Palabras clave
agricultura de precisión
tecnología de bajo costo
Cómo citar
Resumen
En la nota se muestra la experiencia de desarrollo de un dispositivo portátil de bajo costo, denominado Clorofilo, para la estimación relativa de clorofila en hojas de plantas mediante sensores de luz ambiental de teléfonos inteligentes. Este instrumento, basado en tecnologías abiertas y fabricación aditiva, demostró capacidad para diferenciar niveles relativos de clorofila, con potencial aplicación en agricultura de precisión. Aunque su funcionalidad inicial es prometedora, se identificaron desafíos asociados con la calibración, variabilidad de sensores, durabilidad y validación en campo. El dispositivo promueve la democratización tecnológica en contextos rurales y de bajos recursos, abriendo posibilidades para el monitoreo no destructivo del estado nutricional vegetal.
Citas
Carmona Rojas, L. M., Gutiérrez Rodríguez, E. A., Henao Ramirez, A. M., & Urrea Trujillo, A. I. (2022). Nutrition in cacao (Theobroma cacao L.) crops: What determining factors should be considered? Revista de La Facultad de Agronomía, 121(Especial 2), 101. https://doi.org/10.24215/16699513e10.
Khanal, S., Fulton, J., & Shearer, S. (2017). An overview of current and potential applications of thermal remote sensing in precision agriculture. Computers and Electronics in Agriculture, 139, 22–32. https://doi.org/10.1016/j.compag.2017.05.001.
Ospino Villalba, K. (2024). Desarrollo de sistemas instrumentales para el diagnóstico nutricional de plantas y suelos en campo. [online] Medellín, Colombia: Universidad Nacional de Colombia. [Acceso : 25 de mayo 2025]
Padilla, F. M., Gallardo, M., Peña-Fleitas, M. T., De Souza, R., & Thompson, R. B. (2018). Proximal optical sensors for nitrogen management of vegetable crops: A review. In Sensors (Switzerland) (Vol. 18, Issue 7). MDPI AG. https://doi.org/10.3390/s18072083.
Uddling, J., Gelang-Alfredsson, J., Piikki, K., & Pleijel, H. (2007). Evaluating the relationship between leaf chlorophyll concentration and SPAD-502 chlorophyll meter readings. Photosynthesis Research, 91(1), 37–46. https://doi.org/10.1007/s11120-006-9077-5.
Van Den Berg, A. K., & Perkins, T. D. (2004). Evaluation of a portable chlorophyll meter to estimate chlorophyll and nitrogen contents in sugar maple (Acer saccharum Marsh.) leaves. Forest Ecology and Management, 200(1–3), 113–117. https://doi.org/10.1016/j.foreco.2004.06.005.
Brown, L. A., Williams, O., & Dash, J. (2022). Calibration and characterisation of four chlorophyll meters and transmittance spectroscopy for non-destructive estimation of forest leaf chlorophyll concentration. Agricultural and Forest Meteorology, 323. https://doi.org/10.1016/j.agrformet.2022.109059.
Davis, P. A., Caylor, S., Whippo, C. W., & Hangarter, R. P. (2011). Changes in leaf optical properties associated with light-dependent chloroplast movements. Plant, Cell and Environment, 34(12), 2047–2059. https://doi.org/10.1111/j.1365-3040.2011.02402.x
Pavlovic, D., Nikolic, B., Djurovic, S., Waisi, H., Andjelkovic, A., & Marisavljevic, D. (2014). Chlorophyll as a measure of plant health: Agroecological aspects. Pestic. Phytomed., 29(1), 21–34. https://doi.org/10.2298/pif1401021p.
Tholen, D., Boom, C., Noguchi, K., Ueda, S., Katase, T., & Terashima, I. (2008). The chloroplast avoidance response decreases internal conductance to CO2 diffusion in Arabidopsis thaliana leaves. Plant, Cell and Environment, 31(11), 1688–1700. https://doi.org/10.1111/j.1365-3040.2008.01875.x.
Barnes, J. D., Balaguer, L., Manrique, E., Elvira, S., & Davison, A. W. (1992). A reappraisal of the use of DMSO for the extraction and determination of chlorophylls a and b in lichens and higher plants. Environmental and Experimental Botany, 32(2), 85–100. https://doi.org/10.1016/0098-8472(92)90034-Y.
Xiong, D., Chen, J., Yu, T., Gao, W., Ling, X., Li, Y., Peng, S., & Huang, J. (2015). SPAD-based leaf nitrogen estimation is impacted by environmental factors and crop leaf characteristics. Scientific Reports, 5, 1–12.
Suzuki, Y., & Shioi, Y. (1999). Detection of chlorophyll breakdown products in the senescent leaves of higher plants. In Plant Cell Physiol (Vol. 40, Issue 9). https://academic.oup.com/pcp/article/40/9/909/1940130.
Li, Y., He, N., Hou, J., Xu, L., Liu, C., Zhang, J., Wang, Q., Zhang, X., & Wu, X. (2018). Factors influencing leaf chlorophyll content in natural forests at the biome scale. Frontiers in Ecology and Evolution, 6 (6). https://doi.org/10.3389/fevo.2018.00064.
Kamarianakis, Z., & Panagiotakis, S. (2023). Design and Implementation of a Low-Cost Chlorophyll Content Meter. Sensors, 23(5). https://doi.org/10.3390/s23052699.
Adhikari, R., Li, C., Kalbaugh, K., & Nemali, K. (2020). A low-cost smartphone controlled sensor based on image analysis for estimating whole-plant tissue nitrogen (N) content in floriculture crops. Computers and Electronics in Agriculture, 169. https://doi.org/10.1016/j.compag.2019.105173.
Paleari, L., Movedi, E., Vesely, F. M., Invernizzi, M., Piva, D., Zibordi, G., & Confalonieri, R. (2022). Estimating plant nitrogen content in tomato using a smartphone. Field Crops Research, 284. https://doi.org/10.1016/j.fcr.2022.108564.
Martínez, D., & Guiamet, J. (2004). Distortion of the SPAD 502 chlorophyll meter readings by changes in irradiance and leaf water status. Italian Journal of Agronomy, 24(3), 41–46. https://doi.org/10.1051/agro.
Seong, W. M., Park, K. Y., Lee, M. H., Moon, S., Oh, K., Park, H., Lee, S., & Kang, K. (2018). Abnormal self-discharge in lithium-ion batteries. Energy and Environmental Science, 11(4), 970–978. https://doi.org/10.1039/c8ee00186c.
Camburn, B., Viswanathan, V., Linsey, J., Anderson, D., Jensen, D., Crawford, R., Otto, K., & Wood, K. (2017). Design prototyping methods: State of the art in strategies, techniques, and guidelines. Design Science, 3. https://doi.org/10.1017/dsj.2017.10.
Dong, T., Shang, J., Chen, J. M., Liu, J., Qian, B., Ma, B., Morrison, M. J., Zhang, C., Liu, Y., Shi, Y., Pan, H., & Zhou, G. (2019). Assessment of portable chlorophyll meters for measuring crop leaf chlorophyll concentration. Remote Sensing, 11(22). https://doi.org/10.3390/rs11222706.
Donnelly, A., Yu, R., Rehberg, C., Meyer, G., & Young, E. B. (2020). Leaf chlorophyll estimates of temperate deciduous shrubs during autumn senescence using a SPAD-502 meter and calibration with extracted chlorophyll. Annals of Forest Science, 77(2). https://doi.org/10.1007/s13595-020-00940-6.
Richardson, A. D., Duigan, S. P., & Berlyn, G. P. (2002). An evaluation of noninvasive methods to estimate foliar chlorophyll content. New Phytologist, 153(1), 185–194. https://doi.org/10.1046/j.0028-646X.2001.00289.x.
Markwell, J., Osterman, J. C., & Mitchell, J. L. (1995). Calibration of the Minolta SPAD-502 leaf chlorophyll meter. Photosynthesis Research, 46(3), 467–472. https://doi.org/10.1007/BF00032301.
Amigo, J. M., 2020. Hyperspectral and multispectral imaging: setting the scene. In Data Handling in Science and Technology (Vol. 32, pp. 3–16). Elsevier Ltd. https://doi.org/10.1016/B978-0-444-63977-6.00001-8.
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.