UAS-based imaging for prediction of chickpea crop biophysical parameters and yield

Keyphrases

• Systems-based 100%
• Chickpea 100%
• Unmanned Aerial Systems 100%
• Crop Biophysical Parameters 100%
• Vegetation Index 83%
• Morphological Parameters 83%
• Leaf Area Index 66%
• Biophysical Parameters 66%
• R2 Value 50%
• Support Vector Machine Model 50%
• Index Parameters 50%
• Partial Least Squares Regression 33%
• Least Squares Support 33%
• Regression Vectors 33%
• Statistical Model 16%
• Irrigation Regime 16%
• Irrigation 16%
• Cicer Arietinum 16%
• Two-field 16%
• Model-based Testing 16%
• Legume Crops 16%
• Support Vector Machine 16%
• Multivariate Linear Regression 16%
• Plant Height 16%
• Irrigated Crops 16%
• Semi-arid Area 16%
• Harvest Date 16%
• RGB Image 16%
• Order of Accuracy 16%
• Management Decisions 16%
• Rainfed 16%
• Imaging Platform 16%
• Partial Least Squares Regression Model 16%
• Plant Samples 16%
• Irrigation Periods 16%
• Biomass Model 16%
• Spring Crops 16%
• RGB-D Camera 16%
• Area Yield 16%

Agricultural and Biological Sciences

• Chickpea 100%
• Vegetation Index 71%
• Support Vector Machine 57%
• Leaf Area Index 57%
• Least Square 42%
• Irrigation 28%
• Irrigation Management 14%
• Cicer Arietinum 14%
• Spring 14%
• Mathematical Model 14%
• Harvest Date 14%