| Chapter 1 | |
| Table 1. | Ranking Position of First Priority and Protection Country (2001–2010) and (2011–2021). |
| Chapter 2 | |
| Table 1. | Applications: Benefits, Challenges, and Major Enablers. |
| Table 2. | Perceived Benefits of the Different Technologies by the Respondents. |
| Chapter 3 | |
| Table 1. | Literature Support for the Identified Variables. |
| Table 2. | Initial Reachability Matrix. |
| Table 3. | Final Reachability Matrix. |
| Table 4. | Consolidated Levels of Variables. |
| Annexure 1. | Demographic Details of Respondents. |
| Annexure 2. | Interpretive Logic-Knowledge Base. |
| Chapter 5 | |
| Table 1. | Standardized Parameter Estimates for Structural Model. |
| Chapter 6 | |
| Table 1. | Shows an Example of How “Hash” Changes Dramatically with a Small Change in Input. |
| Table 2. | Cloud Computing of Wheat Supply Chain Information. |
| Chapter 7 | |
| Table 1. | Performance Evaluation of Proposed Product Quality Monitoring System. |
| Chapter 8 | |
| Table 1. | IoT Sensor Categories and the Common Measurement Parameters. |
| Table 2. | IoT Applications and Their Benefits. |
| Chapter 9 | |
| Table 1. | Experimental Results. |
| Chapter 10 | |
| Table 1. | Ranking of AI Benefits. |
| Table 2. | ANOVA for Agritech Industry and AI Benefits. |
| Table 3. | Mean Values for Categories under Value Chain Position. |
| Table 4. | Mean Values for Categories under Several Employees. |
| Table 5. | Mean Values for Categories under Nature of Industry. |
| Table 6. | Mean Value for Categories under Type of Business Organization. |
| Table 7. | Mean Values for Agri-Tech Category. |
| Table 8. | Mean Values for Categories under Market Coverage. |
| Table 9. | Mean Values for the Number of Years in the Agritech Business. |
| Table 10. | Ranking of AI Problems. |
| Table 11. | ANOVA for Agritech Industry Profile and AI Problems. |
| Table 12. | Mean Value for Categories under Value Chain Position. |
| Table 13. | Mean Value for Categories under Number of Employees. |
| Table 14. | Mean Values for Categories under Nature of Industry. |
| Table 15. | Type of Business Organization. |
| Table 16. | Mean Values for Agritech Category. |
| Table 17. | Mean Values for Market Coverage. |
| Table 18. | Mean Values for Categories under Number of Years in the Agritech Companies. |
| Table 19. | Chi-Square Test for Profile of Agritech Company and AI Dimensions. |
| Annexure 1. | AI Benefits. |
| Annexure 2. | AI Problems. |
| Chapter 11 | |
| Table 1. | Commercially Available Smart (Active and Intelligent) Packing Systems. |
| Chapter 12 | |
| Table 1. | Industry 4.0 Technologies and Their Applications in Agricultural Supply Chains |
| Chapter 1 | |
| Table 1. | Ranking Position of First Priority and Protection Country (2001–2010) and (2011–2021). |
| Chapter 2 | |
| Table 1. | Applications: Benefits, Challenges, and Major Enablers. |
| Table 2. | Perceived Benefits of the Different Technologies by the Respondents. |
| Chapter 3 | |
| Table 1. | Literature Support for the Identified Variables. |
| Table 2. | Initial Reachability Matrix. |
| Table 3. | Final Reachability Matrix. |
| Table 4. | Consolidated Levels of Variables. |
| Annexure 1. | Demographic Details of Respondents. |
| Annexure 2. | Interpretive Logic-Knowledge Base. |
| Chapter 5 | |
| Table 1. | Standardized Parameter Estimates for Structural Model. |
| Chapter 6 | |
| Table 1. | Shows an Example of How “Hash” Changes Dramatically with a Small Change in Input. |
| Table 2. | Cloud Computing of Wheat Supply Chain Information. |
| Chapter 7 | |
| Table 1. | Performance Evaluation of Proposed Product Quality Monitoring System. |
| Chapter 8 | |
| Table 1. | IoT Sensor Categories and the Common Measurement Parameters. |
| Table 2. | IoT Applications and Their Benefits. |
| Chapter 9 | |
| Table 1. | Experimental Results. |
| Chapter 10 | |
| Table 1. | Ranking of AI Benefits. |
| Table 2. | ANOVA for Agritech Industry and AI Benefits. |
| Table 3. | Mean Values for Categories under Value Chain Position. |
| Table 4. | Mean Values for Categories under Several Employees. |
| Table 5. | Mean Values for Categories under Nature of Industry. |
| Table 6. | Mean Value for Categories under Type of Business Organization. |
| Table 7. | Mean Values for Agri-Tech Category. |
| Table 8. | Mean Values for Categories under Market Coverage. |
| Table 9. | Mean Values for the Number of Years in the Agritech Business. |
| Table 10. | Ranking of AI Problems. |
| Table 11. | ANOVA for Agritech Industry Profile and AI Problems. |
| Table 12. | Mean Value for Categories under Value Chain Position. |
| Table 13. | Mean Value for Categories under Number of Employees. |
| Table 14. | Mean Values for Categories under Nature of Industry. |
| Table 15. | Type of Business Organization. |
| Table 16. | Mean Values for Agritech Category. |
| Table 17. | Mean Values for Market Coverage. |
| Table 18. | Mean Values for Categories under Number of Years in the Agritech Companies. |
| Table 19. | Chi-Square Test for Profile of Agritech Company and AI Dimensions. |
| Annexure 1. | AI Benefits. |
| Annexure 2. | AI Problems. |
| Chapter 11 | |
| Table 1. | Commercially Available Smart (Active and Intelligent) Packing Systems. |
| Chapter 12 | |
| Table 1. | Industry 4.0 Technologies and Their Applications in Agricultural Supply Chains |
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