Table 4.

New sensors and their application to plant macroscopic phenotyping.

Sensor technology	Measure	Applications	References
Sensitive cameras in the visible spectral range of the electromagnetic spectrum.	Produce raw data in the RGB or in the HSV (hue, saturation, value) spaces.	Shoot phenology and color.	Fiorani and Schurr, 2013; Araus and Cairns, 2014
Fluorescence cameras.	Analysis of fluorescence parameters.	Photosynthesis status.	Maxwell and Johnson, 2000; Berger et al., 2004; Bélanger et al., 2008; Chaerle et al., 2009; Fiorani et al., 2012; Fiorani and Schurr, 2013; Araus and Cairns, 2014
		Identification of biotic and abiotic stresses before visible phenotypes could be detected.
Thermal cameras.	Measure the leaf temperature.	Identification of abiotic (Fuentes et al., 2012; Mishra et al., 2012), and biotic (Calderón et al., 2014; Raza et al., 2015) stresses.	Review by (Fiorani and Schurr, 2013; Meron et al., 2013; Araus and Cairns, 2014; Calderón et al., 2014; Prashar and Jones, 2014)
		Evaluation of fruit maturity and bruise (Vadivambal and Jayas, 2011; Ishimwe et al., 2014).
Imaging spectroscopy.	Scanning specific wavebands of interest through high resolution cameras.	Water status by the analysis of the Near-Infrared (NIR) to the mid-infrared wavebands.	Fiorani and Schurr, 2013; Giovanelli et al., 2014
		Photosynthesis status by the analysis of the peak of green reflectance at 550 nm.
		Determination of nitrogen content and pigment composition (Fiorani and Schurr, 2013).
		Estimation of storage time for apple using NIR.
I-sensor.	Measurement of electrical impedance.	Estimation of cuticule and wax characteristics on vine berries and the link with disease resistance.	Herzog et al., 2015