Optimal placement of proximal sensors for precision irrigation in tree crops

Claudio Leones Bazzi, Kelyn Schenatto, Shrinivasa Upadhyaya, Francisco Rojo, Erin Kizer, Channing Ko-Madden

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


Soil water or plant water status-based precision irrigation has the potential to improve water productivity. In this study, the question of number as well as placement of proximal sensors called leaf monitors that provide plant water status information has been addressed, to assist in implementation of precision irrigation. To accomplish this task, an algorithm based on the Fuzzy C-Means logic that utilized spatial variability in soil and plant attributes was developed. First, stable soil properties such as soil texture, digital elevation and apparent soil electrical conductivity data were used to create management zones (MZ). Following the creation of MZ, stem water potential data from an almond orchard and a vineyard located in California were used to determine number as well as the placement location of sensors within each MZ. The methodology and algorithm developed successfully indicated the number of sensors that need to be used and the location of the trees where the sensors should be installed.

Original languageEnglish
Pages (from-to)663-674
Number of pages12
JournalPrecision Agriculture
Issue number4
StatePublished - 15 Aug 2019


  • Management zones
  • Optimal placement of sensors
  • Precision irrigation
  • Proximal sensors


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