Yield projection using productive variables and various types of banana (Musa spp.) seed in Turbo-Colombia.
The productivity of banana cultivation is influenced by different physical, chemical and biological factors, which, in turn, vary between lots, farms and geographical areas; added to this the high climatic variability, high cost of inputs, decrease in labor and adjustment to the supply-demand of the...
| Main Authors: | , |
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| Format: | Online |
| Language: | spa |
| Published: |
Universidad Pedagógica y Tecnológica de Colombia
2022
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| Online Access: | https://revistas.uptc.edu.co/index.php/ciencia_agricultura/article/view/14706 |
| _version_ | 1801706483651444736 |
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| author | Bernal Monterrosa, Miguel Delgado Bejarano, Laura |
| author_facet | Bernal Monterrosa, Miguel Delgado Bejarano, Laura |
| author_sort | Bernal Monterrosa, Miguel |
| collection | OJS |
| description | The productivity of banana cultivation is influenced by different physical, chemical and biological factors, which, in turn, vary between lots, farms and geographical areas; added to this the high climatic variability, high cost of inputs, decrease in labor and adjustment to the supply-demand of the finished product forces the producer to optimize resources and carry out interventions to schedule harvests. The objective of this research was to make a performance projection, considering production variables. The study was carried out during the second half of 2021 and first quarter of 2022 in the department of Antioquia, municipality of Turbo, for the projection was taken into account seed type, weeks to harvest, cluster weight, population, return, collection and loss. Possible scenarios are presented with their respective interactions and performance response. The experimental design was in completely random blocks with 3 repetitions, the data were analyzed with R Studio 2022.02 software, non-parametric tests (Kruskal-Wallis; Yuen) and comparison of means with a post-analysisKruskal-Wallis with a 95% confidence level. Significant differences were found (P<9e-5), where the treatment of corm + pseudostem was the one that presented the best indicators with a number of weeks accumulated at harvest of 28.40±0.35 and a cluster weight of 24.3±0.19 kg. |
| format | Online |
| id | oai:oai.revistas.uptc.edu.co:article-14706 |
| institution | Revista Ciencia y Agricultura |
| language | spa |
| publishDate | 2022 |
| publisher | Universidad Pedagógica y Tecnológica de Colombia |
| record_format | ojs |
| spelling | oai:oai.revistas.uptc.edu.co:article-147062023-01-17T15:13:30Z Yield projection using productive variables and various types of banana (Musa spp.) seed in Turbo-Colombia. Proyección de rendimiento usando variables productivas y diversos tipos de semilla de banano (Musa spp.) en Turbo-Colombia. Bernal Monterrosa, Miguel Delgado Bejarano, Laura Musaceae Propagación Asexual Precocidad Cormo Productividad Musaceae Asexual Propagation Precocity Productivity Corm The productivity of banana cultivation is influenced by different physical, chemical and biological factors, which, in turn, vary between lots, farms and geographical areas; added to this the high climatic variability, high cost of inputs, decrease in labor and adjustment to the supply-demand of the finished product forces the producer to optimize resources and carry out interventions to schedule harvests. The objective of this research was to make a performance projection, considering production variables. The study was carried out during the second half of 2021 and first quarter of 2022 in the department of Antioquia, municipality of Turbo, for the projection was taken into account seed type, weeks to harvest, cluster weight, population, return, collection and loss. Possible scenarios are presented with their respective interactions and performance response. The experimental design was in completely random blocks with 3 repetitions, the data were analyzed with R Studio 2022.02 software, non-parametric tests (Kruskal-Wallis; Yuen) and comparison of means with a post-analysisKruskal-Wallis with a 95% confidence level. Significant differences were found (P<9e-5), where the treatment of corm + pseudostem was the one that presented the best indicators with a number of weeks accumulated at harvest of 28.40±0.35 and a cluster weight of 24.3±0.19 kg. La productividad del cultivo de banano está influenciada por diferentes factores físicos, químicos, biológicos, los cuales, a su vez, varían entre lotes, fincas y zonas geográficas; sumado a esto la alta variabilidad climática, alto costo de insumos, disminución en mano de obra y ajuste a la oferta-demanda del producto terminado obliga al productor a optimizar recursos y realizar intervenciones para programar las cosechas. El objetivo de esta investigación fue realizar una proyección de rendimiento, considerando variables de producción. El estudio se realizó durante el segundo semestre de 2021 y primer trimestre de 2022 en el departamento de Antioquia, municipio de Turbo, para la proyección se tuvo en cuenta tipo de semilla, semanas a cosecha, peso de racimos, población, retorno, recobro y merma. Se plantean posibles escenarios con sus respectivas interacciones y su respuesta en rendimiento. El diseño experimental fue en bloques completamente al azar con 3 repeticiones, los datos se analizaron con el software R Studio 2022.02, se realizaron pruebas no paramétricas (Kruskal-Wallis; Yuen) y comparación de medias con un análisis post-hoc de Kruskal-Wallis con un nivel de confianza del 95%. Se encontraron diferencias significativas (P<9e-5), donde el tratamiento de cormo + pseudotallo fue el que presento los mejores indicadores con un número de semanas acumuladas a cosecha de 28.40±0.35 y un peso de racimo de 24.3±0.19 kg. Universidad Pedagógica y Tecnológica de Colombia 2022-12-12 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion texto application/pdf https://revistas.uptc.edu.co/index.php/ciencia_agricultura/article/view/14706 10.19053/01228420.v19.n3.2022.14706 Ciencia y Agricultura; Vol. 19 No. 3 (2022): Septiembre-Diciembre Ciencia y Agricultura; Vol. 19 Núm. 3 (2022): Septiembre-Diciembre 2539-0899 spa https://revistas.uptc.edu.co/index.php/ciencia_agricultura/article/view/14706/12423 Copyright (c) 2022 Miguel Bernal Monterrosa http://creativecommons.org/licenses/by/4.0 |
| spellingShingle | Musaceae Propagación Asexual Precocidad Cormo Productividad Musaceae Asexual Propagation Precocity Productivity Corm Bernal Monterrosa, Miguel Delgado Bejarano, Laura Yield projection using productive variables and various types of banana (Musa spp.) seed in Turbo-Colombia. |
| title | Yield projection using productive variables and various types of banana (Musa spp.) seed in Turbo-Colombia. |
| title_alt | Proyección de rendimiento usando variables productivas y diversos tipos de semilla de banano (Musa spp.) en Turbo-Colombia. |
| title_full | Yield projection using productive variables and various types of banana (Musa spp.) seed in Turbo-Colombia. |
| title_fullStr | Yield projection using productive variables and various types of banana (Musa spp.) seed in Turbo-Colombia. |
| title_full_unstemmed | Yield projection using productive variables and various types of banana (Musa spp.) seed in Turbo-Colombia. |
| title_short | Yield projection using productive variables and various types of banana (Musa spp.) seed in Turbo-Colombia. |
| title_sort | yield projection using productive variables and various types of banana musa spp seed in turbo colombia |
| topic | Musaceae Propagación Asexual Precocidad Cormo Productividad Musaceae Asexual Propagation Precocity Productivity Corm |
| topic_facet | Musaceae Propagación Asexual Precocidad Cormo Productividad Musaceae Asexual Propagation Precocity Productivity Corm |
| url | https://revistas.uptc.edu.co/index.php/ciencia_agricultura/article/view/14706 |
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