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Inici > English version > GRAP research > GRAP works > Electronic characterization of vegetation (phenotyping)

Electronic characterization of vegetation (phenotyping)

Geometry of tree crops

The structural aspects of a canopy are crucial both at individual tree level as for crops, forests and ecosystems. The space occupied by tree foliage determines the potential for resource capture and for exchanges with the atmosphere. Plant structure influences most biophysical processes, including, photosynthesis, growth, carbon-sequestration, and evapotranspiration. At the forest level, structure plays a key role in processes that involve exchanges of matter and energy between the atmosphere and terrestrial above-ground carbon reserves, and influences wildlife dynamics and fire propagation, among others.

In agriculture, information on the crops structural and geometric characteristics (height, width, volume, leaf area, etc.) has innumerable applications: irrigation, fertilization, application of pesticides, pruning techniques and crop training, among others. The knowledge of the geometrical characteristics of plantations allows optimization of these tasks, thereby reducing its economic and environmental impact.

In recent years, non-contact systems that allow characterizing the plantations in a non-destructive, rapid, accurate and repeatable way have emerged as an alternative to manual methods. The main systems used for the characterization of plants, are based on the use of electronic data acquisition systems associated with sensors based on different physical measuring principles. Apart from the ultrasonic sensors, most sensors used are based on the use of electromagnetic radiation in certain ranges or bands of spectrum (visible, infrared, etc.).

 


 

 

Our research group has deepened in the characterization of vegetation, both through ultrasonic sensors and by LiDAR systems. Both sensors base their operation on the measurement of the distance from a transmitter to an object or surface using pulses of sound waves or laser light, respectively, by measuring the time taken for the pulse to travel the distance from the point of emission to the detection point after bouncing off the object (ultrasonic sensors and time-of-flight LiDAR) or by measuring the phase difference between the incident and reflected waves (phase-shift LiDAR). The main drawbacks of the ultrasonic sensors are its poor spatial resolution, being their sonic cones highly divergent and the lack of scanning systems. In contrast, considering their speed, very high resolution and accuracy, LiDAR systems are becoming one of the sensors most used to characterize the vegetation. If, in addition, the data measured by these sensors are synchronized with those of their spatial coordinates, obtained by georeferencing systems (e.g. GPS), maps of the parameters of interest of the studied fields can be obtained: tree volumes, leaf area index (LAI), crop leaf density, etc.


   

 

Comparacio_volums_capçada

 




New detection systems increasingly accurate, robust and economically affordable have recently appeared on the market, which, in all probability, will encourage the development of the different areas of a sustainable and precision agriculture.

Vinya ETSEAExample of an experimental plot at the School of Agrifood and Forestry Science
and Engineering scanned with a high resolution georeferenced lidar system
.

Detection and classification of weeds

With the collaboration with the research group Ecología de Malas Hierbas del Departamento de Protección Vegetal del Instituto de Ciencias Agrarias del CSIC we have been working to develop a system based on ultrasonic and lidar sensors to detect weed between maize rows. Taking advantage of the ability of these sensors to estimate the distance to objects, it has been also possible to successfully classify the detected weeds into broadleaved weeds (dicot, shorter) or narrowleaved weeds (monocot, taller). Such system would allow the application of specific herbicides according to the type of weed detected.


US_weeds
Source: Weed research, 51 (6): 543-547; DOI: 10.1111/j.1365-3180.2011.00876.x
 

 

 

 

Last modified: 13/05/2015
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