Classification of regions for greenhouse production using multivariate analysis
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protected agriculture
multivariate analysis estratificación
agricultura protegida
análisis multivariado

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Garza Alonso, C. A., Olivares Sáenz, E., Vázquez Alvarado, R. E., & García Treviño, N. E. (2020). Classification of regions for greenhouse production using multivariate analysis. Nova Scientia, 12(24).


Introduction: Protected agriculture has grown considerably in recent years. Temperature is a very important factor that must be considered in greenhouse crop production. The high and low temperatures influence the crops production. Therefore, the temperature is the main climate variable to select an area to install a greenhouse.

Method: Regions classification was carried out with data of 22 locations in the State of Nuevo Leon using two methodologies, one considering the mean monthly temperature external to the greenhouse and another method of classification using multivariate analysis. The criterion of classification using monthly temperatures was:  when average monthly external temperatures were below 15 °C it was classified as “cold month”; Temperatures in the range of 15 to 22 °C were classified as "optimal"; Temperatures in the range of 22 to 27 °C were classified as “hot” and temperatures above 27 °C were classified as ”very hot”. A stratification of the localities was also carried out using the multivariate model of cluster analysis with the height above sea level and the annual average temperature as variables. In addition, a correlation analysis was performed between the height average and monthly temperatures.

Results: Results showed that the methodology used allows to classify different regions according to the average monthly temperatures. Regarding the classification analysis using multivariate statistics, the k-means analysis for k = 4 identified four groups, of which the one and two belong to the high localities and the three and four groups to the lower localities. Considering both classification methods, it was concluded that the high region presents better probabilities of success for the greenhouse production and within this region, the lower asnm localities are more suitable and in the lower region the higher asnm localities are preferable. Considering the correlation analyzes of Pearson and Sperman, it was found that the asnm can be an indicator to define suitable regions to produce in the greenhouse.

Conclusion: The multivariate analysis of k-means to classify data sets according to a predetermined number of groups was an adequate strategy to classify regions to install greenhouses, together with other methodologies such as the one based on monthly average temperatures, which is described in the present publication.
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Benton, J. J. (2007). Tomato plant culture: In the field, greenhouse and home Garden. 2nd Edition CRC press Taylor and Francis Group. 420 p.

Castilla, N. (2004). Invernaderos de plástico: tecnología y manejo. Ediciones Mundi-Presa. Pp. 457.

Ferran-Aranaz, M. (2001). SPSS para Windows. Análisis Estadístico. McGraw Hill. Pp. 317-325.

Flores V., J., Mejía S., E., Montero C., J., Rojano, A. 2011. Análisis numérico del clima interior en un invernadero de tres naves con ventilación mecánica. Agrociencia, 45: 545-560.

González-Real, M. M. y A. Baille. (2000). Control del clima bajo invernadero. En Tecnología para cultivos de alto rendimiento. Ed. A. L. Alarcón. Novedades Agrícolas, S. A. Pp. 337-360.

INEGI. (2019). Mapa digital de México V.6.3.0. Instituto Nacional de Estadística y Geografía. Consultado el 15 de octubre de 2019.

Kawasaki, Y., A. Taketoyo, K. Suzuki, K. Yasuba, H. Kawashima, H. Sasaki, and M. Takaichi. (2010). Effect of local heating around the tomato shoot apex and flower clusters on plant surface temperature and characteristics related to fruit yield. Horticultural Research, 9(3): 345-350.

López-García, J. I. (2000). Control climático de invernaderos en el sudeste español. Aspectos prácticos. En Tecnología para cultivos de alto rendimiento. Ed. A. L. Alarcón. Novedades Agrícolas, S. A. Pp. 361-367.

Sánchez del Castillo, F. y Moreno P., E. C. (2017). Diseño agronómico y manejo de invernaderos. 1ª Ed. Universidad Autónoma Chapingo, México. 405 p.

Serrano C., Z. (2005). Construcción de invernaderos. 3ª Edición. Mundi-Prensa. España. 512 p.

SIAP (Servicio de Información Agroalimentaria y Pesquera) (2019). Producción Agrícola. Disponible en: Consultado el 15 de octubre de 2019.

SNIIM (Sistema Nacional de Información e Integración de Mercados (2019). Mercados Nacionales. Frutas y Hortalizas. Disponible en: Consultado el 15 de octubre de 2019.

Taiz L., E. Zeiger, I. A. Moller and A. Murphy. 2014. Plant physiology and development. 6th Ed. Oxford University Press. 761 p.

USDA (United States Department of Agriculture) (2019). Agricultural Marketing Service. Specialty Crops. Disponible en: Consultado el 15 de octubre de 2019.

Van Der Ploeg, A. and E. Heuvelink. (2005). Influence of sub-optimal temperature on tomato growth and yield: a Review. Journal of Horticultural Science and Biotechnology, 80(6): 652-659.

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