4.7 Article

Obtaining and Validating High-Density Coffee Yield Data

Journal

HORTICULTURAE
Volume 8, Issue 5, Pages -

Publisher

MDPI
DOI: 10.3390/horticulturae8050421

Keywords

precision agriculture; coffee yield monitor; yield map validation; mechanical harvesting; coffee biennial cycle

Categories

Funding

  1. Terrena Agronegocios
  2. Coordination for the Improvement of Higher Education Personnel (in Portuguese: Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior-CAPES) [001]

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This study evaluates the quality of yield data obtained through a yield monitor onboard a coffee harvester and finds a high correlation with data collected using traditional measurement methods. Additionally, by collecting data over three consecutive seasons, the study identifies the internal variability of coffee yield and categorizes regions based on alternating yield patterns between years. The findings suggest that, in order to make effective management decisions, both spatial and biennial yield variability should be taken into account.
Coffee producers are ever more interested in understanding the dynamics of coffee's spatial and temporal variability. However, it is necessary to obtain high-density yield data for decision-making. The objective of this study is to evaluate the quality of yield data obtained through a yield monitor onboard a coffee harvester, as well as to evaluate the potential of the data collected over three harvests. The yield monitor validation data showed a high correlation (above R-2 0.968) when compared with the data obtained by a wagon instrumented with load cells. It was also possible to obtain yield maps for three consecutive seasons, allowing the identification of their internal variability, as well as classifying regions that show alternating yield patterns between years as the expression of the biennial yield behavior manifested inside and along the field, in addition to the spatial variability. This result indicates that, in addition to knowing the spatial yield variability, the biennial variance information must also be considered in the strategies for site-specific management. Regions that presented high yield variance should be alternated according to the productive year (high and low yield) and not only in consideration of their yield variability as on the regions with more stable yield behavior over time. The use of yield data can help the producer make more assertive decisions for crop and farm management.

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