.159.5.9/ait-thesis/detail.php?q=B21440
ER  -