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Agronomía Mesoamericana

On-line version ISSN 2215-3608Print version ISSN 1659-1321

Abstract

GARBANZO-LEON, Gabriel; VARGAS-ROJAS, Jorge Claudio  and  VEGA-VILLALOBOS, Edgar Vidal. Growth and nutrients uptake of dragon fruit (Hylocereus costaricensis and H. monocanthus) cultivated in Costa Rica. Agron. Mesoam [online]. 2024, vol.35, n.1, 57493. ISSN 2215-3608.  http://dx.doi.org/10.15517/am.2024.57493.

Introduction.

The cultivation of dragon fruit (Hylocereus costaricensis and H. monocanthus) is increasing in Costa Rica, but technical information for its management, such as nutritional requirements, fertilization timing, and growth behavior, is lacking. Objective. To quantify and model the growth and nutrient uptake of dragon fruit (H. costaricensis and H. monocanthus) under dry tropics conditions in Costa Rica. Materials and methods. The research was conducted from 2017 to 2020 in Guanacaste, Costa Rica. Plants were sampled at 76, 165, 308, 450, 607, 903, 1249, and 1706 days after planting (DAP) and 205 fruits were analyzed. Dry matter was quantified, and the uptake of N, P, Ca, Mg, K, S, Fe, Cu, Zn, Mn, and B was calculated. Two logistic models were fitted to determine nutrient uptake, and linear regressions were calibrated for fresh fruit. Results. For a planting density of 3000 plants/ha, the nutritional requirements per hectare were: 137 kg N, 32 kg P, 327 kg K, 63 kg Mg, 32 kg S, 1,60 kg Zn, and 0,21 kg B. The best-fitting logistic model (RMSE = 0.09) accurately estimated the uptake of N, P, Ca, S, Zn, and B. The linear regression model demonstrated high predictive capacity (R2 > 0.85) for the nutrient requirements of N, P, K, Mg, and S in the fruit. Conclusion. Logistic models provided high precision in deterministically modeling nutrient uptake in dragon fruit plants. The study affectively quantified and modeled the nutritional behavior of the plants under Costa Rica’s dry tropical conditions, providing essential information for optimizing fertilization programs for the crop.

Keywords : nutrient management; plant nutrition; deterministic models; biomass production.

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