DEVELOPMENT OF YIELD PREDICTION MODELS IN THE MAIZE CROP USING SPECTRAL DATA FOR PRECISION AGRICULTURE APPLICATIONS
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Publicado:
ago 30, 2015
Palabras clave:
aprendizaje automático; NDVI; sensoramiento proximal; sensoramiento remoto; regresión; machine learning; NDVI; proximal sensing; remote sensing; regression
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Resumen
Machine learning techniques were applied with statistical tools such as linear, logistic and multinomial regression, to work out predictive algorithms for yield estimation. Spectroradiometer readings were collected throughout the main maiz producing provinces of Ecuador, at two crop development stages.
A model using six degree polynomial regression is recommended for acceptable yield prediction. This model could contribute to decide about imports strategies and avoid the overlapping with the national production.
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Victor Rueda Ayala, Seshadri Kunapuli, Javier Maiguashca. DEVELOPMENT OF YIELD PREDICTION MODELS IN THE MAIZE CROP USING SPECTRAL DATA FOR PRECISION AGRICULTURE APPLICATIONS. EEC [Internet]. 30 de agosto de 2015 [citado 3 de diciembre de 2024];2(1). Disponible en: https://revistaecuadorescalidad.agrocalidad.gob.ec/revistaecuadorescalidad/index.php/revista/article/view/5
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C. Ferencz, P. Bognár, J. Lichtenberger, D. Hamar, G. Tarcsai, G. Timár, G. Molnár, S. Pásztor, P.
Steinbach, B. Székely, O. E. Ferencz, I. Ferencz-Árkos (2004) “Crop yield estimation by satellite remote sensing”, Int. J. Remote Sens. 25(20), 4113–4149.
R. R. V. Gonçalves, J. Z. Jr, L. A. S. Romani, C. R. Nascimento, A. J. M. Traina (2012) “Analysis of NDVI time series using cross-correlation and forecasting methods for monitoring sugarcane fields in Brazil”, Int. J. Remote Sens. 33(15), 4653–4672.
H. J. Heege, E. Thiessen (2013) “Sensing of Crop Properties”, In H. J. Heege, (Ed.) Precision in Crop Farming, 1 edn., pp. 103–141, Springer Netherlands.
INIAP (2014) “Instituto Nacional de Investigaciones Agropecuarias (National Institute of Agricultural
Research, Ecuador)”, Available online, Last accessed 14 November 2014.
M. Kalubarme, M. Hooda,R.S.and Yadav, G. Saroha (2006) “Spectral vegetation indices and its response to in-situ measured leaf area index of cotton”, In ISPRS, (Ed.) Symposium of ISPRS Commission IV, 25-30 September, Goa, India, vol. Volume XXXVI Part 4, pp. 1–6, International Society for Photogrammetry and Remote Sensing, ISPRS, Commission IV, Goa, India:ISPRS.
H. R. Matinfar (2013) “Modeling wheat yield estimation base upon spectral data and field
measurement, case study: Razan plain, Iran”, Technical Journal of Engineering and Applied Sciences 3(17), 2123–2130.
J. Moore, N. Holden (2003) “Examining the development of a potato crop nutrient management trial using reflectance sensing”, In ASAE, (Ed.) 2003 ASAE Annual Meeting, Paper number 031133, pp. 1–9, American Society of Agricultural and Biological Engineers (ASAE), St. Joseph, Michigan, USA: American Society of Agricultural and Biological Engineers.
R. R. Nemani, S. W. Running (1989) “Testing a theoretical climate-soil-leaf area hydrologic equilibrium of forests using satellite data and ecosystem simulation”, Agric. For. Meteorol. 44(3–4), 245–260.
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J. J. Rouse, R. Haas, J. Schell, D. Deering (1974) “Monitoring Vegetation Systems in the Great Plains with Erts”, In NASA Goddard Space Flight Center 3d ERTS-1 Symposium (1974), vol. 351, pp. 309–317.
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C. Wiegand, S. Maas, J. Aase, J. Hatfield, P. P. Jr., R. Jackson, E. Kanemasu, R. Lapitan (1992) “Multisite analyses of spectral-biophysical data for wheat”, Remote Sens. Environ. 42(1), 1–21.
Q. Xin, P. Gong, C. Yu, L. Yu, M. Broich, A. E. Suyker, R. B. Myneni (2013) “A Production Efficiency Model-Based Method for Satellite Estimates of Corn and Soybean Yields in the Midwestern US”, Rem. Sens. 5(11), 5926–5943.
C. Yang, J. Everitt, Q. Du, B. Luo, J. Chanussot (2013) “Using High-Resolution Airborne and Satellite Imagery to Assess Crop Growth and Yield Variability for Precision Agriculture”, Proceedings of the IEEE 101(3), 582–592.
C. Zadoks, T. Chang, F. Konzak (1974) “A decimal code for the growth stages of cereals”, Weed Res. 14(6), 415–421.
E. Zambrano, F. Hernández (2007) “Inicio, duración y término de la estación lluviosa en cinco localidades de la costa ecuatoriana”, Acta Oceanográfica del Pacífico 14(1), 7–11.
P. Zhang, B. Anderson, B. Tan, D. Huang, R. Myneni (2005) “Potential monitoring of crop production using a satellite-based Climate-Variability Impact Index”, Agric. For. Meteorol. 132(3–4), 344–358.
T. N. Carlson, D. A. Ripley (1997) “On the relation between NDVI, fractional vegetation cover, and leaf area index”, Remote Sens. Environ. 62(3), 241 – 252.
Climate-Data.org (2015) “Clima: Ecuador”, Available online, Last accessed 25 July 2015.
Ecuavisa (2012) “Noticias: Desperdicio de maíz destapa corrupción en Ministerio de Agricultura (News: Wasting of maize production uncovers corruption inside the Ministry of Agriculture)”, Available online, Last accessed 16 March 2015.
J. C. D. M. Esquerdo, J. Z. Júnior, J. F. G. Antunes (2011) “Use of NDVI/AVHRR time-series profiles for soybean crop monitoring in Brazil”, Int. J. Remote Sens. 32(13), 3711–3727.
C. Ferencz, P. Bognár, J. Lichtenberger, D. Hamar, G. Tarcsai, G. Timár, G. Molnár, S. Pásztor, P.
Steinbach, B. Székely, O. E. Ferencz, I. Ferencz-Árkos (2004) “Crop yield estimation by satellite remote sensing”, Int. J. Remote Sens. 25(20), 4113–4149.
R. R. V. Gonçalves, J. Z. Jr, L. A. S. Romani, C. R. Nascimento, A. J. M. Traina (2012) “Analysis of NDVI time series using cross-correlation and forecasting methods for monitoring sugarcane fields in Brazil”, Int. J. Remote Sens. 33(15), 4653–4672.
H. J. Heege, E. Thiessen (2013) “Sensing of Crop Properties”, In H. J. Heege, (Ed.) Precision in Crop Farming, 1 edn., pp. 103–141, Springer Netherlands.
INIAP (2014) “Instituto Nacional de Investigaciones Agropecuarias (National Institute of Agricultural
Research, Ecuador)”, Available online, Last accessed 14 November 2014.
M. Kalubarme, M. Hooda,R.S.and Yadav, G. Saroha (2006) “Spectral vegetation indices and its response to in-situ measured leaf area index of cotton”, In ISPRS, (Ed.) Symposium of ISPRS Commission IV, 25-30 September, Goa, India, vol. Volume XXXVI Part 4, pp. 1–6, International Society for Photogrammetry and Remote Sensing, ISPRS, Commission IV, Goa, India:ISPRS.
H. R. Matinfar (2013) “Modeling wheat yield estimation base upon spectral data and field
measurement, case study: Razan plain, Iran”, Technical Journal of Engineering and Applied Sciences 3(17), 2123–2130.
J. Moore, N. Holden (2003) “Examining the development of a potato crop nutrient management trial using reflectance sensing”, In ASAE, (Ed.) 2003 ASAE Annual Meeting, Paper number 031133, pp. 1–9, American Society of Agricultural and Biological Engineers (ASAE), St. Joseph, Michigan, USA: American Society of Agricultural and Biological Engineers.
R. R. Nemani, S. W. Running (1989) “Testing a theoretical climate-soil-leaf area hydrologic equilibrium of forests using satellite data and ecosystem simulation”, Agric. For. Meteorol. 44(3–4), 245–260.
N. Noureldin, M. Aboelghar, H. Saudy, A. Ali (2013) “Rice yield forecasting models using satellite imagery in Egypt”, Egyptian Journal of Remote Sensing and Space Science 16(1), 125–131.
J. J. Rouse, R. Haas, J. Schell, D. Deering (1974) “Monitoring Vegetation Systems in the Great Plains with Erts”, In NASA Goddard Space Flight Center 3d ERTS-1 Symposium (1974), vol. 351, pp. 309–317.
T. P. Ryan (2013) Sample size determination and power, Wiley Series in Probability and Statistics, Hoboken, New Jersey, USA.: John Wiley & Sons, Inc., 1–404 pp.
C. Wiegand, S. Maas, J. Aase, J. Hatfield, P. P. Jr., R. Jackson, E. Kanemasu, R. Lapitan (1992) “Multisite analyses of spectral-biophysical data for wheat”, Remote Sens. Environ. 42(1), 1–21.
Q. Xin, P. Gong, C. Yu, L. Yu, M. Broich, A. E. Suyker, R. B. Myneni (2013) “A Production Efficiency Model-Based Method for Satellite Estimates of Corn and Soybean Yields in the Midwestern US”, Rem. Sens. 5(11), 5926–5943.
C. Yang, J. Everitt, Q. Du, B. Luo, J. Chanussot (2013) “Using High-Resolution Airborne and Satellite Imagery to Assess Crop Growth and Yield Variability for Precision Agriculture”, Proceedings of the IEEE 101(3), 582–592.
C. Zadoks, T. Chang, F. Konzak (1974) “A decimal code for the growth stages of cereals”, Weed Res. 14(6), 415–421.
E. Zambrano, F. Hernández (2007) “Inicio, duración y término de la estación lluviosa en cinco localidades de la costa ecuatoriana”, Acta Oceanográfica del Pacífico 14(1), 7–11.
P. Zhang, B. Anderson, B. Tan, D. Huang, R. Myneni (2005) “Potential monitoring of crop production using a satellite-based Climate-Variability Impact Index”, Agric. For. Meteorol. 132(3–4), 344–358.