Keyphrases
Non-destructive
100%
Potato
100%
Machine Learning
100%
Nitrate Nitrogen
100%
Chlorophyll Meter
100%
Petiole Nitrate Concentration
100%
Multi-source Data Fusion
100%
Nitrogen Prediction
100%
Nitrate-N Concentration
83%
Random Forest
33%
N Status
33%
SPAD Reading
33%
Concentration Prediction
33%
Minnesota
16%
Nitrogen Fertilizer
16%
Weather Station
16%
Solanum Tuberosum
16%
Yield Quality
16%
Nitrogen N
16%
Fertilizer Source
16%
Application Rate
16%
N Rate
16%
N Stress
16%
Multivariate Linear Regression
16%
Laboratory Analysis
16%
Scaled Experiment
16%
Diagnostic Accuracy
16%
Environmental Conditions
16%
Remote Sensing Technology
16%
Genetic Management
16%
Proximal Sensing
16%
N Use Efficiency
16%
Regression Model
16%
Management Condition
16%
Linear Trend
16%
Transmittance
16%
Machine Learning Models
16%
Application Method
16%
Loamy Sand Soil
16%
Genetic Condition
16%
Least Squares Support Vector Regression (LSSVR)
16%
Stress Indicators
16%
R2 Value
16%
Simple Regression
16%
Tuber Yield
16%
Petiole
16%
Tree Model
16%
N Management
16%
Leaf Chlorophyll Content
16%
Accumulated Degree Days
16%
Three-machine
16%
Plant N Status
16%
Total Moisture
16%
Weather Information
16%
5-fold Cross Validation
16%
Status Diagnosis
16%
Robust Machine Learning
16%
Bayesian Optimization
16%
Extreme Gradient Boosting
16%
Promising Strategies
16%
Two-tree
16%
SPAD-502 Chlorophyll Meter
16%
Extreme Gradient Boosting Regression
16%
Petiole Analysis
16%
Technology Stress
16%
Agricultural and Biological Sciences
Petiole
100%
Chlorophyll
100%
Cultivar
12%
Solanum Tuberosum
12%
Weather Stations
12%
Growing Degree-Day
12%
Loamy Sand Soils
12%
Application Rate
12%
Application Method
12%
Support Vector Machine
12%
Remote Sensing
12%