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Assessment of plant height is an important factor for agronomic and breeder decisions; however, current field phenotyping, such as visual scoring or using a ruler, is time consuming, labour intensive, costly and subjective. For agronomists and plant breeders, the most common method used to measure plant height is still a meter stick. In a 3-year study, we have adopted a herbometre similar to a rising plate meter as a reference method to obtain the weighted plant height of barley cultivars and to evaluate vehicle-based ultrasonic and laser distance sensors. Sets of 30 spring barley cultivars and 14 and 60 winter barley cultivars were tested in 2013, 2014 and 2015, respectively. The herbometre was well suited as a reference method allowing for an increased area and was easy to handle. The herbometre measurements within a plot showed very low coefficients of variation. Good and close relationships (R2 = 0.59, 0.76, 0.80) between the herbometre and the ultrasonic distance sensor measurements were observed in the years 2013, 2014 and 2015, respectively, demonstrating also increased values of heritability. Hence, both sensors were able to differentiate among barley cultivars in standard breeding trials. For the sensors, we observed a 4-fold faster operating time and 6-fold increase of measurement points compared with the herbometre measurement. Based on these results, we conclude that distance sensors represent a powerful and economical high-throughput phenotyping tool for breeders and plant scientists to estimate plant height and to differentiate cultivars for agronomic decisions and breeding activities potentially being also applicable in other small grain cereals with dense crop stands. Particularly, ultrasonic distance sensors may reflect an agronomically and physiologically relevant plant height information.

To optimize plant architecture (e.g., photosynthetic active leaf area, leaf-stem ratio), plant physiologists and plant breeders rely on destructively and tediously harvested biomass samples. A fast and non-destructive method for obtaining information about different plant organs could be vehicle-based spectral proximal sensing. In this 3-year study, the mobile phenotyping platform PhenoTrac 4 was used to compare the measurements from active and passive spectral proximal sensors of leaves, leaf sheaths, culms and ears of 34 spring barley cultivars at anthesis and dough ripeness. Published vegetation indices (VI), partial least square regression (PLSR) models and contour map analysis were compared to assess these traits. Contour maps are matrices consisting of coefficients of determination for all of the binary combinations of wavelengths and the biomass parameters. The PLSR models of leaves, leaf sheaths and culms showed strong correlations (R2 = 0.61–0.76). Published vegetation indices depicted similar coefficients of determination; however, their RMSEs were higher. No wavelength combination could be found by the contour map analysis to improve the results of the PLSR or published VIs. The best results were obtained for the dry weight and N uptake of leaves and culms. The PLSR models yielded satisfactory relationships for leaf sheaths at anthesis (R2 = 0.69), whereas only a low performance for all of sensors and methods was observed at dough ripeness. No relationships with ears were observed. Active and passive sensors performed comparably, with slight advantages observed for the passive spectrometer. The results indicate that tractor-based proximal sensing in combination with optimized spectral indices or PLSR models may represent a suitable tool for plant breeders to assess relevant morphological traits, allowing for a better understanding of plant architecture, which is closely linked to the physiological performance. Further validation of PLSR models is required in independent studies. Organ specific phenotyping represents a first step toward breeding by design.