| A. U. | Arbitrary Unit |
| AI | Artificial Intelligence |
| ANN | Artificial Neural Network |
| CNN | Convolutional Neural Network |
| DT | Decision Trees |
| ET | Ensemble Technique |
| GI | Glycemic Index |
| IoT | Internet of Things |
| IR | Infrared Red |
| ITSBLERP | Inference, Training, Scalability, Bandwidth, Latency, Economics, Reliability, and Privacy Characteristics |
| K-MC | K-Means Clustering |
| K-NN | K-Nearest Neighbor |
| LDA | Linear Discriminant Analysis |
| LI | Lifelong Learning (Ll) |
| LR | Linear Regression |
| LSTM | Long Short-Term Memory |
| MAE | Mean Absolute Error |
| MAP | Modified Atmosphere Packaging |
| MC | Moisture Content |
| ML | Machine Learning |
| NB | Naïve Bayes |
| NIR | Near-Infrared Red |
| PCA | Principal Component Analysis |
| MAPE | Mean absolute percentage error |
| RF | Random Forest |
| RLM | Reinforcement Learning Models |
| RMSE | Root Mean Square Error |
| RNN | Recurrent Neural Network |
| SC | Sugar Content |
| SSLED | Spectral Shelf Life Estimator For Dates |
| SVM | Support Vector Machines |
| SWNIR | Short-Wave Near-Infrared |
| TC | Tannin Content |
| TFLM | Tensor Flow Lite for Microcontrollers |
| TinyML | Tiny Machin Learning |
| TSS | Total Soluble Solids |
| wa | Water Activity |
| Xgboost | Extreme Gradient Boosting |