Digital imaging approaches for phenotyping whole plant nitrogen and phosphorus response in Brachypodium distachyon

Abstract

This work evaluates the phenotypic response of the model grass (Brachypodium distachyon (L.) P. Beauv.) to nitrogen and phosphorus nutrition using a combination of imaging techniques and destructive harvest of shoots and roots. Reference line Bd21-3 was grown in pots using 11 phosphorus and 11 nitrogen concentrations to establish a dose-response curve. Shoot biovolume and biomass, root length and biomass, and tissue phosphorus and nitrogen concentrations increased with nutrient concentration. Shoot biovolume, estimated by imaging, was highly correlated with dry weight (R(2) > 0.92) and both biovolume and growth rate responded strongly to nutrient availability. Higher nutrient supply increased nodal root length more than other root types. Photochemical efficiency was strongly reduced by low phosphorus concentrations as early as 1 week after germination, suggesting that this measurement may be suitable for high throughput screening of phosphorus response. In contrast, nitrogen concentration had little effect on photochemical efficiency. Changes in biovolume over time were used to compare growth rates of four accessions in response to nitrogen and phosphorus supply. We demonstrate that a time series image-based approach coupled with mathematical modeling provides higher resolution of genotypic response to nutrient supply than traditional destructive techniques and shows promise for high throughput screening and determination of genomic regions associated with superior nutrient use efficiency.

Integrating Image-Based Phenomics and Association Analysis to Dissect the Genetic Architecture of Temporal Salinity Responses in Rice

“…This approach simplifies phenotypic comparisons between individuals across multiple time points and can be used to accurately predict future outcomes. Time series data sets derived from image-based phenotyping have been combined with functional data analysis to examine shoot and root growth in response to various environmental conditions (Walter et al, 2002;van der Weele et al, 2003;Chen et al, 2014;Poiré et al, 2014;Bac-Molenaar et al, 2015). Functional data analysis can be combined with conventional genetic analysis such as linkage mapping and GWAS to identify loci that may be regulating dynamic processes (Cui et al, 2006;Wu and Lin, 2006;He et al, 2010;Das et al, 2011;Bac-Molenaar et al, 2015).…”

Utilization of Machine Vision to Monitor the Dynamic Responses of Rice Leaf Morphology and Colour to Nitrogen, Phosphorus, and Potassium Deficiencies

“…Relative growth rate (RGR) is an essential parameter to evaluate plant growth rate and is widely used in botany studies [22,23]. In this…”

“…By using nondestructive technology, a time series of plant images can be acquired to reveal phenotypic responses to environmental stress [22,23], such as the distinct responses of leaf morphology and colour to NPK deficiencies in this paper, helping us to further explore the mechanisms of plant growth.…”

“…Recently, continuous monitoring has been applied in numerous studies to study the phenotypic responses of plants to various environmental conditions [22][23][24]. Studies conducted by Poire et al [22], Neilson et al [23], and Yong-hui et al [25] reported the temporal dynamics of leaf morphology and colour during the leaf extension stage.…”

“…Studies conducted by Poire et al [22], Neilson et al [23], and Yong-hui et al [25] reported the temporal dynamics of leaf morphology and colour during the leaf extension stage. eir results also showed that different nutrient supplies resulted in various dynamic characteristics (such as the leaf extension rates and rates of colour change), which indicated that nutrient deficiency could be identified by dynamic characteristics at early stages.…”