Monitoring Sunflower and Maize Canopy Under Alternative Nitrogen Regimes with Lidar and Optical Sensors

Öz

Crop fertilization is an important part of cost and energy inputs in agriculture. The opportunity to apply the variable rate of nitrogen fertilizers according to the plant needs in each part of the field is a promising practice to increase the fertilizer use efficiency. An experiment was conducted in 2016 in the University of Thessaly farm, Central Greece in order to evaluate the use of lidar and optical sensors to monitor the crop canopy for sunflower and maize. The canopy development can serve as a good indicator for the nutrition state of the crops regarding especially the nitrogen, and it can be used as an indicator for variable rate application systems. In order to obtain plants with different canopy development, a field experiment was established with treatments receiving the normal, farmer’s practice, nitrogen rates (100%N) at basic fertilization, treatments receiving 50% reduced nitrogen fertilizer (50%N) and treatments with no nitrogen application (0%N). During growing, the crop canopy was monitored with a lidar and an optical sensor. Manual measurements of plant height and weight were also made. The manual measurements revealed the effect of variable fertilizer rates to plant development. The plots with higher nitrogen rates had higher and more vigor plants. The lidar sensor depicted more clearly these differences compared to the optical sensor. Plant height was sufficiently assessed for both the sunflower and maize crop by lidar. Plant volume though was assessed only for the sunflower. A problem with the lidar sensor was the small sampling rate (almost 2Hz) but this can be compensated by its ability to scan simultaneously more than one crop rows (4 to 6) and obtain multiple sample information.

Anahtar Kelimeler

• Canopy height
• crop monitoring
• lidar sensor
• precision fertilization

Kaynakça

1. Arnó, J., Escolà, A., Vallès, J.M., Sanz, R., Masip, J., Palacín, J. and Rosell, J.R. 2009. Use of a ground-based LIDAR scanner to measure leaf area and canopy structure variability of grapevines. 7th European Conference on Precision Agriculture, Wageningen, The Netherlands, pp.177-184.
2. Ehlert, D., Adamek, R. and Horn, H-J. 2009. Laser rangefinder-based measuring of crop biomass under field conditions. Precision Agriculture vol. 10, pp 395-408.
3. Escolà, A., Arnó, J., Sanz, R., Camp, F., Masip, J., Solanelles, F. and Rosell, J.R. 2009. Sensing tree canopy parameters in real time for precision fructiculture/horticulture applications: methodology set-up and first results. 7th European Conference on Precision Agriculture, Wageningen, The Netherlands, pp.185-191.
4. Gil, E., Escola, A., Rosell, J.,Planas S. and Vald, L. 2007. Variable rate application of plant protection products in vineyard using ultrasonic sensors. Crop Protection vol. 26, pp. 1287–1297
5. Llorens, J., Gil, E., Llop, J. and Queraltó, M. 2011. Georeferenced LiDAR 3D Vine Plantation Map Generation. Sensors, volume 11, pp. 6237-6256
6. Moorthy, I., Millera, J., Jimenez J., Zarco-Tejadac, P., Hub, B. and Chend, J. 2011. Field characterization of olive (Olea europaea L.) tree crown architecture using terrestrial laser scanning data. Agricultural and Forest Meteorology vol. 151, pp. 204–214.
7. Rosell, J.R., Llorens, J., Sanz, R., Arno΄, J., Ribes-Dasi, M., Masip, J., Escola`, A., Campc, F., Solanelles, F., Gracia, F., Gil, E., Val, L., Planas, S. and Palacin, J. 2009. Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial LIDAR scanning. Agricultural and Forest Meteorology, 149, pp. 1505-1515.
8. Swain, K.C., Zaman, Q.U.Z., Schumann A.W. and Percival, D.C. 2009. Detecting Weed and Bare-spot in Wild Blueberry Using Ultrasonic Sensor Technology. 2009 ASABE Annual International Meeting. Reno, Nevada, June 2009.

9. Tumbo, S. D., Salyani, M., Whitney, J., Wheaton T. and Miller W. 2002. Investigation of Laser and ultrasonic ranging sensots for measurements of citrus canopy volume. Applied Engineering in Agriculture. Vol. 18(3), pp. 367–372.
10. Zhang, L. and Grift, T. 2012. A LIDAR-based crop height measurement system for Miscanthus giganteus. Computers and Electronics in Agriculture vol. 85, pp. 70–76.