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

• Autor(a) principal: Silva,Marcelo B. da
• Data de Publicação: 2020
• Outros Autores: Partelli,Fábio L., Gontijo,Ivoney, Caldas,Marcellus M.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista Brasileira de Engenharia Agrícola e Ambiental (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662020001200834
• topic: Coffea canephora; geostatistics; plant nutrition

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.