UAV remote sensing of spatial variation in banana production

Brian L. Machovina, Kenneth Feeley, Brett J. Machovina

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


Remote sensing through Unmanned Aerial Vehicles (UAV) can potentially be used to identify the factors influencing agricultural yield and thereby increase production efficiency. The use of UAV remains largely underutilised in tropical agricultural systems. In this study we tested a fixed-wing UAV system equipped with a sensor system for mapping spatial patterns of photosynthetic activity in banana plantations in Costa Rica. Spatial patterns derived from the Normalised Difference Vegetation Index (NDVI) were compared with spatial patterns of physical soil quality and banana fruit production data. We found spatial patterns of NDVI were significantly positively correlated with spatial patterns of several metrics of fruit yield and quality: bunch weight, number of hands per bunch, length of largest finger, and yield. NDVI was significantly negatively correlated with banana loss (discarded due to low quality). Spatial patterns of NDVI were not correlated with spatial patterns of physical soil quality. These results indicate that UAV systems can be used in banana plantations to help map patterns of fruit quality and yield, potentially aiding investigations of spatial patterns of underlying factors affecting production and thereby helping to increase agricultural efficiency.

Original languageEnglish (US)
Pages (from-to)1281-1287
Number of pages7
JournalCrop and Pasture Science
Issue number12
StatePublished - Jan 1 2016
Externally publishedYes


  • crop productivity
  • Musa
  • NDVI

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Plant Science


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