Published

2014-01-01

Evaluation of various conventional methods for sampling weeds in potato and spinach crops

Evaluación de diferentes metodologías convencionales de muestreo de malezas en cultivos de papa y espinaca

DOI:

https://doi.org/10.15446/agron.colomb.v32n1.39613

Keywords:

vegetables, weed science, crop weed competition, cover, abundance, density (en)
hortalizas, malherbología, competencia de maleza-cultivo, cobertura, abundancia, densidad (es)

Authors

  • David Jamaica External Assessor
  • Guido Plaza Universidad Nacional de Colombia - Sede Bogotá - Faculty of Agricultural Sciences - Department of Agronomy
This study aimed to evaluate (at an exploratory level), some of the different conventional sampling designs in a section of a potato crop and in a commercial crop of spinach. Weeds were sampled in a 16 x 48 m section of a potato crop with a set grid of 192 sections. The cover and density of the weeds were registered in squares of from 0.25 to 64 m2. The results were used to create a database that allowed for the simulation of different sampling designs: variables and square size. A second sampling was carried out with these results in a spinach crop of 1.16 ha with a set grid of 6 x 6 m cells, evaluating the cover in 4 m2 squares. Another database was created with this information, which was used to simulate other sampling designs such as distribution and quantity of sampling squares. According to the obtained results, a good method for approximating the quantity of squares for diverse samples is 10-12 squares (4 m2) for richness per ha and 18 or more squares for abundance per hectare. This square size is optimal since it allows for a sampling of more area without losing sight of low-profile species, with the cover variable best representing the abundance of the weeds.

Este estudio tuvo como objetivo evaluar (a un nivel exploratorio), algunos de los diferentes diseños de muestreo convencionales en una sección de un cultivo de la papa, y en un cultivo comercial de espinacas. Se realizó un muestreo de malezas en una sección de 16 x 48 m de un cultivo de papa, en red rígida de 192 secciones, en las que se registró la cobertura y la densidad de malezas, en tamaños de cuadro desde 0,25 m2, hasta 64 m2, con esta información se conformó una base de datos que permitió simular diversos diseños de muestreo como: variables y tamaño de cuadro. Con estos resultados se realizó un segundo muestreo en un cultivo de 1,16 ha de espinaca, en la cual se estableció una red rígida de 6 x 6 m, evaluando la cobertura en cuadros de 4 m2. Con esta información se conformó otra base de datos con la cual se simularon otros diseños de muestreo como distribución y cantidad de cuadros muestreados. Según los resultados obtenidos, una buena forma de aproximarse a la cantidad de cuadros para los diversos muestreos es: 10-12 cuadros de 4 m2 por ha, para riqueza; 18 o más cuadros para abundancia. Este tamaño de cuadro resulta óptimo, debido a que permite muestrear más área sin perder de vista especies de porte bajo, siendo la cobertura la variable que mejor representa la abundancia de las malezas.

References

Barroso, J., D. Ruiz, C. Fernandez-Quintanilla, E.S. Leguizamon, P.J. Hernaiz, A. Ribeiro, B. Diaz, B.D. Maxwell, and L.J. Rew. 2005. Comparison of sampling methodologies for site-specific management of Avena sterilis. Weed Res. 45(3), 165-174.

Bautista Z., F. 2004. Técnicas de muestreo para manejadores de recursos naturales. Universidad Nacional Autónoma de México (UNAM), Mexico DF.

Booth, B., S. Murphy, and C. Swanton. 2003. Weed ecology in natural and agricultural systems. CAB International, Wallingford, UK.

Braun-Blanquet, J. and J.L.J. Oriol de Bolòs. 1979. Fitosociología. Bases para el estudio de las comunidades vegetales. H. Blume Ediciones, Madrid.

Clay, S. and G. Johnson. 2002. Scouting for weeds (on line). Crop Manage. 1(1).

Colbach, N., F. Dessaint, and F. Forcella. 2000. Evaluating field-scale sampling methods for the estimation of mean plant densities of weeds. Weed Res. 40(5), 411-430.

Cottam, G., J.T. Curtis, and A.J. Catana. 1957. Some sampling characteristics of a series of aggregated populations. Ecol. 38(4), 610-622.

Feyaerts, F. and L. Van Gool. 2001. Multi-spectral vision system for weed detection. Pattern Recogn. Lett. 22(6-7), 667-674.

Fuentes, C.L. 1986. Metodología y técnicas para evaluar las poblaciones de malezas y su efecto en los cultivos. Rev. Comalfi 13, 29-50.

Gold, H.J., J. Bay, and G.G. Wilkerson. 1996. Scouting for weeds, based on the negative binomial distribution. Weed Sci. 44, 504-510.

González-Andújar, J.L. and M. Saavedra. 2003. Spatial distribution of annual grass weed populations in winter cereals. Crop Prot. 22(4), 629-633.

Heijting, S., W. Van der Werf, A. Stein, and M.J. Kropff. 2007. Are weed patches stable in location? Application of an explicitly two-dimensional methodology. Weed Res. 47, 381-395.

Jurado-Expósito, M., F. Lopez-Granados, J.L. González-Andújar, and L. García-Torres. 2004. Spatial and temporal analysis of Convolvulus arvensis L. populations over four growing seasons. Eur. J. Agron. 21(3), 287-296.

LaMastus, F.E. and D.R. Shaw. 2005. Comparison of different sampling scales to estimate weed populations in three soybean fields. Precis. Agric. 6(3), 271-280.

Leguizamón, E.S. 2005. El manejo de malezas en el campo. Rev. Agromensajes 17, 26-29.

Marshall, E.J.P. 1988. Field-scale estimates of grass weed populations in arable land. Weed Res. 28(3), 191-198.

Matteucci, S.D. and A. Colma. 1982. Metodología para el estudio de la vegetación. Biology Series No. 22. The General Secretariat of the Organization of American States, Washington DC.

Mostacedo, B. and T.S. Fredericksen. 2000. Manual de métodos básicos de muestreo y análisis en ecología vegetal. Bolfor, Santa Cruz de la Sierra, Bolivia.

Okamoto, H., T. Murata, T. Kataoka, and S.I. Hata. 2007. Plant classification for weed detection using hyperspectral imaging with wavelet analysis. Weed Biol. Manage. 7(1), 31-37.

Rew, L.J. and R.D. Cousens. 2001. Spatial distribution of weeds in arable crops: are current sampling and analytical methods appropriate? Weed Res. 41(1), 1-18.

Sui, R., J.A. Thomasson, J. Hanks, and J. Wooten. 2008. Ground-based sensing system for weed mapping in cotton. Comput. Electron. Agric. 60(1), 31-38.

Wiles, L.J. 2005. Sampling to make maps for site-specific weed management. Weed Sci. 53(2), 228-235.

How to Cite

APA

Jamaica, D. and Plaza, G. (2014). Evaluation of various conventional methods for sampling weeds in potato and spinach crops. Agronomía Colombiana, 32(1), 36–43. https://doi.org/10.15446/agron.colomb.v32n1.39613

ACM

[1]
Jamaica, D. and Plaza, G. 2014. Evaluation of various conventional methods for sampling weeds in potato and spinach crops. Agronomía Colombiana. 32, 1 (Jan. 2014), 36–43. DOI:https://doi.org/10.15446/agron.colomb.v32n1.39613.

ACS

(1)
Jamaica, D.; Plaza, G. Evaluation of various conventional methods for sampling weeds in potato and spinach crops. Agron. Colomb. 2014, 32, 36-43.

ABNT

JAMAICA, D.; PLAZA, G. Evaluation of various conventional methods for sampling weeds in potato and spinach crops. Agronomía Colombiana, [S. l.], v. 32, n. 1, p. 36–43, 2014. DOI: 10.15446/agron.colomb.v32n1.39613. Disponível em: https://revistas.unal.edu.co/index.php/agrocol/article/view/39613. Acesso em: 14 jul. 2024.

Chicago

Jamaica, David, and Guido Plaza. 2014. “Evaluation of various conventional methods for sampling weeds in potato and spinach crops”. Agronomía Colombiana 32 (1):36-43. https://doi.org/10.15446/agron.colomb.v32n1.39613.

Harvard

Jamaica, D. and Plaza, G. (2014) “Evaluation of various conventional methods for sampling weeds in potato and spinach crops”, Agronomía Colombiana, 32(1), pp. 36–43. doi: 10.15446/agron.colomb.v32n1.39613.

IEEE

[1]
D. Jamaica and G. Plaza, “Evaluation of various conventional methods for sampling weeds in potato and spinach crops”, Agron. Colomb., vol. 32, no. 1, pp. 36–43, Jan. 2014.

MLA

Jamaica, D., and G. Plaza. “Evaluation of various conventional methods for sampling weeds in potato and spinach crops”. Agronomía Colombiana, vol. 32, no. 1, Jan. 2014, pp. 36-43, doi:10.15446/agron.colomb.v32n1.39613.

Turabian

Jamaica, David, and Guido Plaza. “Evaluation of various conventional methods for sampling weeds in potato and spinach crops”. Agronomía Colombiana 32, no. 1 (January 1, 2014): 36–43. Accessed July 14, 2024. https://revistas.unal.edu.co/index.php/agrocol/article/view/39613.

Vancouver

1.
Jamaica D, Plaza G. Evaluation of various conventional methods for sampling weeds in potato and spinach crops. Agron. Colomb. [Internet]. 2014 Jan. 1 [cited 2024 Jul. 14];32(1):36-43. Available from: https://revistas.unal.edu.co/index.php/agrocol/article/view/39613

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CrossRef citations2

1. Kavir Osorio, Andrés Puerto, Cesar Pedraza, David Jamaica, Leonardo Rodríguez. (2020). A Deep Learning Approach for Weed Detection in Lettuce Crops Using Multispectral Images. AgriEngineering, 2(3), p.471. https://doi.org/10.3390/agriengineering2030032.

2. Ramesh Nuthakki, S. G. Mangala Gowri, Satyasrikanth. (2024). Crop weed detection using artificial neural networks. INTERNATIONAL CONFERENCE ON EMERGING TRENDS IN ELECTRONICS AND COMMUNICATION ENGINEERING - 2023. INTERNATIONAL CONFERENCE ON EMERGING TRENDS IN ELECTRONICS AND COMMUNICATION ENGINEERING - 2023. 3028, p.030015. https://doi.org/10.1063/5.0212115.

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