Diagnóstico nutrimental en limón persa con análisis estadístico por componentes principales

Se realizaron muestreos de suelo y foliar en 30 huertos de limón persa (Citrus latifolia Tanaka) en la zona productora de Nayarit, México en 2015. Por medio del análisis estadístico por componentes principales se agruparon 12 variables (en suelo: pH, MO, nitrógeno disponible anual, fósforo, potasio, calcio y magnesio; en tejido vegetal: nitrógeno, fósforo, potasio, calcio y magnesio). Los resultados indican que con excepción de nitrógeno en tejido vegetal (N tv), las variables se agruparon en dos componentes principales y representaron 86.73 % de la varianza. El primer componente correlacionó fuertemente con variables de carácter químico-orgánicas y el segundo con variables de tipo físico-químicas. Se observaron seis grupos con características similares en cuanto al estado nutrimental. Este método estadístico aporta una idea visual de las interacciones entre las variables y permite realizar acciones inmediatas conforme a las necesidades nutrimentales de cada huerto.

The objective of this study was to identify the interaction of organic matter (OM), pH, nutritional availability in soil and concentration in plant tissue of nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) in Persian lime (Citrus latifolia Tanaka) orchards, through the principal components method. Soil and leaf samples were collected in 30 Persian lemon orchards in the Mexican production area of Nayarit (Xalisco, Tepic, Santa Maria del Oro, and San Pedro Lagunillas municipalities), in 2015. A statistical analysis of main components was performed with 12 variables (soil pH, OM, nitrogen available annually, phosphorus, potassium, calcium and magnesium, plant tissue nitrogen, phosphorus, potassium, calcium and magnesium). The results indicate that, with exception of nitrogen in plant tissue (N tv), the variables were grouped into two components and represented 86.73% of the variance. The first component strongly correlated chemical-organic variables and the second component physical-chemical variables. Six groups with similar characteristics were observed regarding nutritional status. This statistical method provides a visual idea of the interactions between the variables and allows immediate actions according to the nutritional needs of each orchard.