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PIETRO CATANIA

Application of a precision apiculture system to monitor honey daily production

  • Authors: Catania P.; Vallone M.
  • Publication year: 2020
  • Type: Articolo in rivista
  • Key words: Arduino; Beekeeping; Environment; Hive; Honey; Precision agriculture; Wind
  • OA Link: http://hdl.handle.net/10447/412247

Abstract

Precision beekeeping or precision apiculture is an apiary management strategy based on the monitoring of individual bee colonies to minimize resource consumption and maximize the productivity of bees. Bees play a fundamental role in ensuring pollination; they can also be considered as indicators of the state of pollution and are used as bio monitors. Beekeeping needs continuous monitoring of the animals and can benefit from advanced intelligent ambiance technologies. The aim of this study was the design of a precision apiculture system (PAS) platform for monitoring and controlling the following environmental parameters: wind, temperature, and relative humidity inside and outside the hive, in order to assess their influence on honey production. PAS is based on an Arduino board with an Atmel microcontroller, and the connection of a load cell for recording the weight of the hive, relative humidity and temperature sensor inside the hive, and relative humidity and temperature sensor outside the hive using an anemometer. PAS was installed in common hives and placed in an open field in a French honeysuckle plot; the system was developed to operate in continuous mode, monitoring the period of 24 April–1 June 2019. Temperature was constant in the monitored period, around 35◦ C, inside the hive, proving that no criticalities occurred regarding swarming or absconding. In the period between 24 and 28 May, a lack of honey production was recorded, attributed to a lowering of the external temperature. PAS was useful to point out the eventual reduction in honey production due to wind; several peaks of windiness exceeding 5 m s−1 were recorded, noting that honey production decreases with the peaks in wind. Therefore, the data recorded by PAS platform provided a valid decisional support to the operator. It can be implemented by inserting additional sensors for detecting other parameters, such as rain or sound.