RESUMEN
Concerns about methane (CH4) emissions from rice, a staple sustaining over 3.5 billion people globally, are heightened due to its status as the second-largest contributor to greenhouse gases, driving climate change. Accurate quantification of CH4 emissions from rice fields is crucial for understanding gas concentrations. Leveraging technological advancements, we present a groundbreaking solution that integrates machine learning and remote sensing data, challenging traditional closed chamber methods. To achieve this, our methodology involves extensive data collection using drones equipped with a Micasense Altum camera and ground sensors, effectively reducing reliance on labor-intensive and costly field sampling. In this experimental project, our research delves into the intricate relationship between environmental variables, such as soil conditions and weather patterns, and CH4 emissions. We achieved remarkable results by utilizing unmanned aerial vehicles (UAV) and evaluating over 20 regression models, emphasizing an R2 value of 0.98 and 0.95 for the training and testing data, respectively. This outcome designates the random forest regressor as the most suitable model with superior predictive capabilities. Notably, phosphorus, GRVI median, and cumulative soil and water temperature emerged as the model's fittest variables for predicting these values. Our findings underscore an innovative, cost-effective, and efficient alternative for quantifying CH4 emissions, marking a significant advancement in the technology-driven approach to evaluating rice growth parameters and vegetation indices, providing valuable insights for advancing gas emissions studies in rice paddies.
Asunto(s)
Agricultura , Contaminantes Atmosféricos , Monitoreo del Ambiente , Metano , Oryza , Tecnología de Sensores Remotos , Metano/análisis , Monitoreo del Ambiente/métodos , Contaminantes Atmosféricos/análisis , Agricultura/métodos , Dispositivos Aéreos No Tripulados , Gases de Efecto Invernadero/análisis , Suelo/química , Contaminación del Aire/estadística & datos numéricosRESUMEN
La aparición de un escenario teleonómico como respuesta a la relación de los académicos y los administrativos universitarios, que es propiciada por una tensión confianza - desconfianza, que en la actualidad como diada polarizada no es explorada como oportunidad dialógica, sino como obstáculo de los intereses unívocos, tendría efecto sobre la relación de la universidad con la sociedad en la medida en que permitiría, también reconociendo otras tensiones, forjar una identidad en apertura de posibilidades en la que académicos y administrativos universitarios se vinculen a través de objetivos y propósitos.
The appearance of a teleonomic scenario as an answer to the relation between university academics and staff, which is brought about by a trust-mistrust tension, which currently, as a polarized dyad, is not explored as a dialogical opportunity, but as an obstacle of univocal interests, would have an effect on the relation between university and society, inasmuch as it would allow, recognizing other tensions, as well, to forge an identity in favor of the possibilities in which university academics and staff are part through objectives and purposes.