Development of a multi-band sensor for crop temperature measurement

Abstract A system combining a miniature long wavelength infrared (LWIR) camera with a visible, or RGB, camera was developed to capture a field of view and derive a plant-specific temperature measurement. The electronic and software development of the instrument, including calibration, field operation, and post-processing of data, are described. Calibration of the LWIR camera was accurate to 0.65 °C when relating pixel output to a thermal measurement, allowing it to act as a thermal camera. A processing algorithm was developed to identify plants within a visible camera image using a binary mask to identify crop/non-crop components within the field of view. The mask was then used to obtain a crop-only region of interest from the thermal image, over which data were integrated to create a temperature measurement. The instrument was tested against an infrared thermometer on soybean plots during September and October 2016. It was capable of removing shaded areas and soil from thermal images to produce temperature measurements more representative of the crop canopy.

[1]  Thomas J. Trout,et al.  Estimating maize water stress by standard deviation of canopy temperature in thermal imagery , 2016 .

[2]  V. Alchanatis,et al.  Review: Sensing technologies for precision specialty crop production , 2010 .

[3]  Pablo J. Zarco-Tejada,et al.  Almond tree canopy temperature reveals intra-crown variability that is water stress-dependent , 2012 .

[4]  Yufeng Ge,et al.  Temporal dynamics of maize plant growth, water use, and leaf water content using automated high throughput RGB and hyperspectral imaging , 2016, Comput. Electron. Agric..

[5]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[6]  Yufeng Ge,et al.  A multi-sensor system for high throughput field phenotyping in soybean and wheat breeding , 2016, Comput. Electron. Agric..

[7]  Y. Cohen,et al.  Estimation of leaf water potential by thermal imagery and spatial analysis. , 2005, Journal of experimental botany.

[8]  Won Suk Lee,et al.  Immature green citrus fruit detection using color and thermal images , 2018, Comput. Electron. Agric..

[9]  H. Budzier,et al.  Calibration of uncooled thermal infrared cameras , 2015 .

[10]  S. Idso,et al.  Canopy temperature as a crop water stress indicator , 1981 .

[11]  J R Saylor,et al.  A method for the temperature calibration of an infrared camera using water as a radiative source. , 2009, The Review of scientific instruments.

[12]  J. Araus,et al.  Infrared Thermal Imaging as a Rapid Tool for Identifying Water-Stress Tolerant Maize Genotypes of Different Phenology , 2013 .

[13]  G. Meyer,et al.  Verification of color vegetation indices for automated crop imaging applications , 2008 .

[14]  J. A. Millen,et al.  CORN CANOPY TEMPERATURES MEASURED WITH A MOVING INFRARED THERMOMETER ARRAY , 2002 .

[15]  C. B. Tanner.  Plant Temperatures 1 , 1963 .

[16]  Edward Jones,et al.  A survey of image processing techniques for plant extraction and segmentation in the field , 2016, Comput. Electron. Agric..

[17]  C. B. Tanner,et al.  Infrared Thermometry of Vegetation1 , 1966 .

[18]  Martin A. Hebel,et al.  Original papers: Evaluation of a wireless infrared thermometer with a narrow field of view , 2011 .

[19]  E. Fereres,et al.  Improving the precision of irrigation in a pistachio farm using an unmanned airborne thermal system , 2014, Irrigation Science.

[20]  Y. Ge,et al.  Characterizing wheat response to water limitation using multispectral and thermal imaging. , 2017 .

[21]  Jeffrey W. White,et al.  Development and evaluation of a field-based high-throughput phenotyping platform. , 2013, Functional plant biology : FPB.

[22]  Xavier P. Burgos-Artizzu,et al.  utomatic segmentation of relevant textures in agricultural images , 2010 .

[23]  Y. Cohen,et al.  Use of thermal and visible imagery for estimating crop water status of irrigated grapevine. , 2006, Journal of experimental botany.

[24]  Stephan J. Maas,et al.  Scanned and spot measured canopy temperatures of cotton and corn , 2004 .

[25]  Ajay Sharda,et al.  Development and evaluation of thermal infrared imaging system for high spatial and temporal resolution crop water stress monitoring of corn within a greenhouse , 2016, Comput. Electron. Agric..