PI-Plat: a high-resolution image-based 3D reconstruction method to estimate growth dynamics of rice inflorescence traits

Abstract

BackgroundRecent advances in image-based plant phenotyping have improved our capability to study vegetative stage growth dynamics. However, more complex agronomic traits such as inflorescence architecture (IA), which predominantly contributes to grain crop yield are more challenging to quantify and hence are relatively less explored. Previous efforts to estimate inflorescence-related traits using image-based phenotyping have been limited to destructive end-point measurements. Development of non-destructive inflorescence phenotyping platforms could accelerate the discovery of the phenotypic variation with respect to inflorescence dynamics and mapping of the underlying genes regulating critical yield components.ResultsThe major objective of this study is to evaluate post-fertilization development and growth dynamics of inflorescence at high spatial and temporal resolution in rice. For this, we developed the Panicle Imaging Platform (PI-Plat) to comprehend multi-dimensional features of IA in a non-destructive manner. We used 11 rice genotypes to capture multi-view images of primary panicle on weekly basis after the fertilization. These images were used to reconstruct a 3D point cloud of the panicle, which enabled us to extract digital traits such as voxel count and color intensity. We found that the voxel count of developing panicles is positively correlated with seed number and weight at maturity. The voxel count from developing panicles projected overall volumes that increased during the grain filling phase, wherein quantification of color intensity estimated the rate of panicle maturation. Our 3D based phenotyping solution showed superior performance compared to conventional 2D based approaches.ConclusionsFor harnessing the potential of the existing genetic resources, we need a comprehensive understanding of the genotype-to-phenotype relationship. Relatively low-cost sequencing platforms have facilitated high-throughput genotyping, while phenotyping, especially for complex traits, has posed major challenges for crop improvement. PI-Plat offers a low cost and high-resolution platform to phenotype inflorescence-related traits using 3D reconstruction-based approach. Further, the non-destructive nature of the platform facilitates analyses of the same panicle at multiple developmental time points, which can be utilized to explore the genetic variation for dynamic inflorescence traits in cereals.

Robotic Technologies for High-Throughput Plant Phenotyping: Contemporary Reviews and Future Perspectives

“…The morphometric parameters of inflorescence are highly correlated with yield and grain quality (Leilah and Al-Khateeb, 2005;Gegas et al, 2010). Several studies discussed about using image-based techniques (2D images/3D reconstruction) to extract architectural traits such as length and width of inflorescence, inflorescence volume (weight), grain shape and size, grain angle, and number of grains, and number of flowers (Faroq et al, 2013;Crowell et al, 2014;Gage et al, 2017;Rudolph et al, 2019;Sandhu et al, 2019;Xiong et al, 2019;Zhou et al, 2019). In such applications to measure the morphological traits, a robot with LIDAR/camera can be useful to automatically take images/point cloud data from different views of the inflorescence.…”

Bottlenecks and opportunities in field-based high-throughput phenotyping for heat and drought stress

“…Research into using remote sensing to quantify seed number and grain weight of a plant in a field environment is limited. There has been success in controlled environments in which a 3D reconstruction of rice showed that seed number for the panicle had a significant ( P <0.05) positive correlation with the voxel count of the reconstruction throughout the grain-filling period ( r =0.61–0.70) ( Sandhu et al , 2019 ). This same experiment also found a significant ( P <0.05) positive correlation ( r =0.48–0.74) between voxel count and seed weight which increased approaching maturity.…”

Allelic variation in rice Fertilization Independent Endosperm 1 contributes to grain width under high night temperature stress

“…Plants were grown in a glasshouse under controlled conditions (16 h 30 AE 1°C : 8 h 23 AE 1°C, light : dark, relative humidity 55-60%). At 1 d after c. 50-70% of the primary panicle underwent flowering (Sandhu et al, 2019), three plants from each accession were transferred to a glasshouse under 16 h 30 AE 1°C : 8 h 28 AE 1°C, light : dark conditions for a terminal HNT treatment and the remaining three plants for each accession were maintained under the control glasshouse conditions (30 AE 1°C : 23 AE 1°C, light : dark). HNT stress and control conditions for this study represent the glasshouse air temperatures.…”