Assessment of soil variability and its effect on citrus production: a statistical approach

Kirandeep K. Mann, Arnold W. Schumann, Thomas A. Obreza

Abstract


Site-specifi c management of citrus groves based on major yield-limiting soil properties requires an understanding of relationships between citrus production and variable characteristics of soils. To explore these relationships, a 10-ha citrus grove with generally sandy soils was divided into fi ve productivity zones based on tree canopy volume in ArcView 3.2. These productivity zones were termed as “very poor,” “poor,” “medium,” “good”, and “very good.” Soil samples were collected from six locations from each productivity zone at four depths (0–15, 15–30, 30–45, and 45–60 cm). The relationships between citrus production and soil properties at the four cumulative depths were evaluated using various statistical methods including correlation, stepwise multiple linear regression, cluster analysis, discriminant function analysis, and partial least squares (PLS) regression. Soil organic matter, cation exchange capacity, Mehlich I-extractable P, oxalate-extractable Al, soil color, sand and water content at permanent wilting point contributed greatly to the variability in citrus production. Overall, the signifi cance of this contribution was higher at greater depths. The predictive models developed using PLS regression analysis explained 45% to 58%, and 54% to 71% variance for yield and canopy volume, respectively, and the percentage variance explained increased with the increased root zone depth. The yield from the poor areas of the grove was over-predicted when the variations in soil properties of the top 15-cm layer were used; however, a realistic prediction was observed when including the soil properties up to 60-cm depth. These predictive models can be used for site-specifi c management of the citrus groves with variable tree growth.


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Proc. Fla. State Hort. Soc.     ISSN 0886-7283