Title:	Sensor-Based Platform for Evaluation of Atmospheric Carbon Sequestration's Potential by Maize Crops.
Authors:	CRUVINEL, P. E. COLNAGO, L. A.
Affiliation:	PAULO ESTEVAO CRUVINEL, CNPDIA; LUIZ ALBERTO COLNAGO, CNPDIA.
Date Issued:	2025
Citation:	In: THE TENTH INTERNATIONAL CONFERENCE ON ADVANCES IN SENSORS, ACTUATORS, METERING AND SENSING - ALLSENSORS 2025, 2025, Nice, France. Proceedings... Wilmington, USA: IARIA, 2025.
Pages:	6 p.
Description:	The development of sensor-based techniques has been allowing advanced studies for agriculture’s decision support systems. This paper discusses an innovative sensorbased method for the evaluation of CO₂ sequestration potential from the atmosphere by agricultural crop environments. This study has led to new insights into the management of crop fields for food and biomass production for energy. It also brings together information related to the carbon sequestration potential, which can allow opportunities not only for the use of sensors and related techniques in soil science but also for value aggregation for the agricultural process and environmental care. For validation, an experimental maize crop area has been used. Besides, studies about atmospheric carbon sequestration potential were evaluated. Such analyses have become possible by using vegetation indexes related to the normalized difference vegetation and the modified chlorophyll absorption in reflective, both calculated with data acquired using a multispectral sensor. In addition, three other sensors have been used for solar light intensity, soil water content, and air temperature measurements. Results have shown the spatial variability of the carbon sequestration potential, as well as its temporal variability when considering different phenomenological phases of the maize culture. Furthermore, a positive correlation with plant management and the carbon sequestration potential has been found, i.e., leading to an adequate new sensor-based descriptor for atmospheric carbon sequestration by plants evaluation.
Keywords:	Light-band sensors Intelligent instrumentation
Type of Material:	Artigo em anais e proceedings
Access:	openAccess
Appears in Collections:	Artigo em anais de congresso (CNPDIA)