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Spatial variability of leaf macronutrient concentration and fruit production of an Arabica coffee plantation using two sampling densities

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Abstract

The nutritional and productive attributes of Arabica coffee (Coffea arabica L.) can vary spatially within cultivated areas. Precision farming techniques applied to coffee plantations can diagnose this spatial variability and propose solutions to correct this unevenness. The objective of this study was to characterize the distribution and spatial dependence of leaf macronutrient concentration and fruit production in an Arabica coffee plantation, in Barra do Choça, Bahia, northeastern Brazil, at two sampling densities. The concentrations of leaf macronutrients (N, P, K, Ca, Mg, and S) in 2019 and coffee production in the 2018/2019 and 2019/2020 agricultural years were evaluated at sampling densities of 2 and 5 points ha–1. The data were subjected to descriptive and geostatistical analyses. The results showed that the sampling density directly interferes in the identification of spatial dependence for the leaf macronutrient concentrations and fruit production in Arabica coffee plantations. While the sampling of 2 points ha−1 revealed a "weak" spatial dependence index for Mg and fruit production in the 2018/2019 agricultural year, in addition to the occurrence of a pure nugget effect for the other macronutrients and the 2019/2020 agricultural year, the sampling of 5 points ha−1 was able to identify "strong" spatial dependence for P, K, Ca, and Mg; "moderate" for N and fruit production in both agricultural year; and "weak" only for S. The analysis under higher sampling density revealed nutritional imbalance in the coffee plantation, with N deficiency in 44.8% and P defficiency in 36.1% of the sampling area. Adequate K, Ca, and Mg concentrations were indentified only in 40.2%, 35.4% and 45.5% of the area, respectively. These data showed that sampling density of 5 points ha−1 is more favorable for identifying patterns of dependence on leaf macronutrients and yield of Arabica coffee, favoring the mapping of its distribution and consequent identification of management zones. A positive spatial correlation was also found between the leaf concentration of some macronutrients and the fruit production of Arabica coffee at the highest sampling density.

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Data availability

Reasonable requests for the datasets from this study will be honored by the corresponding author.

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Acknowledgements

Thanks to the National Council for Scientific and Technological Development (CNPq) for providing an award for excellence in research to the third author.

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Authors and Affiliations

  1. Postgraduation Program in Agronomy (Crop Science), State University of Southwestern Bahia (UESB), Vitória da Conquista, Bahia, Brazil

    Gabriel Fernandes Pinto Ferreira

  2. Department of Agricultural Engineering and Soils, State University of Southwestern Bahia (UESB), Estrada do Bem Querer, km 04, Vitória da Conquista, Bahia, 45083-900, Brazil

    Odair Lacerda Lemos

  3. Department of Crop Science, College of Agricultural Sciences, São Paulo State University (UNESP), Av. Universitária, 3780, Lageado Experimental Farm, Botucatu, São Paulo, 18610-034, Brazil

    Rogério Peres Soratto

  4. São Paulo Agency of Agribusiness Technology (APTA/SAA), Midwest Regional/SAA, Av. Rodrigues Alves, 4040, Bauru, São Paulo, 17030-000, Brazil

    Marcos José Perdoná

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  1. Gabriel Fernandes Pinto Ferreira
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  2. Odair Lacerda Lemos
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Correspondence to Rogério Peres Soratto.

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Ferreira, G.F.P., Lemos, O.L., Soratto, R.P. et al. Spatial variability of leaf macronutrient concentration and fruit production of an Arabica coffee plantation using two sampling densities. Precision Agric 23, 1473–1488 (2022). https://doi.org/10.1007/s11119-022-09894-3

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