Abstract

Plant transpiration is considered one of the most important physiological functions because it constitutes the plants evolving adaptation to exchange moisture with a dry atmosphere which can dehydrate or eventually kill the plant. Due to the importance of transpiration, accurate measurement methods are required; therefore, a smart sensor that fuses five primary sensors is proposed which can measure air temperature, leaf temperature, air relative humidity, plant out relative humidity and ambient light. A field programmable gate array based unit is used to perform signal processing algorithms as average decimation and infinite impulse response filters to the primary sensor readings in order to reduce the signal noise and improve its quality. Once the primary sensor readings are filtered, transpiration dynamics such as: transpiration, stomatal conductance, leaf-air-temperature-difference and vapor pressure deficit are calculated in real time by the smart sensor. This permits the user to observe different primary and calculated measurements at the same time and the relationship between these which is very useful in precision agriculture in the detection of abnormal conditions. Finally, transpiration related stress conditions can be detected in real time because of the use of online processing and embedded communications capabilities.

Highlights

  • Plant transpiration is the process in which plants exchange moisture with the atmosphere [1]

  • The data acquisition systems, aforementioned computations, data communication and leaf chamber servomotor/vacuum pump control system are implemented in a field programmable gate array (FPGA) as an embedded smart sensor approach

  • It consists of the following stages: primary sensors, data acquisition system (DAS), FPGA-based digital signal processing (DSP), RAM memory to storage sensors measurements, RS232 data communication module, and leaf chamber mechanism control system

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Summary

Introduction

Plant transpiration is the process in which plants exchange moisture with the atmosphere [1]. VPD has been studied in greenhouse climate controller design in order to determine when RH is near to dew point to avoid excessive fogging and leaf condensation that leads to plant diseases [7] Those systems do not fuse their sensors data with other transpiration-related response variables such as ambient light and LATD nor do they have online in situ signal processing capabilities to make real-time decisions. It makes necessary the development of a real time transpiration dynamics intelligent sensor to early detect stress and disorder conditions The contribution of this project is to develop a smart sensor capable of estimating plant transpiration dynamic variables: E, Cleaf, LATD, and VPD, through the fusion of five primary low-cost sensors: two RH capacitive sensors, two Resistance Temperature Detector (RTD) sensors, one light quantum sensor, average atmospheric pressure data, and fixed volumetric air flow. The data acquisition systems, aforementioned computations, data communication and leaf chamber servomotor/vacuum pump control system are implemented in a field programmable gate array (FPGA) as an embedded smart sensor approach

Plant Transpiration Water-Atmosphere Scheme
Transpiration Process
Stomatal Conductance
Vapor Pressure Deficit
Smart Sensor Methodology
Transpiration Smart Sensing Cycle Methodology
Transpiration Methodology
Stomatal Conductance Estimation Methodology
Leaf-Air Temperature Difference Methodology
Experiment Setup
Primary Sensor Signal Improvement Results
Transpiration Results and Comparison
Fused Transpiration Dynamics Smart Sensing Results
Conclusions
Full Text
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