FPGA-based wireless smart sensor for real-time photosynthesis monitoring

• Wireless photosynthesis measurement.
• Real time net photosynthesis calculation through FPGA-based signal processing.
• Accuracy improvement in CO2 signal by digital oversampling and Kalman filtering.
• Novel derivative and integrative indexes from net photosynthesis.
• Results of monitoring a Capsicum annuum L. plant with the proposed system.

Photosynthesis is considered the most important physiological function because it constitutes the main biomass entrance for the planet and consequently it permits the continuance of life on earth. Therefore, accurate photosynthesis measurement methods are required to understand many photosynthesis-related phenomena and to characterize new plant varieties. This project has been carried out to cover those necessities by developing a novel FPGA-based photosynthesis smart sensor. The smart sensor is capable of acquiring and fusing the primary sensor signals to measure temperature, relative humidity, solar radiation, CO2, air pressure and air flow. The measurements are used to calculate net photosynthesis in real time and transmit the data via wireless communication to a sink node. Also it is capable of estimating other response variables such as: carbon content, accumulated photosynthesis and photosynthesis first derivative. This permits the estimation of carbon balance and integrative and derivative variables from net photosynthesis in real time due to the FPGA processing capabilities. In addition, the proposed smart sensor is capable of performing signal processing, such as average decimation and Kalman filters, to the primary sensor readings so as to decrease the amount of noise, especially in the CO2 sensor while improving its accuracy. In order to prove the effectiveness of the proposed system, an experiment was carried out to monitor the photosynthetic response of chili pepper (Capsicum annuum L.) as case of study in which photosynthetic activity can successfully be observed during the excitation light periods. Results revealed useful information which can be utilized as new tool for precision agriculture by estimating the aforementioned variables and also the derivative and integrative new indexes. These indexes can be utilized to estimate carbon accumulation over the crop cycle and fast derivative photosynthesis changes in relation to the net photosynthesis measurement which can be utilized to detect different stress conditions in the crops, permitting growers to apply a correction strategy with opportunity.

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