scholarly journals Image‐based root phenotyping links root architecture to micronutrient concentration in cassava

2020 ◽  
Vol 2 (6) ◽  
pp. 678-687
Author(s):  
Natalie Busener ◽  
Jitrana Kengkanna ◽  
Patompong Johns Saengwilai ◽  
Alexander Bucksch
Keyword(s):  
Root Architecture ◽  
Micronutrient Concentration ◽  
Root Phenotyping

scholarly journals Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems

2017 ◽  
Vol 68 (5) ◽  
pp. 965-982 ◽  
Author(s):  
Jiangsan Zhao ◽  
Gernot Bodner ◽  
Boris Rewald ◽  
Daniel Leitner ◽  
Kerstin A. Nagel ◽  
...  
Keyword(s):  
Root Architecture ◽  
Root Systems ◽  
Seedling Root ◽  
Root Phenotyping ◽  
Architecture Simulation ◽  
Mature Root

scholarly journals Phenotyping Root Architecture of Soil-Grown Rice: A Robust Protocol Combining Manual Practices with Image-based Analyses

2020 ◽  
Author(s):  
P. De Bauw ◽  
J. A. Ramarolahy ◽  
K. Senthilkumar ◽  
T. Rakotoson ◽  
R. Merckx ◽  
...  
Keyword(s):  
Root System ◽  
Root Architecture ◽  
Root Systems ◽  
Field Conditions ◽  
Rice Root ◽  
Root Tip ◽  
Genotypic Differences ◽  
Rice Varieties ◽  
Lower Accuracy ◽  
Root Phenotyping

AbstractBackgroundBreeding towards resilient rice varieties is often constrained by the limited data on root system architecture obtained from relevant agricultural environments. Knowledge on the genotypic differences and responses of root architecture to environmental factors is limited due the difficulty of analysing soil-grown rice roots. An improved method using imaging is thus needed, but the existing methods were never proven successful for rice. Here, we aimed to evaluate and improve a higher throughput method of image-based root phenotyping for rice grown under field conditions. Rice root systems from seven experiments were phenotyped based on the “shovelomics” method of root system excavation followed by manual root phenotyping and digital root analysis after root imaging. Analyzed traits were compared between manual and image-based root phenotyping systems using Spearman rank correlations to evaluate whether both methods similarly rank the phenotypes. For each trait, the relative phenotypic variation was calculated. A principal component analysis was then conducted to assess patterns in root architectural variation.ResultsSeveral manually collected and image-based root traits were identified as having a high potential of differentiating among contrasting phenotypes, while other traits are found to be inaccurate and thus unreliable for rice. The image-based traits projected area, root tip thickness, stem diameter, and root system depth successfully replace the manual determination of root characteristics, however attention should be paid to the lower accuracy of the image-based methodology, especially when working with older and larger root systems.ConclusionsThe challenges and opportunities of rice root phenotyping in field conditions are discussed for both methods. We therefore propose an integrated protocol adjusted to the complexity of the rice root structure combining image analysis in a water bath and the manual scoring of three traits (i.e. lateral density, secondary branching degree, and nodal root thickness at the root base). The proposed methodology ensures higher throughput and enhanced accuracy during root phenotyping of soil grown rice in fields or pots compared to manual scoring only, it is cheap to develop and operate, it is valid in remote environments, and it enables fast data extraction.

scholarly journals Development of Root Phenotyping Platforms for Identification of Root Architecture Mutations in EMS-Induced and Low-Path-Sequenced Sorghum Mutant Population

2020 ◽  
Vol 11 (06) ◽  
pp. 838-850
Author(s):  
Viktor Tishchenko ◽  
Mingli Wang ◽  
Zhanguo Xin ◽  
Melanie Harrison
Keyword(s):  
Root Architecture ◽  
Mutant Population ◽  
Root Phenotyping

scholarly journals High throughput phenotyping of root growth dynamics, lateral root formation, root architecture and root hair development enabled by PlaRoM

2009 ◽  
Vol 36 (11) ◽  
pp. 938 ◽  
Author(s):  
Nima Yazdanbakhsh ◽  
Joachim Fisahn
Keyword(s):  
Root Growth ◽  
Growth Kinetics ◽  
Lateral Root ◽  
Root Architecture ◽  
Imaging Techniques ◽  
Plant Root ◽  
Primary Root ◽  
Growth Media ◽  
Root Extension ◽  
Lateral Root Development

Plant organ phenotyping by non-invasive video imaging techniques provides a powerful tool to assess physiological traits and biomass production. We describe here a range of applications of a recently developed plant root monitoring platform (PlaRoM). PlaRoM consists of an imaging platform and a root extension profiling software application. This platform has been developed for multi parallel recordings of root growth phenotypes of up to 50 individual seedlings over several days, with high spatial and temporal resolution. PlaRoM can investigate root extension profiles of different genotypes in various growth conditions (e.g. light protocol, temperature, growth media). In particular, we present primary root growth kinetics that was collected over several days. Furthermore, addition of 0.01% sucrose to the growth medium provided sufficient carbohydrates to maintain reduced growth rates in extended nights. Further analysis of records obtained from the imaging platform revealed that lateral root development exhibits similar growth kinetics to the primary root, but that root hairs develop in a faster rate. The compatibility of PlaRoM with currently accessible software packages for studying root architecture will be discussed. We are aiming for a global application of our collected root images to analytical tools provided in remote locations.

Knockdown of MicroRNA160a/b by STTM leads to root architecture changes via auxin signaling in Solanum tuberosum

2021 ◽  
Author(s):  
Jiangwei Yang ◽  
Ning Zhang ◽  
Jinlin Zhang ◽  
Xin Jin ◽  
Xi Zhu ◽  
...  
Keyword(s):  
Solanum Tuberosum ◽  
Root Architecture ◽  
Auxin Signaling

scholarly journals Meta-QTL and ortho-MQTL analyses identified genomic regions controlling rice yield, yield-related traits and root architecture under water deficit conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bahman Khahani ◽  
Elahe Tavakol ◽  
Vahid Shariati ◽  
Laura Rossini
Keyword(s):  
Water Deficit ◽  
Root Architecture ◽  
Agronomic Traits ◽  
Heading Date ◽  
Dry Weight ◽  
Genetic Dissection ◽  
Rice Varieties ◽  
Average Confidence ◽  
Stable Qtls ◽  
Genomic Regions

AbstractMeta-QTL (MQTL) analysis is a robust approach for genetic dissection of complex quantitative traits. Rice varieties adapted to non-flooded cultivation are highly desirable in breeding programs due to the water deficit global problem. In order to identify stable QTLs for major agronomic traits under water deficit conditions, we performed a comprehensive MQTL analysis on 563 QTLs from 67 rice populations published from 2001 to 2019. Yield and yield-related traits including grain weight, heading date, plant height, tiller number as well as root architecture-related traits including root dry weight, root length, root number, root thickness, the ratio of deep rooting and plant water content under water deficit condition were investigated. A total of 61 stable MQTLs over different genetic backgrounds and environments were identified. The average confidence interval of MQTLs was considerably refined compared to the initial QTLs, resulted in the identification of some well-known functionally characterized genes and several putative novel CGs for investigated traits. Ortho-MQTL mining based on genomic collinearity between rice and maize allowed identification of five ortho-MQTLs between these two cereals. The results can help breeders to improve yield under water deficit conditions.

Influence of nutrient deficiency on root architecture and root hair morphology of trifoliate orange (Poncirus trifoliata L. Raf.) seedlings under sand culture

2013 ◽  
Vol 162 ◽  
pp. 100-105 ◽  
Author(s):  
Xiu Cao ◽  
Chunli Chen ◽  
Dejian Zhang ◽  
Bo Shu ◽  
Jie Xiao ◽  
...  
Keyword(s):  
Root Hair ◽  
Root Architecture ◽  
Nutrient Deficiency ◽  
Poncirus Trifoliata ◽  
Sand Culture ◽  
Trifoliate Orange ◽  
Hair Morphology

Rhizobacteria modify root architecture and improve nutrient uptake in oil palm seedlings despite reduced fertilizer

Rhizosphere ◽  
2021 ◽  
pp. 100420
Author(s):  
Josué Valente Lima ◽  
Ricardo Salles Tinôco ◽  
Fabio Lopes Olivares ◽  
Gilson Sanchez Chia ◽  
José Ailton Gomes de Melo Júnior ◽  
...  
Keyword(s):  
Nutrient Uptake ◽  
Oil Palm ◽  
Root Architecture
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