Real-time monitoring of ammonia emissions from cereal crops using LoRaWAN-based sensing technology
Rattachement africain : hu, pk, ie, jo. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
This study presents a LoRaWAN-based IoT system developed for real-time monitoring of ammonia (NH₃) emissions in cereal crop fields. Sustainable agriculture increasingly demands on-farm greenhouse gas (GHG) tracking linked to environmental variables. IoT offers efficient real-time monitoring of soil NH₃ emissions and associated factors. Our research introduces a unique Field Monitoring Laboratory: a LoRaWAN-connected IoT system integrating soil, crop, and microclimate sensors to observe NH₃⁺, air temperature, rainfall, humidity, soil temperature, and moisture content. The system comprises a field lab, data server, and custom dashboard with analytics capabilities. NH₃ fluxes were measured in autumn-sown cereals across three growing seasons (2020-2023). Tukey's Kramer test revealed significant (p < 0.05, p < 0.001) differences in NH₃ emissions and environmental variables between years. Highest NH₃ emissions (1.94 ppm in 2020, 1.71 ppm in 2021) coincided with elevated air (25-31 °C) and soil (21-23 °C) temperatures, and higher mean and peak rainfall (0.40-0.48 mm average; max 9-31.6 mm). Principal Component Analysis showed 65.8% variance explained by PC1 and PC2, with high loadings from temperature and soil moisture. Spearman's correlation indicated moderate positive associations (r = 0.38-0.4, p < 0.05) of NH₃ with soil moisture at 20 cm and 40 cm of soil depth, and a weak negative correlation (r = -0.16 and - 0.17) with soil temperature at 20 cm and 40 cm. The study underscores the potential of IoT technology using calibrated gas sensors and LoRaWAN for real-time NH₃ and environmental monitoring, enabling informed decision-making in smart agriculture.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Real-time monitoring of ammonia emissions from cereal crops using LoRaWAN-based sensing technology
- Date Crossref
- 06/12/2025
- Éditeur
- Springer Science and Business Media LLC
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
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