Preliminary studies for modeling diploid potato crop
Las variedades de papa diploide (Solanum phureja Juz. et Buk.) se cultivan en diferentes regiones de América del Sur, principalmente en Colombia, Ecuador, Perú y Bolivia. Estas variedades se destacan por sus características organolépticas y nutricionales. Sin embargo, no se han realizado suficientes...
- Autores:
-
Saldaña Villota, Tatiana María
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2020
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/79548
- Palabra clave:
- 580 - Plantas
630 - Agricultura y tecnologías relacionadas::633 - Cultivos de campo y de plantación
Papa (Solanum phureja Juz. et Buk)
Potato
Radiation use efficiency
Leaf area index
Foliage cover
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional
| id |
UNACIONAL2_0df0657b9691a0fe18c8bfb73a87afdd |
|---|---|
| oai_identifier_str |
oai:repositorio.unal.edu.co:unal/79548 |
| network_acronym_str |
UNACIONAL2 |
| network_name_str |
Universidad Nacional de Colombia |
| repository_id_str |
|
| dc.title.eng.fl_str_mv |
Preliminary studies for modeling diploid potato crop |
| dc.title.translated.spa.fl_str_mv |
Estudios preliminares para la modelación de variedades de papa diploides |
| title |
Preliminary studies for modeling diploid potato crop |
| spellingShingle |
Preliminary studies for modeling diploid potato crop 580 - Plantas 630 - Agricultura y tecnologías relacionadas::633 - Cultivos de campo y de plantación Papa (Solanum phureja Juz. et Buk) Potato Radiation use efficiency Leaf area index Foliage cover |
| title_short |
Preliminary studies for modeling diploid potato crop |
| title_full |
Preliminary studies for modeling diploid potato crop |
| title_fullStr |
Preliminary studies for modeling diploid potato crop |
| title_full_unstemmed |
Preliminary studies for modeling diploid potato crop |
| title_sort |
Preliminary studies for modeling diploid potato crop |
| dc.creator.fl_str_mv |
Saldaña Villota, Tatiana María |
| dc.contributor.advisor.none.fl_str_mv |
Cotes Torres, José Miguel |
| dc.contributor.author.none.fl_str_mv |
Saldaña Villota, Tatiana María |
| dc.contributor.researchgroup.spa.fl_str_mv |
Mejoramiento y Producción de Especies Andinas y Tropicales |
| dc.subject.ddc.spa.fl_str_mv |
580 - Plantas 630 - Agricultura y tecnologías relacionadas::633 - Cultivos de campo y de plantación |
| topic |
580 - Plantas 630 - Agricultura y tecnologías relacionadas::633 - Cultivos de campo y de plantación Papa (Solanum phureja Juz. et Buk) Potato Radiation use efficiency Leaf area index Foliage cover |
| dc.subject.armarc.none.fl_str_mv |
Papa (Solanum phureja Juz. et Buk) |
| dc.subject.proposal.eng.fl_str_mv |
Potato Radiation use efficiency Leaf area index Foliage cover |
| description |
Las variedades de papa diploide (Solanum phureja Juz. et Buk.) se cultivan en diferentes regiones de América del Sur, principalmente en Colombia, Ecuador, Perú y Bolivia. Estas variedades se destacan por sus características organolépticas y nutricionales. Sin embargo, no se han realizado suficientes estudios para mejorar la comprensión de la dinámica de crecimiento y desarrollo de este cultivo y mejorar las condiciones agronómicas del mismo. Con el objetivo de mejorar el conocimiento sobre estas variedades y su uso en estudios de modelación de cultivos, en esta investigación se evaluó el modelo SUBSTOR-Potato, y aunque el modelo predice bien el crecimiento de los tubérculos, no logra simular variables relacionadas con la parte vegetativa. Este estudio explica que las dificultades de SUBSTOR-Potato para simular la parte vegetativa se deben a fallas en la estimación del índice de área foliar y del uso eficiente de la radiación (RUE) en cultivos de papa. Por lo tanto, esta investigación también se llevó a cabo con el objetivo de estimar la fracción de radiación solar interceptada a partir del porcentaje de cobertura de follaje mediante el uso de fotografías. También muestra cómo estimar el índice de área foliar a partir de la cobertura del follaje aplicando la ley de Beer-Lambert. La expectativa, es que este conocimiento pueda usarse para desarrollar un modelo de cultivo de papa diploide. Finalmente, de acuerdo con las características del crecimiento en diferentes momentos fenológicos y de la importancia del RUE para comprender la productividad del cultivo, este estudio también tuvo como objetivo estimar el RUE del cultivo de papa diploide involucrando no solo la biomasa total acumulada respecto a la cantidad de PAR interceptada, sino que también tomó en cuenta las pérdidas de carbohidratos por respiración. |
| publishDate |
2020 |
| dc.date.issued.none.fl_str_mv |
2020 |
| dc.date.accessioned.none.fl_str_mv |
2021-05-24T16:37:00Z |
| dc.date.available.none.fl_str_mv |
2021-05-24T16:37:00Z |
| dc.type.spa.fl_str_mv |
Trabajo de grado - Doctorado |
| dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
| dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
| dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_db06 |
| dc.type.content.spa.fl_str_mv |
Text |
| dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/TD |
| format |
http://purl.org/coar/resource_type/c_db06 |
| status_str |
acceptedVersion |
| dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/79548 |
| dc.identifier.instname.spa.fl_str_mv |
Universidad Nacional de Colombia |
| dc.identifier.reponame.spa.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
| dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.unal.edu.co/ |
| url |
https://repositorio.unal.edu.co/handle/unal/79548 https://repositorio.unal.edu.co/ |
| identifier_str_mv |
Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
| dc.language.iso.spa.fl_str_mv |
eng |
| language |
eng |
| dc.relation.references.spa.fl_str_mv |
Alamar, M. C., Tosetti, R., Landahl, S., Bermejo, A., & Terry, L. A. (2017). Assuring potato tuber quality during storage: A future perspective. Frontiers in Plant Science, 8(2034), 1–6. https://doi.org/10.3389/fpls.2017.02034 Alva, A. K., Marcos, J., Stockle, C., Reddy, V. R., & Timlin, D. (2010). A crop simulation model for predicting yield and fate of nitrogen in irrigated potato rotation cropping system. Journal of Crop Improvement, 24(2), 142–152. https://doi.org/10.1080/15427520903581239 Amthor, J. S. (1984). The role of maintenance respiration in plant growth. Plant, Cell and Environment, 7(8), 561–569. https://doi.org/10.1111/j.1365-3040.1984.tb01856.x Amthor, J. S. (2000). The McCree-de Wit-Penning de Vries-Thornley respiration paradigms: 30 Years later. Annals of Botany, 86(1), 1–20. https://doi.org/10.1006/anbo.2000.1175 Birch, P. R. J., Bryan, G., Fenton, B., Gilroy, E. M., Hein, I., Jones, J. T., Prashar, A., Taylor, M. A., Torrance, L., & Toth, I. K. (2012). Crops that feed the world 8: Potato: Are the trends of increased global production sustainable? In Food Security (Vol. 4, Issue 4). https://doi.org/10.1007/s12571-012-0220-1 Boogaard, H. L., & Kroes, J. G. (1998). Leaching of nitrogen and phosphorus from rural areas to surface waters in the Netherlands. Nutrient Cycling in Agroecosystems, 50(1–3), 321–324. https://doi.org/10.1007/978-94-017-3021-1_35 Bréda, N. (2003). Ground-based measurements of leaf area index: A review of methods, instruments and current controversies. Journal of Experimental Botany, 54(392), 2403–2417. https://doi.org/10.1093/jxb/erg263 Brown, H. E., Huth, N., & Holzworth, D. (2011). A potato model built using the APSIM Plant.net Framework. MODSIM 2011 - 19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty, 961–967. https://doi.org/10.36334/modsim.2011.b3.brown Bukasov, S. M. (1933). The potatoes of South America and their breeding possibilities. (According to data gathered by expeditions of the Institute of Plant Industry to Central and South America.). Bull. Appl. Bot, 58–192. Burgos, G., Salas, E., Amoros, W., Auqui, M., Muñoa, L., Kimura, M., & Bonierbale, M. (2009). Total and individual carotenoid profiles in Solanum phureja of cultivated potatoes: I. Concentrations and relationships as determined by spectrophotometry and HPLC. Journal of Food Composition and Analysis, 22(6), 503–508. https://doi.org/10.1016/j.jfca.2008.08.008 Cadena, M., Naranjo, A., & Ñústez, C. (2005). Evaluating the response of 60 Solanum phureja (Juz. et Buk.) genotypes to attacks by the Guatemalan moth (Tecia solanivora Povolny). Agronomía Colombiana, 23(1), 112–116. Campbell, G. S. (1986). Extinction coefficients for radiation in plant canopies calculated using an ellipsoidal inclination angle distribution. Agricultural and Forest Meteorology, 36(4), 317–321. https://doi.org/10.1016/0168-1923(86)90010-9 Campbell, G. S. (1990). Derivation of an angle density function for canopies with ellipsoidal leaf angle distributions. Agricultural and Forest Meteorology, 49, 173–176. Campbell, G. S., & van Evert, F. K. (1995). Light interception by plant canopies: Efficiency and architecture. In Resource Capture by Crops (pp. 35–52). University Press. Campillo, C., García, M. I., Daza, C., & Prieto, M. H. (2010). Study of a non-destructive method for estimating the leaf area index in vegetable crops using digital images. HortScience, 45(10), 1459–1463. Correll, D. (1962). Potato Its Wild Relatives (First Edit). Texas Research Foundation. De la Casa, A., Ovando, G., Bressanini, L., Martínez, J., & Ibarra, E. (2008). Leaf Area Index in Potato Estimate From Canopy Cover. Agronomía Trop., 58(1), 61–64. De la Casa, A., Ovando, G., Bressanini, L., Rodríguez, Á., & Martínez, J. (2007). Use of leaf area index and ground cover to estimate intercepted radiation in potato. Agricultura Técnica, 67(1), 78–85. Dobson, G., Griffiths, D. W., Davies, H. V., & McNicol, J. W. (2004). Comparison of fatty acid and polar lipid contents of tubers from two potato species, Solanum tuberosum and Solanum phureja. Journal of Agricultural and Food Chemistry, 52(20), 6306–6314. https://doi.org/10.1021/jf049692r Dodds, K. S., & Paxman, G. J. (1962). The Genetic System of Cultivated Diploid Potatoes. Evolution, 16(2), 154. https://doi.org/10.2307/2406194 El-Sharkawy, M. A. (2011). Overview: Early history of crop growth and photosynthesis modeling. BioSystems, 103(2), 205–211. https://doi.org/10.1016/j.biosystems.2010.08.004 Escallón, R., Ramirez, M., & Ñústez, C. E. (2005). Evaluating potential yield and resistance to Phytophthora infestans (Mont. de Bary) in the Solanum phureja (Juz. et Buk.) yellow potato collection. Agronomia Colombiana, 23(1), 35–41. Gayler, S., Wang, E., Priesack, E., Schaaf, T., & Maidl, F.-X. (2002). Modeling biomass growth, N-uptake and phenological development of potato crop. Geoderma, 105, 367–383. https://doi.org/10.1016/S0016-7061(01)00113-6 Gifford, R. M., Thorne, J. H., Hitz, W. D., & Giaquinta, R. T. (1984). Crop productivity and photoassimilate partitioning. Science, 225, 801–808. https://doi.org/10.1126/science.225.4664.801 Griffin, T. S., Johnson, B. S., & Ritchie, J. T. (1993). A simulation model for potato growth and development: SUBSTOR-Potato version 2.0. Department of Agronomy and Soil Science, College of Tropical Agriculture and Human Resources, University of Hawai, Honolulu. Soil Science, 32. Gutaker, R. M., Weiß, C. L., Ellis, D., Anglin, N. L., Knapp, S., Luis Fernández-Alonso, J., Prat, S., & Burbano, H. A. (2019). The origins and adaptation of European potatoes reconstructed from historical genomes. Nature Ecology and Evolution, 3(July). https://doi.org/10.1038/s41559-019-0921-3 Guzmán, M., & Rodríguez, P. (2010). Susceptibility of Solanum phureja (Juz. et Buk.) to potato yellow vein virus. Agronomía Colombiana, 28(2), 219–224. Hansen, S., Abrahamsen, P., Petersen, C. T., & Styczen, M. (2012). DAISY: Model, use, calibration and validation. Transactions of the ASABE, 55(4), 1315–1333. Hariharan, I. K., Wake, D. B., & Wake, M. H. (2016). Indeterminate growth: Could it represent the ancestral condition? Cold Spring Harbor Perspectives in Biology, 8(2), 1–17. https://doi.org/10.1101/cshperspect.a019174 Hatfield, J. (2014). Radiation use efficiency: Evaluation of cropping and management systems. Agronomy Journal, 106(5), 1820–1827. https://doi.org/10.2134/agronj2013.0310 Haverkort, A. J., Franke, A. C., Steyn, J. M., Pronk, A. A., Caldiz, D. O., & Kooman, P. L. (2015). A Robust Potato Model: LINTUL-Potato-DSS. Potato Research, 58(4), 313–327. https://doi.org/10.1007/s11540-015-9303-7 Haverkort, A. J., & Top, J. L. (2011). The potato ontology: Delimitation of the domain, modelling concepts, and prospects of performance. Potato Research, 54(2), 119–136. https://doi.org/10.1007/s11540-010-9184-8 Hawkes, J. G. (1956). Taxonomic studies on the tuber ‐ bearing Solanums. 1: Solanum tuberosum and the tetraploid species complex. Proceedings of the Linnean Society of London, 166(1–2), 97–144. https://doi.org/10.1111/j.1095-8312.1956.tb00754.x Hawkes, J. G. (1990). The Potato: Evolution, biodiversity and genetic resources. Smithsonian Institution Press. Hodges, T., Johnson, S. L., & Johnson, B. S. (1992). A Modular Structure for crop simulation models: Implemented in the SIMPOTATO model. Agronomy Journal, 84(5), 911–915. https://doi.org/10.2134/agronj1992.00021962008400050027x Hoogenboom, G., Porter, C. H., Boote, K. J., Shelia, V., Wilkens, P. W., Singh, U., White, J. W., Asseng, S., Lizaso, J. I., Moreno, L. P., Pavan, W., Ogoshi, R., Hunt, L. A., Tsuji, G. Y., & Jones, J. W. (2019). The DSSAT crop modeling ecosystem. In K. J. Boote (Ed.), Advances in Crop Modeling for a Sustainable Agriculture (pp. 173–216). Burleigh Dodds Science Publishing. Hoogenboom, G., Porter, C. H., Shelia, V., Boote, K. J., Singh, U., White, J. W., Hunt, L. A., Ogoshi, R., Lizaso, J. I., Koo, J., Asseng, S., Singels, A., Moreno, L. P., & Jones, J. W. (2018). Decision Support System for Agrotechnology Transfer (DSSAT). Version 4.7.2 (4.7.2). www.DSSAT.net Ingram, K. T., & McCloud, D. E. (1984). Simulation of Potato Crop Growth and Development 1. Crop Science, 24(1), 21–27. https://doi.org/10.2135/cropsci1984.0011183x002400010006x Jamieson, P. D., Zyskowski, R. F., Sinton, S. M., Brown, H. E., & Butler, R. C. (2006). Potato calculator: A tool for scheduling nitrogen fertiliser applications. Agronomy New Zealand, 36(July 2015), 49–53. Jennings, S. A., Koehler, A. K., Nicklin, K. J., Deva, C., Sait, S. M., & Challinor, A. J. (2020). Global Potato Yields Increase Under Climate Change With Adaptation and CO2 Fertilisation. Frontiers in Sustainable Food Systems, 4(December). https://doi.org/10.3389/fsufs.2020.519324 Jonckheere, I., Fleck, S., Nackaerts, K., Muys, B., Coppin, P., Weiss, M., & Baret, F. (2004). Review of methods for in situ leaf area index determination Part I. Theories, sensors and hemispherical photography. Agricultural and Forest Meteorology, 121, 19–35. https://doi.org/10.1016/j.agrformet.2003.08.027 Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., Wilkens, P. W., Singh, U., Gijsman, A. J., & Ritchie, J. T. (2003). The DSSAT cropping system model. European Journal of Agronomy, 18(3–4), 235–265. https://doi.org/10.1016/S1161-0301(02)00107-7 Kadaja, J., & Tooming, H. (2004). Potato production model based on principle of maximum plant productivity. Agricultural and Forest Meteorology, 127(1–2), 17–33. https://doi.org/10.1016/j.agrformet.2004.08.003 Lenz-Wiedemann, V. I. S., Klar, C. W., & Schneider, K. (2010). Development and test of a crop growth model for application within a Global Change decision support system. Ecological Modelling, 221(2), 314–329. https://doi.org/10.1016/j.ecolmodel.2009.10.014 Li, T., Hasegawa, T., Yin, X., Zhu, Y., Boote, K., Adam, M., Bregaglio, S., Buis, S., Confalonieri, R., Fumoto, T., Gaydon, D., Marcaida, M., Nakagawa, H., Oriol, P., Ruane, A. C., Ruget, F., Singh, B., Singh, U., Tang, L., … Bouman, B. (2015). Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions. Global Change Biology, 21(3), 1328–1341. https://doi.org/10.1111/gcb.12758 Ligarreto, G., & Suárez, M. (2003). Evaluation of the potential of genetics resources of creole potato (Solanum phureja) for industrial quality. Agronomía Colombiana, 21(1–3), 83–94. Luo, S., He, Y., Li, Q., Jiao, W., Zhu, Y., & Zhao, X. (2020). Nondestructive estimation of potato yield using relative variables derived from multi-period LAI and hyperspectral data based on weighted growth stage. Plant Methods, 16(1), 1–14. https://doi.org/10.1186/s13007-020-00693-3 Lutaladio, N., & Castaldi, L. (2009). Potato: The hidden treasure. Journal of Food Composition and Analysis, 22(6), 491–493. https://doi.org/10.1016/j.jfca.2009.05.002 Mann, J. E., Curry, G. L., DeMichele, D. W., & Baker, D. N. (1980). Light Penetration in a Row-Crop with Random Plant Spacing1. Agronomy Journal, 72(1), 131. https://doi.org/10.2134/agronj1980.00021962007200010026x Monsi, M., & Saeki, T. (1953). Über den Lichtfaktor in den Pflanzengesellschaften und seine Bedeutung für die Stoffproduktion. Jap. Journ. Bot., 14, 22–52. Monteith, J. L. (1977). Climate and the efficiency of crop production in Britain. Philosophical Transactions of the Royal Society B: Biological Sciences, 281, 277–294. https://doi.org/10.1098/rstb.1977.0140 Moslemkhani, K., Mozafari, J., Shams-Bakhsh, M., & Mohamadi, E. (2012). Expressions of some defense genes against Ralstonia Solanacearum in susceptible and resistant potato genotypes under in vitro conditions. Iran. J. Plant Path., 48(2), 57–60. Murchie, E. H., Townsend, A., & Reynolds, M. (2019). Crop Radiation Capture and Use Efficiency. In R. Savin & G. Slafer (Eds.), Crop Science (pp. 73–106). Springer. https://doi.org/10.1007/978-1-4939-8621-7 NIKON®. (2019). Capture NX-D Reference Manual (pp. 1–58). Ovchinnikova, A., Krylova, E., Gavrilenko, T., Smekalova, T., Zhuk, M., Knapp, S., & Spooner, D. M. (2011). Taxonomy of cultivated potatoes (Solanum section Petota: Solanaceae). Botanical Journal of the Linnean Society, 165(2), 107–155. https://doi.org/10.1111/j.1095-8339.2010.01107.x Patrignani, A., & Ochsner, T. E. (2015). Canopeo: A powerful new tool for measuring fractional green canopy cover. Agronomy Journal, 107(6), 2312–2320. https://doi.org/10.2134/agronj15.0150 Pregno, L. M., & Armour, J. D. (1992). Boron deficiency and toxicity in potato cv. Sebago on an Oxisol of the Atherton Tablelands, North Queensland. Australian Journal of Experimental Agriculture, 32(2), 251–253. https://doi.org/10.1071/EA9920251 R Core Team. (2020). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. https://www.r-project.org/ Raymundo, R., Kleinwechter, U., & Asseng, S. (2014). Virtual potato crop modeling: A comparison of genetic coefficients of the DSSAT-SUBSTOR potato model with breeding goals for developing countries. January, 1–15. https://doi.org/10.5281/zenodo.7687 Reddy, B., Mandal, R., Chakroborty, M., Hijam, L., & Dutta, P. (2018). A review on potato (Solanum tuberosum L.) and its genetic diversity. International Journal of Genetics, 10(2), 360–364. https://doi.org/10.9735/0975-2862.10.2.360-364 Ritchie, J. T., Griffin, T. S., & Johnson, B. S. (1995). SUBSTOR: Functional model of potato growth, development and yield. In P. Kabat, B. Marshall, B. J. van der Broek, J. Vos, & H. van Keulen (Eds.), Modelling and Parameterization of the Soil-Plant-Atmosphere System: A Comparison of Potato Growth Models (pp. 401–435). Wageningen Pers. Russell, G., Marshall, B., & Jarvis, P. . (1989). Plant canopies: their growth, form and function (G. Russell, B. Marshall, & P. G. Jarvis (eds.)). Cambridge University Press. Saqib, M., & Anjum, M. A. (2021). Applications of decision support system: A case study of solanaceous vegetables. Phyton - International Journal of Experimental Botany, 90(2), 331–352. https://doi.org/10.32604/phyton.2021.011685 Sinclair, T., & Muchow, R. (1999). Radiation Use Efficiency. Advances in Agronomy, 65, 215–265. https://doi.org/10.1016/s0065-2113(08)60914-1 Singh, J., Govindakrishnan, P., Lal, S., & Aggarwal, P. (2005). Increasing the efficiency of agronomy experiments in potato using INFOCROP-POTATO model. Potato Research, 48(3–4), 131–152. https://doi.org/10.1007/BF02742372 Sinoquet, H., & Andrieu, B. (1993). The geometrical structure of plant canopies : characterization and direct measurement methods. In Crop structure and light microclimate (Issue June, pp. 131–158). Spooner, D. M., Ghislain, M., Simon, R., Jansky, S. H., & Gavrilenko, T. (2014). Systematics, Diversity, Genetics, and Evolution of Wild and Cultivated Potatoes. Botanical Review, 80(4), 283–383. https://doi.org/10.1007/s12229-014-9146-y Steduto, P., Hsiao, T. C., Raes, D., & Fereres, E. (2009). Aquacrop-the FAO crop model to simulate yield response to water: I. concepts and underlying principles. Agronomy Journal, 101(3), 426–437. https://doi.org/10.2134/agronj2008.0139s Steven, M. D., Biscoe, P. V., Jaggard, K. W., & Paruntu, J. (1986). Foliage cover and radiation interception. Field Crops Research, 13(C), 75–87. https://doi.org/10.1016/0378-4290(86)90012-2 Stöckle, C. O., & Kemanian, A. R. (2009). Crop Radiation Capture and Use Efficiency. Crop Physiology, 145–170. https://doi.org/10.1016/b978-0-12-374431-9.00007-4 Sukhotu, T., & Hosaka, K. (2006). Origin and evolution of Andigena potatoes revealed by chloroplast and nuclear DNA markers. Genome, 49(6), 636–647. https://doi.org/10.1139/G06-014 Thornley, J. H. M. (2011). Plant growth and respiration re-visited: Maintenance respiration defined it is an emergent property of, not a separate process within, the system and why the respiration: Photosynthesis ratio is conservative. Annals of Botany, 108(7), 1365–1380. https://doi.org/10.1093/aob/mcr238 Urbanek, S. (2014). Package jpeg: Read and write JPEG images. 1–5. https://cran.r-project.org/package=jpeg Vose, J. M., Clinton, B. D., Sullivan, N. H., & Bolstad, P. V. (2008). Vertical leaf area distribution, light transmittance, and application of the Beer–Lambert Law in four mature hardwood stands in the southern Appalachians. Canadian Journal of Forest Research, 25(6), 1036–1043. https://doi.org/10.1139/x95-113 Wallach, D., Makowski, D., Jones, J. W., & Brun, F. (2019). Working with dynamic crop models. Methods, tools and examples for agroculture and environment (Third edit). Academic Press. https://doi.org/10.1016/c2011-0-06987-9 Watson, D. J. (1947). Comparative Physiological Studies on the Growth of Field Crops. I. Variation in net assimilation rate and leaf area between species and varieties, and within and between years. Annals of Applied Biology, 11(41), 41–76. https://doi.org/10.1111/j.1744-7348.1953.tb02364.x Webb, N., Wood, J., & Nicholl, C. (2008). User Manual for the SunScan Canopy Analysis System Delta-T Devices Ltd. White, J. W., Hoogenboom, G., Kimball, B. A., & Wall, G. W. (2011). Methodologies for simulating impacts of climate change on crop production. Field Crops Research, 124(3), 357–368. https://doi.org/10.1016/j.fcr.2011.07.001 Willmott, C. J., Ackleson, S. G., Davis, R. E., Feddema, J. J., Klink, K. M., Legates, D. R., O’donnell, J., & Rowe, C. M. (1985). Statistics for the evaluation and comparison of models. Journal of Geophysical Research, 90(5), 8995–9005. Wolf, J. (2002). Comparison of two potato simulation models under climate change. I. Model calibration and sensitivity analyses. Climate Research, 21, 173–186. Yamaguchi, J. (1978). Respiration and the growth efficiency in relation to crop productivity. J. Fac. Agric. Hokkaido Univ., 59, 59129. Yang, J., Greenwood, D. J., Rowell, D. L., Wadsworth, G. A., & Burns, I. G. (2000). Statistical methods for evaluating a crop nitrogen simulation model, N_ABLE. Agricultural Systems, 64(1), 37–53. https://doi.org/10.1016/S0308-521X(00)00010-X Zhao, C., Liu, B., Xiao, L., Hoogenboom, G., Boote, K. J., Kassie, B. T., Pavan, W., Shelia, V., Kim, K. S., Hernandez-Ochoa, I. M., Wallach, D., Porter, C. H., Stockle, C. O., Zhu, Y., & Asseng, S. (2019). A SIMPLE crop model. European Journal of Agronomy, 104(January), 97–106. https://doi.org/10.1016/j.eja.2019.01.009 |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
| dc.rights.license.spa.fl_str_mv |
Atribución-NoComercial-SinDerivadas 4.0 Internacional |
| dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
Atribución-NoComercial-SinDerivadas 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ http://purl.org/coar/access_right/c_abf2 |
| eu_rights_str_mv |
openAccess |
| dc.format.extent.spa.fl_str_mv |
46 páginas |
| dc.format.mimetype.spa.fl_str_mv |
application/pdf |
| dc.publisher.spa.fl_str_mv |
Universidad Nacional de Colombia - Sede Medellín |
| dc.publisher.program.spa.fl_str_mv |
Medellín - Ciencias Agrarias - Doctorado en Ciencias Agrarias |
| dc.publisher.department.spa.fl_str_mv |
Departamento de Agronómicas |
| dc.publisher.faculty.spa.fl_str_mv |
Facultad de Ciencias Agrarias |
| dc.publisher.place.spa.fl_str_mv |
Medellín |
| dc.publisher.branch.spa.fl_str_mv |
Universidad Nacional de Colombia - Sede Medellín |
| institution |
Universidad Nacional de Colombia |
| bitstream.url.fl_str_mv |
https://repositorio.unal.edu.co/bitstream/unal/79548/1/license.txt https://repositorio.unal.edu.co/bitstream/unal/79548/2/1085253669.2020.pdf https://repositorio.unal.edu.co/bitstream/unal/79548/3/license_rdf https://repositorio.unal.edu.co/bitstream/unal/79548/4/1085253669.2020.pdf.jpg |
| bitstream.checksum.fl_str_mv |
cccfe52f796b7c63423298c2d3365fc6 19fad1939d9eb2b34e1bc90f6d887c34 4460e5956bc1d1639be9ae6146a50347 8930b78be43c3ce9c45f22cecfec61ab |
| bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 |
| repository.name.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
| repository.mail.fl_str_mv |
repositorio_nal@unal.edu.co |
| _version_ |
1814090025057386496 |
| spelling |
Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Cotes Torres, José Miguel64e95e58ce3fb3bcdbb32a3161a0a44e600Saldaña Villota, Tatiana María9f256ae22fe8e58bd472d4fa648b73eaMejoramiento y Producción de Especies Andinas y Tropicales2021-05-24T16:37:00Z2021-05-24T16:37:00Z2020https://repositorio.unal.edu.co/handle/unal/79548Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/Las variedades de papa diploide (Solanum phureja Juz. et Buk.) se cultivan en diferentes regiones de América del Sur, principalmente en Colombia, Ecuador, Perú y Bolivia. Estas variedades se destacan por sus características organolépticas y nutricionales. Sin embargo, no se han realizado suficientes estudios para mejorar la comprensión de la dinámica de crecimiento y desarrollo de este cultivo y mejorar las condiciones agronómicas del mismo. Con el objetivo de mejorar el conocimiento sobre estas variedades y su uso en estudios de modelación de cultivos, en esta investigación se evaluó el modelo SUBSTOR-Potato, y aunque el modelo predice bien el crecimiento de los tubérculos, no logra simular variables relacionadas con la parte vegetativa. Este estudio explica que las dificultades de SUBSTOR-Potato para simular la parte vegetativa se deben a fallas en la estimación del índice de área foliar y del uso eficiente de la radiación (RUE) en cultivos de papa. Por lo tanto, esta investigación también se llevó a cabo con el objetivo de estimar la fracción de radiación solar interceptada a partir del porcentaje de cobertura de follaje mediante el uso de fotografías. También muestra cómo estimar el índice de área foliar a partir de la cobertura del follaje aplicando la ley de Beer-Lambert. La expectativa, es que este conocimiento pueda usarse para desarrollar un modelo de cultivo de papa diploide. Finalmente, de acuerdo con las características del crecimiento en diferentes momentos fenológicos y de la importancia del RUE para comprender la productividad del cultivo, este estudio también tuvo como objetivo estimar el RUE del cultivo de papa diploide involucrando no solo la biomasa total acumulada respecto a la cantidad de PAR interceptada, sino que también tomó en cuenta las pérdidas de carbohidratos por respiración.The diploid potato cultivars (Solanum phureja Juz. et Buk.) are grown in different South American regions, mainly in Colombia, Ecuador, Peru, and Bolivia. These cultivars stand out for their organoleptic and nutritional characteristics. However, not enough studies have been carried out to improve the understanding of this crop growth and development dynamics and improve its agronomic conditions. With the aim of increase knowledge about these cultivars and their use in crop modeling studies, in this research, the SUBSTORPotato model was evaluated. Although the model predicts well the tuber growth, it has some issues simulating variables related to the vegetative part. This study explains that the difficulties of SUBSTOR-Potato to simulate the vegetative part are due to failures in the estimation of the leaf area index and the radiation use efficiency (RUE) in potato crops. Therefore, this research was also carried out with the objective of estimating the fraction of intercepted solar radiation from the foliage cover by using photographs. It also shows how to estimate the leaf area index from the foliage cover applying the Beer-Lambert law. The expectation is that this knowledge can be used to develop a diploid potato crop model. Finally, according to the growth characteristics at different phenological moments and the importance of the RUE to understand the productivity of the crop, this study also aimed to estimate the RUE of the diploid potato crop involving not only the total biomass accumulated concerning the amount of PAR intercepted, but also took into account the carbohydrate losses per respiration.DoctoradoDoctora en Ciencias AgrariasFisiología de la Producción Vegetal46 páginasapplication/pdfengUniversidad Nacional de Colombia - Sede MedellínMedellín - Ciencias Agrarias - Doctorado en Ciencias AgrariasDepartamento de AgronómicasFacultad de Ciencias AgrariasMedellínUniversidad Nacional de Colombia - Sede Medellín580 - Plantas630 - Agricultura y tecnologías relacionadas::633 - Cultivos de campo y de plantaciónPapa (Solanum phureja Juz. et Buk)PotatoRadiation use efficiencyLeaf area indexFoliage coverPreliminary studies for modeling diploid potato cropEstudios preliminares para la modelación de variedades de papa diploidesTrabajo de grado - Doctoradoinfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_db06Texthttp://purl.org/redcol/resource_type/TDAlamar, M. C., Tosetti, R., Landahl, S., Bermejo, A., & Terry, L. A. (2017). Assuring potato tuber quality during storage: A future perspective. Frontiers in Plant Science, 8(2034), 1–6. https://doi.org/10.3389/fpls.2017.02034Alva, A. K., Marcos, J., Stockle, C., Reddy, V. R., & Timlin, D. (2010). A crop simulation model for predicting yield and fate of nitrogen in irrigated potato rotation cropping system. Journal of Crop Improvement, 24(2), 142–152. https://doi.org/10.1080/15427520903581239Amthor, J. S. (1984). The role of maintenance respiration in plant growth. Plant, Cell and Environment, 7(8), 561–569. https://doi.org/10.1111/j.1365-3040.1984.tb01856.xAmthor, J. S. (2000). The McCree-de Wit-Penning de Vries-Thornley respiration paradigms: 30 Years later. Annals of Botany, 86(1), 1–20. https://doi.org/10.1006/anbo.2000.1175Birch, P. R. J., Bryan, G., Fenton, B., Gilroy, E. M., Hein, I., Jones, J. T., Prashar, A., Taylor, M. A., Torrance, L., & Toth, I. K. (2012). Crops that feed the world 8: Potato: Are the trends of increased global production sustainable? In Food Security (Vol. 4, Issue 4). https://doi.org/10.1007/s12571-012-0220-1Boogaard, H. L., & Kroes, J. G. (1998). Leaching of nitrogen and phosphorus from rural areas to surface waters in the Netherlands. Nutrient Cycling in Agroecosystems, 50(1–3), 321–324. https://doi.org/10.1007/978-94-017-3021-1_35 Bréda, N. (2003). Ground-based measurements of leaf area index: A review of methods, instruments and current controversies. Journal of Experimental Botany, 54(392), 2403–2417. https://doi.org/10.1093/jxb/erg263Brown, H. E., Huth, N., & Holzworth, D. (2011). A potato model built using the APSIM Plant.net Framework. MODSIM 2011 - 19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty, 961–967. https://doi.org/10.36334/modsim.2011.b3.brownBukasov, S. M. (1933). The potatoes of South America and their breeding possibilities. (According to data gathered by expeditions of the Institute of Plant Industry to Central and South America.). Bull. Appl. Bot, 58–192.Burgos, G., Salas, E., Amoros, W., Auqui, M., Muñoa, L., Kimura, M., & Bonierbale, M. (2009). Total and individual carotenoid profiles in Solanum phureja of cultivated potatoes: I. Concentrations and relationships as determined by spectrophotometry and HPLC. Journal of Food Composition and Analysis, 22(6), 503–508. https://doi.org/10.1016/j.jfca.2008.08.008Cadena, M., Naranjo, A., & Ñústez, C. (2005). Evaluating the response of 60 Solanum phureja (Juz. et Buk.) genotypes to attacks by the Guatemalan moth (Tecia solanivora Povolny). Agronomía Colombiana, 23(1), 112–116.Campbell, G. S. (1986). Extinction coefficients for radiation in plant canopies calculated using an ellipsoidal inclination angle distribution. Agricultural and Forest Meteorology, 36(4), 317–321. https://doi.org/10.1016/0168-1923(86)90010-9Campbell, G. S. (1990). Derivation of an angle density function for canopies with ellipsoidal leaf angle distributions. Agricultural and Forest Meteorology, 49, 173–176.Campbell, G. S., & van Evert, F. K. (1995). Light interception by plant canopies: Efficiency and architecture. In Resource Capture by Crops (pp. 35–52). University Press.Campillo, C., García, M. I., Daza, C., & Prieto, M. H. (2010). Study of a non-destructive method for estimating the leaf area index in vegetable crops using digital images. HortScience, 45(10), 1459–1463.Correll, D. (1962). Potato Its Wild Relatives (First Edit). Texas Research Foundation.De la Casa, A., Ovando, G., Bressanini, L., Martínez, J., & Ibarra, E. (2008). Leaf Area Index in Potato Estimate From Canopy Cover. Agronomía Trop., 58(1), 61–64.De la Casa, A., Ovando, G., Bressanini, L., Rodríguez, Á., & Martínez, J. (2007). Use of leaf area index and ground cover to estimate intercepted radiation in potato. Agricultura Técnica, 67(1), 78–85.Dobson, G., Griffiths, D. W., Davies, H. V., & McNicol, J. W. (2004). Comparison of fatty acid and polar lipid contents of tubers from two potato species, Solanum tuberosum and Solanum phureja. Journal of Agricultural and Food Chemistry, 52(20), 6306–6314. https://doi.org/10.1021/jf049692rDodds, K. S., & Paxman, G. J. (1962). The Genetic System of Cultivated Diploid Potatoes. Evolution, 16(2), 154. https://doi.org/10.2307/2406194El-Sharkawy, M. A. (2011). Overview: Early history of crop growth and photosynthesis modeling. BioSystems, 103(2), 205–211. https://doi.org/10.1016/j.biosystems.2010.08.004Escallón, R., Ramirez, M., & Ñústez, C. E. (2005). Evaluating potential yield and resistance to Phytophthora infestans (Mont. de Bary) in the Solanum phureja (Juz. et Buk.) yellow potato collection. Agronomia Colombiana, 23(1), 35–41.Gayler, S., Wang, E., Priesack, E., Schaaf, T., & Maidl, F.-X. (2002). Modeling biomass growth, N-uptake and phenological development of potato crop. Geoderma, 105, 367–383. https://doi.org/10.1016/S0016-7061(01)00113-6Gifford, R. M., Thorne, J. H., Hitz, W. D., & Giaquinta, R. T. (1984). Crop productivity and photoassimilate partitioning. Science, 225, 801–808. https://doi.org/10.1126/science.225.4664.801Griffin, T. S., Johnson, B. S., & Ritchie, J. T. (1993). A simulation model for potato growth and development: SUBSTOR-Potato version 2.0. Department of Agronomy and Soil Science, College of Tropical Agriculture and Human Resources, University of Hawai, Honolulu. Soil Science, 32.Gutaker, R. M., Weiß, C. L., Ellis, D., Anglin, N. L., Knapp, S., Luis Fernández-Alonso, J., Prat, S., & Burbano, H. A. (2019). The origins and adaptation of European potatoes reconstructed from historical genomes. Nature Ecology and Evolution, 3(July). https://doi.org/10.1038/s41559-019-0921-3Guzmán, M., & Rodríguez, P. (2010). Susceptibility of Solanum phureja (Juz. et Buk.) to potato yellow vein virus. Agronomía Colombiana, 28(2), 219–224.Hansen, S., Abrahamsen, P., Petersen, C. T., & Styczen, M. (2012). DAISY: Model, use, calibration and validation. Transactions of the ASABE, 55(4), 1315–1333.Hariharan, I. K., Wake, D. B., & Wake, M. H. (2016). Indeterminate growth: Could it represent the ancestral condition? Cold Spring Harbor Perspectives in Biology, 8(2), 1–17. https://doi.org/10.1101/cshperspect.a019174Hatfield, J. (2014). Radiation use efficiency: Evaluation of cropping and management systems. Agronomy Journal, 106(5), 1820–1827. https://doi.org/10.2134/agronj2013.0310Haverkort, A. J., Franke, A. C., Steyn, J. M., Pronk, A. A., Caldiz, D. O., & Kooman, P. L. (2015). A Robust Potato Model: LINTUL-Potato-DSS. Potato Research, 58(4), 313–327. https://doi.org/10.1007/s11540-015-9303-7Haverkort, A. J., & Top, J. L. (2011). The potato ontology: Delimitation of the domain, modelling concepts, and prospects of performance. Potato Research, 54(2), 119–136. https://doi.org/10.1007/s11540-010-9184-8Hawkes, J. G. (1956). Taxonomic studies on the tuber ‐ bearing Solanums. 1: Solanum tuberosum and the tetraploid species complex. Proceedings of the Linnean Society of London, 166(1–2), 97–144. https://doi.org/10.1111/j.1095-8312.1956.tb00754.xHawkes, J. G. (1990). The Potato: Evolution, biodiversity and genetic resources. Smithsonian Institution Press.Hodges, T., Johnson, S. L., & Johnson, B. S. (1992). A Modular Structure for crop simulation models: Implemented in the SIMPOTATO model. Agronomy Journal, 84(5), 911–915. https://doi.org/10.2134/agronj1992.00021962008400050027xHoogenboom, G., Porter, C. H., Boote, K. J., Shelia, V., Wilkens, P. W., Singh, U., White, J. W., Asseng, S., Lizaso, J. I., Moreno, L. P., Pavan, W., Ogoshi, R., Hunt, L. A., Tsuji, G. Y., & Jones, J. W. (2019). The DSSAT crop modeling ecosystem. In K. J. Boote (Ed.), Advances in Crop Modeling for a Sustainable Agriculture (pp. 173–216). Burleigh Dodds Science Publishing.Hoogenboom, G., Porter, C. H., Shelia, V., Boote, K. J., Singh, U., White, J. W., Hunt, L. A., Ogoshi, R., Lizaso, J. I., Koo, J., Asseng, S., Singels, A., Moreno, L. P., & Jones, J. W. (2018). Decision Support System for Agrotechnology Transfer (DSSAT). Version 4.7.2 (4.7.2). www.DSSAT.netIngram, K. T., & McCloud, D. E. (1984). Simulation of Potato Crop Growth and Development 1. Crop Science, 24(1), 21–27. https://doi.org/10.2135/cropsci1984.0011183x002400010006xJamieson, P. D., Zyskowski, R. F., Sinton, S. M., Brown, H. E., & Butler, R. C. (2006). Potato calculator: A tool for scheduling nitrogen fertiliser applications. Agronomy New Zealand, 36(July 2015), 49–53.Jennings, S. A., Koehler, A. K., Nicklin, K. J., Deva, C., Sait, S. M., & Challinor, A. J. (2020). Global Potato Yields Increase Under Climate Change With Adaptation and CO2 Fertilisation. Frontiers in Sustainable Food Systems, 4(December). https://doi.org/10.3389/fsufs.2020.519324Jonckheere, I., Fleck, S., Nackaerts, K., Muys, B., Coppin, P., Weiss, M., & Baret, F. (2004). Review of methods for in situ leaf area index determination Part I. Theories, sensors and hemispherical photography. Agricultural and Forest Meteorology, 121, 19–35. https://doi.org/10.1016/j.agrformet.2003.08.027Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., Wilkens, P. W., Singh, U., Gijsman, A. J., & Ritchie, J. T. (2003). The DSSAT cropping system model. European Journal of Agronomy, 18(3–4), 235–265. https://doi.org/10.1016/S1161-0301(02)00107-7Kadaja, J., & Tooming, H. (2004). Potato production model based on principle of maximum plant productivity. Agricultural and Forest Meteorology, 127(1–2), 17–33. https://doi.org/10.1016/j.agrformet.2004.08.003Lenz-Wiedemann, V. I. S., Klar, C. W., & Schneider, K. (2010). Development and test of a crop growth model for application within a Global Change decision support system. Ecological Modelling, 221(2), 314–329. https://doi.org/10.1016/j.ecolmodel.2009.10.014Li, T., Hasegawa, T., Yin, X., Zhu, Y., Boote, K., Adam, M., Bregaglio, S., Buis, S., Confalonieri, R., Fumoto, T., Gaydon, D., Marcaida, M., Nakagawa, H., Oriol, P., Ruane, A. C., Ruget, F., Singh, B., Singh, U., Tang, L., … Bouman, B. (2015). Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions. Global Change Biology, 21(3), 1328–1341. https://doi.org/10.1111/gcb.12758Ligarreto, G., & Suárez, M. (2003). Evaluation of the potential of genetics resources of creole potato (Solanum phureja) for industrial quality. Agronomía Colombiana, 21(1–3), 83–94.Luo, S., He, Y., Li, Q., Jiao, W., Zhu, Y., & Zhao, X. (2020). Nondestructive estimation of potato yield using relative variables derived from multi-period LAI and hyperspectral data based on weighted growth stage. Plant Methods, 16(1), 1–14. https://doi.org/10.1186/s13007-020-00693-3Lutaladio, N., & Castaldi, L. (2009). Potato: The hidden treasure. Journal of Food Composition and Analysis, 22(6), 491–493. https://doi.org/10.1016/j.jfca.2009.05.002Mann, J. E., Curry, G. L., DeMichele, D. W., & Baker, D. N. (1980). Light Penetration in a Row-Crop with Random Plant Spacing1. Agronomy Journal, 72(1), 131. https://doi.org/10.2134/agronj1980.00021962007200010026xMonsi, M., & Saeki, T. (1953). Über den Lichtfaktor in den Pflanzengesellschaften und seine Bedeutung für die Stoffproduktion. Jap. Journ. Bot., 14, 22–52.Monteith, J. L. (1977). Climate and the efficiency of crop production in Britain. Philosophical Transactions of the Royal Society B: Biological Sciences, 281, 277–294. https://doi.org/10.1098/rstb.1977.0140Moslemkhani, K., Mozafari, J., Shams-Bakhsh, M., & Mohamadi, E. (2012). Expressions of some defense genes against Ralstonia Solanacearum in susceptible and resistant potato genotypes under in vitro conditions. Iran. J. Plant Path., 48(2), 57–60.Murchie, E. H., Townsend, A., & Reynolds, M. (2019). Crop Radiation Capture and Use Efficiency. In R. Savin & G. Slafer (Eds.), Crop Science (pp. 73–106). Springer. https://doi.org/10.1007/978-1-4939-8621-7NIKON®. (2019). Capture NX-D Reference Manual (pp. 1–58).Ovchinnikova, A., Krylova, E., Gavrilenko, T., Smekalova, T., Zhuk, M., Knapp, S., & Spooner, D. M. (2011). Taxonomy of cultivated potatoes (Solanum section Petota: Solanaceae). Botanical Journal of the Linnean Society, 165(2), 107–155. https://doi.org/10.1111/j.1095-8339.2010.01107.xPatrignani, A., & Ochsner, T. E. (2015). Canopeo: A powerful new tool for measuring fractional green canopy cover. Agronomy Journal, 107(6), 2312–2320. https://doi.org/10.2134/agronj15.0150Pregno, L. M., & Armour, J. D. (1992). Boron deficiency and toxicity in potato cv. Sebago on an Oxisol of the Atherton Tablelands, North Queensland. Australian Journal of Experimental Agriculture, 32(2), 251–253. https://doi.org/10.1071/EA9920251R Core Team. (2020). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. https://www.r-project.org/Raymundo, R., Kleinwechter, U., & Asseng, S. (2014). Virtual potato crop modeling: A comparison of genetic coefficients of the DSSAT-SUBSTOR potato model with breeding goals for developing countries. January, 1–15. https://doi.org/10.5281/zenodo.7687Reddy, B., Mandal, R., Chakroborty, M., Hijam, L., & Dutta, P. (2018). A review on potato (Solanum tuberosum L.) and its genetic diversity. International Journal of Genetics, 10(2), 360–364. https://doi.org/10.9735/0975-2862.10.2.360-364Ritchie, J. T., Griffin, T. S., & Johnson, B. S. (1995). SUBSTOR: Functional model of potato growth, development and yield. In P. Kabat, B. Marshall, B. J. van der Broek, J. Vos, & H. van Keulen (Eds.), Modelling and Parameterization of the Soil-Plant-Atmosphere System: A Comparison of Potato Growth Models (pp. 401–435). Wageningen Pers.Russell, G., Marshall, B., & Jarvis, P. . (1989). Plant canopies: their growth, form and function (G. Russell, B. Marshall, & P. G. Jarvis (eds.)). Cambridge University Press.Saqib, M., & Anjum, M. A. (2021). Applications of decision support system: A case study of solanaceous vegetables. Phyton - International Journal of Experimental Botany, 90(2), 331–352. https://doi.org/10.32604/phyton.2021.011685Sinclair, T., & Muchow, R. (1999). Radiation Use Efficiency. Advances in Agronomy, 65, 215–265. https://doi.org/10.1016/s0065-2113(08)60914-1Singh, J., Govindakrishnan, P., Lal, S., & Aggarwal, P. (2005). Increasing the efficiency of agronomy experiments in potato using INFOCROP-POTATO model. Potato Research, 48(3–4), 131–152. https://doi.org/10.1007/BF02742372Sinoquet, H., & Andrieu, B. (1993). The geometrical structure of plant canopies : characterization and direct measurement methods. In Crop structure and light microclimate (Issue June, pp. 131–158).Spooner, D. M., Ghislain, M., Simon, R., Jansky, S. H., & Gavrilenko, T. (2014). Systematics, Diversity, Genetics, and Evolution of Wild and Cultivated Potatoes. Botanical Review, 80(4), 283–383. https://doi.org/10.1007/s12229-014-9146-ySteduto, P., Hsiao, T. C., Raes, D., & Fereres, E. (2009). Aquacrop-the FAO crop model to simulate yield response to water: I. concepts and underlying principles. Agronomy Journal, 101(3), 426–437. https://doi.org/10.2134/agronj2008.0139sSteven, M. D., Biscoe, P. V., Jaggard, K. W., & Paruntu, J. (1986). Foliage cover and radiation interception. Field Crops Research, 13(C), 75–87. https://doi.org/10.1016/0378-4290(86)90012-2Stöckle, C. O., & Kemanian, A. R. (2009). Crop Radiation Capture and Use Efficiency. Crop Physiology, 145–170. https://doi.org/10.1016/b978-0-12-374431-9.00007-4Sukhotu, T., & Hosaka, K. (2006). Origin and evolution of Andigena potatoes revealed by chloroplast and nuclear DNA markers. Genome, 49(6), 636–647. https://doi.org/10.1139/G06-014Thornley, J. H. M. (2011). Plant growth and respiration re-visited: Maintenance respiration defined it is an emergent property of, not a separate process within, the system and why the respiration: Photosynthesis ratio is conservative. Annals of Botany, 108(7), 1365–1380. https://doi.org/10.1093/aob/mcr238Urbanek, S. (2014). Package jpeg: Read and write JPEG images. 1–5. https://cran.r-project.org/package=jpegVose, J. M., Clinton, B. D., Sullivan, N. H., & Bolstad, P. V. (2008). Vertical leaf area distribution, light transmittance, and application of the Beer–Lambert Law in four mature hardwood stands in the southern Appalachians. Canadian Journal of Forest Research, 25(6), 1036–1043. https://doi.org/10.1139/x95-113Wallach, D., Makowski, D., Jones, J. W., & Brun, F. (2019). Working with dynamic crop models. Methods, tools and examples for agroculture and environment (Third edit). Academic Press. https://doi.org/10.1016/c2011-0-06987-9Watson, D. J. (1947). Comparative Physiological Studies on the Growth of Field Crops. I. Variation in net assimilation rate and leaf area between species and varieties, and within and between years. Annals of Applied Biology, 11(41), 41–76. https://doi.org/10.1111/j.1744-7348.1953.tb02364.xWebb, N., Wood, J., & Nicholl, C. (2008). User Manual for the SunScan Canopy Analysis System Delta-T Devices Ltd.White, J. W., Hoogenboom, G., Kimball, B. A., & Wall, G. W. (2011). Methodologies for simulating impacts of climate change on crop production. Field Crops Research, 124(3), 357–368. https://doi.org/10.1016/j.fcr.2011.07.001Willmott, C. J., Ackleson, S. G., Davis, R. E., Feddema, J. J., Klink, K. M., Legates, D. R., O’donnell, J., & Rowe, C. M. (1985). Statistics for the evaluation and comparison of models. Journal of Geophysical Research, 90(5), 8995–9005.Wolf, J. (2002). Comparison of two potato simulation models under climate change. I. Model calibration and sensitivity analyses. Climate Research, 21, 173–186.Yamaguchi, J. (1978). Respiration and the growth efficiency in relation to crop productivity. J. Fac. Agric. Hokkaido Univ., 59, 59129.Yang, J., Greenwood, D. J., Rowell, D. L., Wadsworth, G. A., & Burns, I. G. (2000). Statistical methods for evaluating a crop nitrogen simulation model, N_ABLE. Agricultural Systems, 64(1), 37–53. https://doi.org/10.1016/S0308-521X(00)00010-XZhao, C., Liu, B., Xiao, L., Hoogenboom, G., Boote, K. J., Kassie, B. T., Pavan, W., Shelia, V., Kim, K. S., Hernandez-Ochoa, I. M., Wallach, D., Porter, C. H., Stockle, C. O., Zhu, Y., & Asseng, S. (2019). A SIMPLE crop model. European Journal of Agronomy, 104(January), 97–106. https://doi.org/10.1016/j.eja.2019.01.009LICENSElicense.txtlicense.txttext/plain; charset=utf-83964https://repositorio.unal.edu.co/bitstream/unal/79548/1/license.txtcccfe52f796b7c63423298c2d3365fc6MD51ORIGINAL1085253669.2020.pdf1085253669.2020.pdfTesis doctorado en Ciencias Agrariasapplication/pdf690922https://repositorio.unal.edu.co/bitstream/unal/79548/2/1085253669.2020.pdf19fad1939d9eb2b34e1bc90f6d887c34MD52CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://repositorio.unal.edu.co/bitstream/unal/79548/3/license_rdf4460e5956bc1d1639be9ae6146a50347MD53THUMBNAIL1085253669.2020.pdf.jpg1085253669.2020.pdf.jpgGenerated Thumbnailimage/jpeg4937https://repositorio.unal.edu.co/bitstream/unal/79548/4/1085253669.2020.pdf.jpg8930b78be43c3ce9c45f22cecfec61abMD54unal/79548oai:repositorio.unal.edu.co:unal/795482024-07-19 23:32:17.144Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.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 |