Background: It was noted that academic studies on Digital Transformations (DT) and OHS are generally conducted at the national level in developing and underdeveloped countries. In this context, it was stated that the issue concerns the whole of humanity and that joint studies should be conducted across countries. Methods: This research is based on the relational survey model and uses a quantitative approach, with the survey method as the data collection tool. Survey participants were selected by a simple random sampling method, so that each individual constituting the universe has an equal probability of participating in the research. Results: As a result, within the scope of digital transformation, it was determined that the personal development of the workers affected the managerial measures and precautions and awareness and consciousness levels of occupational health and safety practices, whereas it did not affect the variables of training cooperation and communication. Conclusion: As a result of the regression analyses performed in the study, it was concluded that the administrative measures and measures taken regarding OHS have a positive effect on work efficiency, personal development of employees, communication between employees, and cooperation between employees.
Regional dairy brands invest in blockchain traceability, but price premiums depend on perceived authenticity and food-safety reassurance. We conduct choice experiments with urban and rural shoppers and estimate mixed logit models for label attributes. Transparency on farm origin and antibiotic use drives premiums more than technology claims alone.
Brief water deficit before heat waves can precondition seedlings, but metabolic signatures of effective priming remain unclear. We apply controlled drought cycles followed by heat chambers and profile polar metabolites via LC-MS. Primed seedlings accumulate distinct osmolyte and antioxidant profiles associated with maintained membrane integrity during subsequent stress.
Irrigation modernization programs assume linear responses to capital subsidies, yet neighbor effects and credit constraints produce heterogeneous uptake. We parameterize an agent-based model with survey data on risk preferences and social learning and simulate policy mixes. Partial subsidies paired with demonstration plots accelerate adoption more than lump-sum grants alone.
Aggregate-protected carbon pools respond slowly to management, complicating verification of sequestration claims. We sample long-term rotation plots with physical fractionation and compare cover-crop mixes against fallow controls. Particulate organic matter increases under mixed covers, while mineral-associated carbon shows gains only when tillage intensity remains low for a decade or more.
Extended cold storage can suppress ripening but alter aroma profiles if oxygen and carbon dioxide regimes are mismatched. We monitor firmness, soluble solids, and volatile emissions in replicated chambers across three cultivars. Optimal gas combinations differ by cultivar, supporting cultivar-specific storage protocols rather than uniform setpoints.
Seasonal livestock movement intersects with expanding cropland and conservation boundaries in ways that official cadastral maps rarely capture. We facilitate participatory mapping sessions with herder associations and compile digitized corridor routes against reported conflict incidents. Overlay analysis highlights pinch points where mediation and water-point investments could reduce encroachment pressure.
Farm-scale digesters promise to close nutrient loops while displacing fossil heat, yet system boundaries strongly affect reported emissions. We compare wet and dry digestion configurations for mixed livestock and crop residues using attributional life cycle assessment. Dry digestion reduces transport burdens but increases methane slip unless scrubbing is maintained.
Early blight detection in field crops often relies on visual scouting that misses incipient lesions. We collect multispectral orthomosaics from small unmanned aerial vehicles over replicated trial plots and train gradient-boosted classifiers on ground-truth severity scores. Cross-validated models discriminate low versus high pressure zones with sufficient accuracy to guide variable fungicide applications.