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.

摘要 空间变异性研究与诊断推荐综合系统（Diagnosis and Recommendation Integrated System, DRIS）所得信息，有助于深入理解矿质养分平衡与限制作物产量的因素之间的关联。本研究发现，Conilon咖啡田中营养平衡的植株可能与低生产力相关。研究于巴西圣埃斯皮里图州圣马特乌斯的一块高产Conilon咖啡（Coffea canephora）田开展。设置包含100个采样点的样方网格，每个点位对应单株咖啡植株。从每株植株的结果枝上采集20对叶片，制备用于营养分析的样品。对每株采样植株评估咖啡锈病（Hemileia vastatrix）发病率、咖啡果小蠹（Hypothenemus hampei）发生情况，以及土壤物理特性。计算DRIS与养分平衡指数（Nutrient Balance Index, NBI），结合产量数据通过描述性统计学方法进行表征。绘制了NBI、产量、总砂粒含量以及锈病和咖啡果小蠹发病率的空间分布地图。研究证实，Conilon咖啡的养分平衡与产量之间相关性较低，表明非养分因素同样会影响植株生产。在地图上NBI较高的区域，植株的养分平衡是生产的主要限制因子，因为该区域多数植株的产量低于采样植株的平均生产力。将地统计学工具与NBI结合使用，可更深入理解养分与非养分变量对Conilon咖啡产量的影响机制。