A spectroscopy-based detector to monitor tomato growth condition in greenhouse

Yang Ce, Li Minzan, Cui Di

Research output: Contribution to journalConference articlepeer-review

Abstract

A spectroscopy-based detector is developed to measure the nitrogen and chlorophyll content of tomato leaves and then to predict the growth condition of tomato plants in greenhouse. The detector uses two wavebands, 527 nm and 762 nm, since it is proved that these wavebands are sensitive to nitrogen and chlorophyll content in plant leaves by previous field test. The detector contains: A Y-type optic fiber, two silicon photocells, a signal processing unit, and a MCU. Light reflection from tomato leaves is transmitted by the Y-type optic fiber to the surface of the silicon photo cells, which transfer optical signal into electrical signal. Then the analog signal is amplified to conform to the TTL level signal standard and finally converted to digital signal by MAX186. After that, the MCU carries on a series of actions, including data calculating, displaying and storage. Using the measured data, the Normalized Difference Vegetation Index (NDVI) is calculated to estimate the nitrogen and chlorophyll content in plant leaves. The result is directly displayed on an LCD screen. Users have an option in saving data, either into a USB-memory stick or into a database over the PC serial port. The detector is portable, inexpensive, and convenient, which make it meet farmers' need in China. The performance test shows that the growth model works very well, and the device has high accuracy in predicting the growth condition of tomato plants in greenhouse.

Original languageEnglish (US)
Article number71571I
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume7157
DOIs
StatePublished - Mar 26 2009
Event2008 International Conference on Optical Instruments and Technology: Advanced Sensor Technologies and Applications - Beijing, China
Duration: Nov 16 2008Nov 19 2008

Keywords

  • Crop growth condition
  • Optical fiber
  • Optical sensor
  • Precision agriculture
  • Spectroscopy

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