Novel Digital Features Discriminate Between Drought Resistant and Drought Sensitive Rice Under Controlled and Field Conditions

Abstract

Dynamic quantification of drought response is a key issue both for variety selection and for functional genetic study of rice drought resistance. Traditional assessment of drought resistance traits, such as stay-green and leaf-rolling, has utilized manual measurements, that are often subjective, error-prone, poorly quantified and time consuming. To relieve this phenotyping bottleneck, we demonstrate a feasible, robust and non-destructive method that dynamically quantifies response to drought, under both controlled and field conditions. Firstly, RGB images of individual rice plants at different growth points were analyzed to derive 4 features that were influenced by imposition of drought. These include a feature related to the ability to stay green, which we termed greenness plant area ratio (GPAR) and 3 shape descriptors [total plant area/bounding rectangle area ratio (TBR), perimeter area ratio (PAR) and total plant area/convex hull area ratio (TCR)]. Experiments showed that these 4 features were capable of discriminating reliably between drought resistant and drought sensitive accessions, and dynamically quantifying the drought response under controlled conditions across time (at either daily or half hourly time intervals). We compared the 3 shape descriptors and concluded that PAR was more robust and sensitive to leaf-rolling than the other shape descriptors. In addition, PAR and GPAR proved to be effective in quantification of drought response in the field. Moreover, the values obtained in field experiments using the collection of rice varieties were correlated with those derived from pot-based experiments. The general applicability of the algorithms is demonstrated by their ability to probe archival Miscanthus data previously collected on an independent platform. In conclusion, this image-based technology is robust providing a platform-independent tool for quantifying drought response that should be of general utility for breeding and functional genomics in future.

Image-Based Assessment of Drought Response in Grapevines

“…Decreasing of the green color fraction (or increasing yellow or brown ones) is usually associated to onset and progress of leaf senescence as induced also by drought to the extent that reduction or prolonged persistence of green color are thought robust indicators to discriminate drought prone or tolerant plants (Munné-Bosch and Alegre, 2004;Cai et al, 2016;Duan et al, 2018). During the early 3 DADI, GGF values were not statistically significant among the irrigation treatments, showing a GGF sitting at around 0.6 ( Figure 10).…”

“…For example, leaf angle variation can reduce the thermo-radiative load on leaf (and in turn its temperature, conductance and transpiration), minimizing the inhibition of photosystem II and contributing to water conservation (Gamon and Pearcy, 1989;Palliotti et al, 2008). Many grass species also display leaf blade rolling in response to drought, reducing the surface exposed to thermal radiation and such responses are quantifiable using image based analyses (Duan et al, 2018).…”

High-throughput phenotyping platform for analyzing drought tolerance in rice

“…Image-based traits were extracted from 507 rice accessions were classified into biomass, greenness, morphological, and histogram texture (Guo et al 2018 ). Duan et al ( 2018 ) analyzed four RGB traits including green projected area ratio, total projected area area/bounding rectangle of area ratio, perimeter/projected area ratio, and total projected plant area/convex hull area ratio from 40 drought-resistant and drought-sensitive accessions of rice. Drought stress analysis platforms in rice are mostly based on RGB traits, and various imaging analysis techniques including RGB are needed to develop them.…”

QTL detection and putative candidate gene prediction for leaf rolling under moisture stress condition in wheat

“…Leaf rolling is a complex quantitative trait that is controlled by multiple genes following non-Mendelian inheritance 15 . Leaf rolling is a typical response related to mechanism of reducing moisture stress in field crops which is well studied in rice 16 , 17 and maize 15 , 18 . Five mutants in maize 19 – 22 and 17 mutants in rice with leaf rolling traits 22 have been characterized.…”