Nutritional balance and its relationship to yield in a coffee field: Inferences from geospatial analysis

Abstract

Information obtained from studies of spatial variability and the Diagnosis and Recommendation Integrated System (DRIS) may contribute to understanding better the relationship between mineral nutrient balance and factors that limit the crop yield. This study shows that nutritionally balanced plants may be associated with low productivity in Conilon coffee fields. The study was carried out on a highly productive Conilon coffee (Coffea canephora) field, in São Mateus, state of Espírito Santo, Brazil. A sample grid was established with 100 points, each point linked to one plant. Twenty pairs of leaves from each plant were collected from productive branches to create a sample for nutritional analysis. The rust incidence (Hemileia vastatrix), the presence of the coffee borer (Hypothenemus hampei), and the physical characteristics of the soil were evaluated in each sampled plant. DRIS and Nutrient Balance Index (NBI) were calculated, and from the yield data, they were characterized using descriptive statistics. Maps were created showing the spatial distribution of the NBI, yield, total sand, and incidence of rust and coffee borer. It was verified the low relationship between nutritional balance and yield in Conilon coffee, suggesting that non-nutritional factors also influenced plant production. In areas of the maps with high NBI, the plant’s nutritional balance was the main limiting factor of production, since most plants in this area produced less than the average productivity of the plants sampled. The use of a geostatistics tool combined with the NBI resulted in better understanding of the relationship between nutritional and non-nutritional variables on the Conilon coffee yield.

Sistema Integrado de Diagnóstico y Recomendación, su aplicación y utilidad en la agricultura. Una Revisión

“…The combination of GIS with DRIS provides a better understanding of the interrelation of nutritional and non-nutritional variables on crop yield. In Brazil, these tools have identified the relationship of the incidence of rust (Hemileia vastatrix) and CBB (Hypothenemus hampei) with the NBI in terms of yield for Conilon coffee (Da Silva et al, 2020), along with the zoning of areas with a nutritional imbalance and low yield in adult Açaí palm plants (Oliveira et al, 2020). Meanwhile, in Colombia, the spatial distribution of NBI in the soil and leaf tissue of plants has led to the validation of Critical Levels and Sufficiency Ranges in oil palm (Herrera, 2015).…”

Diagnosis about the perspectives of precision applications of coffee growing technologies in municipalities of Bahia, Brazil

“…Geostatistical analysis allows spatially organizing data according to the similarity between georeferenced neighbors Alves, 2013). Geostatistics was used by Silva et al (2020) in experiments on nutritional balance and its relationship with productivity in a Conilon coffee farm in Espírito Santo state. The research used a sample grid of 100 points, each point liked to one plant.…”

“…The research used a sample grid of 100 points, each point liked to one plant. Silva et al (2020) evaluated that the use of a Geostatistics tools allied to the Nutricional Balance Index (NBI) resulted in a better understanding of the relationship between nutritional and non-nutritional variables in Conilon coffee productivity.…”

Continuous assessment of cowpea [Vigna unguiculata L. Walp.] nutritional status using diagnosis and recommendation integrated system approach

“…Therefore, soil portion explored by root, soil moisture, soil temperature, and aeration, and even the higher or lower absorption due to the own plant’s nutritional needs is not taken into account as factors in this method 8 . As soil fertility is its capacity to provide adequate nutrients for specified plants when other factors are favorable, tissue analysis is considered a more direct method of soil fertility evaluation than soil analysis 9 – 11 . Diagnosis and Recommendation Integrated System (DRIS) has emerged as one of the most accurate methods in detecting nutritional deficiencies and excesses as it accounts for the relationship among nutrients 11 , 12 .…”

“…As soil fertility is its capacity to provide adequate nutrients for specified plants when other factors are favorable, tissue analysis is considered a more direct method of soil fertility evaluation than soil analysis 9 – 11 . Diagnosis and Recommendation Integrated System (DRIS) has emerged as one of the most accurate methods in detecting nutritional deficiencies and excesses as it accounts for the relationship among nutrients 11 , 12 . DRIS is a bivariate approach developed by Beaufils 13 to interpret the results of leaf tissue analysis.…”