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Crop improvement efforts are targeting increased above-ground biomass and radiation-use efficiency as drivers for greater yield. Early ground cover and canopy height contribute to biomass production, but manual measurements of these traits, and in particular above-ground biomass, are slow and labor-intensive, more so when made at multiple developmental stages. These constraints limit the ability to capture these data in a temporal fashion, hampering insights that could be gained from multi-dimensional data. Here we demonstrate the capacity of Light Detection and Ranging (LiDAR), mounted on a lightweight, mobile, ground-based platform, for rapid multi-temporal and non-destructive estimation of canopy height, ground cover and above-ground biomass. Field validation of LiDAR measurements is presented. For canopy height, strong relationships with LiDAR ( r 2 of 0.99 and root mean square error of 0.017 m) were obtained. Ground cover was estimated from LiDAR using two methodologies: red reflectance image and canopy height. In contrast to NDVI, LiDAR was not affected by saturation at high ground cover, and the comparison of both LiDAR methodologies showed strong association ( r 2 = 0.92 and slope = 1.02) at ground cover above 0.8. For above-ground biomass, a dedicated field experiment was performed with destructive biomass sampled eight times across different developmental stages. Two methodologies are presented for the estimation of biomass from LiDAR: 3D voxel index (3DVI) and 3D profile index (3DPI). The parameters involved in the calculation of 3DVI and 3DPI were optimized for each sample event from tillering to maturity, as well as generalized for any developmental stage. Individual sample point predictions were strong while predictions across all eight sample events, provided the strongest association with biomass ( r 2 = 0.93 and r 2 = 0.92) for 3DPI and 3DVI, respectively. Given these results, we believe that application of this system will provide new opportunities to deliver improved genotypes and agronomic interventions via more efficient and reliable phenotyping of these important traits in large experiments.

Stomata are the site of CO2 exchange for water in a leaf. Variation in stomatal control offers promise in genetic improvement of transpiration and photosynthetic rates to improve wheat performance. However, techniques for estimating stomatal conductance (SC) are slow, limiting potential for efficient measurement and genetic modification of this trait. Genotypic variation in canopy temperature (CT) and leaf porosity (LP), as surrogates for SC, were assessed in three wheat mapping populations grown under well-watered conditions. The range and resulting genetic variance were large but not always repeatable across days and years for CT and LP alike. Leaf-to-leaf variation was large for LP, reducing heritability to near zero on a single-leaf basis. Replication across dates and years increased line-mean heritability to ~75% for both CT and LP. Across sampling dates and populations, CT showed a large, additive genetic correlation with LP (rg=-0.67 to -0.83) as expected. Genetic increases in pre-flowering CT were associated with reduced final plant height and both increased harvest index and grain yield but were uncorrelated with aerial biomass. In contrast, post-flowering, cooler canopies were associated with greater aerial biomass and increased grain number and yield. A multi-environment QTL analysis identified up to 16 and 15 genomic regions for CT and LP, respectively, across all three populations. Several of the LP and CT QTL co-located with known QTL for plant height and phenological development and intervals for many of the CT and LP quantitative trait loci (QTL) overlapped, supporting a common genetic basis for the two traits. Notably, both Rht-B1b and Rht-D1b dwarfing alleles were paradoxically positive for LP and CT (i.e. semi-dwarfs had higher stomatal conductance but warmer canopies) highlighting the issue of translation from leaf to canopy in screening for greater transpiration. The strong requirement for repeated assessment of SC suggests the more rapid CT assessment may be of greater value for indirect screening of high or low SC among large numbers of early-generation breeding lines. However, account must be taken of variation in development and canopy architecture when interpreting performance and selecting breeding lines on the basis of CT.