International Journal of Agriculture Innovation, Technology and Globalisation (5 papers in press)

Regular Issues

• Global hunger is on the rise: investigating the pillar of stability in developing countries agribusinesses  
  by Maximilian Haug, Axel Hund, Heiko Gewald 
  Abstract: The 11th Global Food Security Index reported a deterioration in the global food environment for the third year. This development alarms global food security, especially for developing countries, which was highlighted during the COVID-19 pandemic in how fragile food supply chains can be and, therefore, directly threaten human lives. Literature suggests that digitalisation can overcome problems within the food supply chain. We use the case of Mauritius, a developing country, to various challenges related to food security. We focus on and investigate the food security pillar of stability while elaborating on the role of digital technologies within it. Our interviews reveal challenges such as distrust among stakeholders, a corresponding lack of collaboration among all stakeholders, and inadequate governmental interventions.
  Keywords: food security; digital technology; developing countries; stability; Mauritius; information technology; sustainability; agribusiness; availability; access; pillar.
  DOI: 10.1504/IJAITG.2025.10077662
   
  
• Exploring repeat purchase behaviour for organic food: evidence from an extended TPB framework  
  by Anju Yadav, Sunil Kumar 
  Abstract: The growing awareness of environmental sustainability and health consciousness has significantly increased the demand for organic food, particularly among younger consumers. This study investigates the determinants of repeat purchase behaviour toward organic food by extending the theory of planned behaviour. Data were collected through a structured survey from 446 consumers in Delhi NCR who had purchased organic food within the previous three months. The relationships among extended TPB constructs were analysed using PLS-SEM. The results indicate that subjective norms and environmental concern exert a stronger and more significant influence on purchase intention than other TPB variables. Purchase intention is found to be a key predictor of actual buying behaviour, which subsequently drives repeat purchase behaviour. The study highlights the growing importance of social influence and ecological values in sustaining organic food consumption. It extends TPB by incorporating environmental concern and offers managerial insights for promoting long-term organic food consumption and consumer loyalty.
  Keywords: theory of planned behaviour; TPB; organic food products; sustainability; environmental concern; repeat purchase behaviour.
  DOI: 10.1504/IJAITG.2026.10078126
   
  
• Deployable lightweight deep learning models for multiclass classification of cocoa and coffee seeds  
  by Emmanuel Asante, Ezekiel Mensah Martey, Eric Opoku, Obed Appiah, Emmanuel Effah 
  Abstract: Accurate cocoa and coffee seed classification is vital for quality control, especially in sub-Saharan Africa, where manual inspection is subjective and labour-intensive. This study tests deep learning models for automated seed classification using multi-source images from variable field conditions. Twelve CNNs, including high-capacity and lightweight architectures, were trained and evaluated following a unified protocol. All models were exported to TensorFlow Lite, quantised to 8-bit, and benchmarked on deployment-ready graphs. Evaluation across accuracy, precision, recall, F1-score, size, parameters, FLOPs, and inference latency showed that lightweight models achieved the best trade-off between accuracy and latency. MobileNetV3Small had the highest performance at 98.7% accuracy and 79 ms latency, followed by MNasNet (96%, 71 ms). DenseNet121 performed well (95.8%) but with a higher computational cost. These findings show compact neural networks, when optimised, can match or outperform larger models for real-time mobile deployment.
  Keywords: multiclass cocoa-coffee classification; deployable deep learning models; lightweight CNNs; agricultural innovation; seed quality assessment.
  DOI: 10.1504/IJAITG.2026.10078417
   
  
• Aflatoxin awareness and food security among smallholder farmers in Tanzania  
  by Fulgence Dominick Waryoba 
  Abstract: Consumption of aflatoxin contaminated food causes serious human health problems. Extant literature paid much attention on awareness levels about the effects and causes of aflatoxin contamination. But, less is known about how aflatoxin contamination awareness affects food quality in a causal relationship manner. The analytical framework of this study integrated situation awareness theory and techno-ecology theory using structural equation modelling. The study found that farmers are highly informed on the causes especially at the food storage stage, while less informed on the effects. Although the effect of aflatoxin contamination awareness on food security is only significant at the farm preparation stage, the analytical framework can be adapted for appropriate agricultural policy decisions at global, regional and country level. By adding more regions or enhancing longitudinal analysis and using aflatoxin test kits, future studies can overcome the technical faults of the current study.
  Keywords: aflatoxin awareness; aflatoxin contamination; food security; situation awareness; technology adaptation; ecological system; structural equation modeling; global agricultural policy decision.
  DOI: 10.1504/IJAITG.2026.10078748
   
  
• AeroAgriNet: swarm intelligent flying edge machines for precision Agriculture 4.0  
  by Mohammad Shahnawaz Shaikh 
  Abstract: This study presents AeroAgriNet, a swarm-intelligent flying-edge framework designed to enable autonomous, low-latency aerial intelligence for precision agriculture in connectivity-constrained farmlands. The architecture allows each UAV to operate as a mobile edge node with on-board AI inference, decentralised coordination, IoT-supported decision-making, and federated learning. Experimental and simulation results demonstrate significant performance improvements over cloud-based systems, achieving latency of 94
  Keywords: computational offloading; distributed inference; edge computing; federated learning; federated learning; FL; multi UAV collaboration; real-time analytics; swarm robotics; wireless sensor networks; SDG 2 zero hunger; SDG 9 industry; innovation and infrastructure.
  DOI: 10.1504/IJAITG.2026.10078988