196 research outputs found

    L’exploration du gite à Dinosauriens jurassiques de damparis

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    Evolving technologies for growing, imaging and analyzing 3D root system architecture of crop plants

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    A plant's ability to maintain or improve its yield under limiting conditions, such as nutrient deficiency or drought, can be strongly influenced by root system architecture (RSA), the three-dimensional distribution of the different root types in the soil. The ability to image, track and quantify these root system attributes in a dynamic fashion is a useful tool in assessing desirable genetic and physiological root traits. Recent advances in imaging technology and phenotyping software have resulted in substantive progress in describing and quantifying RSA. We have designed a hydroponic growth system which retains the three-dimensional RSA of the plant root system, while allowing for aeration, solution replenishment and the imposition of nutrient treatments, as well as high-quality imaging of the root system. The simplicity and flexibility of the system allows for modifications tailored to the RSA of different crop species and improved throughput. This paper details the recent improvements and innovations in our root growth and imaging system which allows for greater image sensitivity (detection of fine roots and other root details), higher efficiency, and a broad array of growing conditions for plants that more closely mimic those found under field conditions

    Fine-mapping of qRL6.1, a major QTL for root length of rice seedlings grown under a wide range of NH4+ concentrations in hydroponic conditions

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    Root system development is an important target for improving yield in cereal crops. Active root systems that can take up nutrients more efficiently are essential for enhancing grain yield. In this study, we attempted to identify quantitative trait loci (QTL) involved in root system development by measuring root length of rice seedlings grown in hydroponic culture. Reliable growth conditions for estimating the root length were first established to renew nutrient solutions daily and supply NH4+ as a single nitrogen source. Thirty-eight chromosome segment substitution lines derived from a cross between ‘Koshihikari’, a japonica variety, and ‘Kasalath’, an indica variety, were used to detect QTL for seminal root length of seedlings grown in 5 or 500 μM NH4+. Eight chromosomal regions were found to be involved in root elongation. Among them, the most effective QTL was detected on a ‘Kasalath’ segment of SL-218, which was localized to the long-arm of chromosome 6. The ‘Kasalath’ allele at this QTL, qRL6.1, greatly promoted root elongation under all NH4+ concentrations tested. The genetic effect of this QTL was confirmed by analysis of the near-isogenic line (NIL) qRL6.1. The seminal root length of the NIL was 13.5–21.1% longer than that of ‘Koshihikari’ under different NH4+ concentrations. Toward our goal of applying qRL6.1 in a molecular breeding program to enhance rice yield, a candidate genomic region of qRL6.1 was delimited within a 337 kb region in the ‘Nipponbare’ genome by means of progeny testing of F2 plants/F3 lines derived from a cross between SL-218 and ‘Koshihikari’

    Accelerating root system phenotyping of seedlings through a computer-assisted processing pipeline

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    Background: There are numerous systems and techniques to measure the growth of plant roots. However, phenotyping large numbers of plant roots for breeding and genetic analyses remains challenging. One major difficulty is to achieve high throughput and resolution at a reasonable cost per plant sample. Here we describe a cost-effective root phenotyping pipeline, on which we perform time and accuracy benchmarking to identify bottlenecks in such pipelines and strategies for their acceleration. Results: Our root phenotyping pipeline was assembled with custom software and low cost material and equipment. Results show that sample preparation and handling of samples during screening are the most time consuming task in root phenotyping. Algorithms can be used to speed up the extraction of root traits from image data, but when applied to large numbers of images, there is a trade-off between time of processing the data and errors contained in the database. Conclusions: Scaling-up root phenotyping to large numbers of genotypes will require not only automation of sample preparation and sample handling, but also efficient algorithms for error detection for more reliable replacement of manual interventions

    Rice actin binding protein RMD controls crown root angle in response to external phosphate

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    Root angle has a major impact on acquisition of nutrients like phosphate that accumulate in topsoil and in many species; low phosphate induces shallower root growth as an adaptive response. Identifying genes and mechanisms controlling root angle is therefore of paramount importance to plant breeding. Here we show that the actin-binding protein Rice Morphology Determinant (RMD) controls root growth angle by linking actin filaments and gravity-sensing organelles termed statoliths. RMD is upregulated in response to low external phosphate and mutants lacking of RMD have steeper crown root growth angles that are unresponsive to phosphate levels. RMD protein localizes to the surface of statoliths, and rmd mutants exhibit faster gravitropic response owing to more rapid statoliths movement. We conclude that adaptive changes to root angle in response to external phosphate availability are RMD dependent, providing a potential target for breeders
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