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

Keyphrases

• Systems-based 100%
• Unmanned Aerial Systems 100%
• Vegetation Index 100%
• Morphological Parameters 100%
• Crop Biophysical Parameters 100%
• Chickpea 100%
• Biophysical Parameters 80%
• Leaf Area Index 80%
• Support Vector Machine Model 60%
• R2 Value 60%
• Index Parameter 60%
• Partial Least Squares Regression 40%
• Least Squares Support 40%
• Regression Vector 40%
• Order of Accuracy 20%
• Irrigation 20%
• RGB Image 20%
• Multiple Linear Regression 20%
• Plant Height 20%
• Model-based Testing 20%
• Statistical Model 20%
• Support Vector Machine 20%
• Semi-arid Area 20%
• Two-field 20%
• RGB-D Camera 20%
• Management Decisions 20%
• Plant Samples 20%
• Rainfed 20%
• Irrigation Periods 20%
• Biomass Model 20%
• Spring Crops 20%
• Harvest Date 20%
• Legume Crops 20%
• Irrigated Crops 20%
• Cicer Arietinum 20%
• Imaging Platform 20%
• Partial Least Squares Regression Model 20%
• Area Yield 20%
• Irrigation Regimes 20%
• RMSE Value 20%
• Full Maturity 20%
• Chickpea Varieties 20%

Agricultural and Biological Sciences

• Chickpea 100%
• Vegetation Index 71%
• Support Vector Machine 57%
• Leaf Area Index 57%
• Least Squares Method 42%
• Spring 14%
• Irrigation Management 14%
• Mathematical Model 14%
• Harvest Date 14%