Recent Posts

Nanoscale movements of cellulose microfibrils in primary cell walls ($)

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Cell walls are complex mixtures of cellulose microfibrils, proteins and other materials. Their mechanical properties can be measured and modeled, but it is not always simple to translate these measurements to changes at the molecular level. Zhang et al. used atomic force microscopy to provide an unprecedented…

Functional principal component analysis: a robust method for time-series phenotypic data

Molecular breeding relies on careful assessment of phenotypic traits linked to DNA markers so that causal genes can be identified and desirable crop alleles selected. Over the past decade, DNA markers have become abundant with the rapid advancement of next-generation sequencing technology, including…

Single nucleus analysis of Arabidopsis seeds reveals new cell types and imprinting dynamics (bioRxiv)

Arabidopsis seeds consist of various tissue like seed coat, embryo, and endosperm. The endosperm provides the nutrient supplies to the growing embryo and has three domains namely, micropylar (surrounding embryo), chalazal (opposite end of the seed), and peripheral (in between micropylar and chalazal)…

Review: Crop phenomics and high-throughput phenotyping (Mol. Plant)

Crop phenomics has lagged behind crop genomics because traditional methods are time-consuming, expensive, invasive and subjective. Recently, high-throughput, automated, sensor and machine-vision methods have been developed, as reviewed by Yang et al. This review describes a large number of phenotyping…

Review: Deep learning for plant genomics and crop improvement (Curr. Opin. Plant Biol.)

One of the goals of plant science is to use the molecular phenotype (genome, transcriptome, proteome) to predict the whole-plant phenotype. Deep learning approaches can potentially begin to do this, starting with a training dataset, and testing it with a validation dataset. Wang et al. review advances…

Transdisciplinary Plant Phenomics and Phenotyping for Maize Crop Improvement

When: Tuesday, January 21, 2020, at 12 PM PST (UTC-8) | 2 PM CST (UTC-6) | 3 PM EST (UTC -5) Emerging tools in plant phenomics and high-throughput field phenotyping are redefining possibilities for decisions in plant breeding and agronomy as well as discoveries in the plant sciences more broadly.…

Simulation modeling platform provides a powerful tool for identifying optimal traits and management practices for wheat production

Author: Robert P Skelton1 skelrob@berkeley.edu Affiliation: Dept. of Integrative Biology, University of California Berkeley, Berkeley, CA, 94720, USA  Global demand for food security places an emphasis on a need to improve crop yield. The complexity of plant development and its interaction…

Functional Phenomics: Studying Root Physiology Using Affordable Open Source Tools

Tuesday, December 17, 2019, at 11 AM PST (UTC-8) | 1 PM CST (UTC-6) | 2 PM EST (UTC-5) Functional phenomics is an emerging discipline that utilizes phenotyping, physiology, multivariate statistics, and simulation modeling to generate and test new hypotheses about how plant traits integrate to influence…

The use of high throughput phenotyping for assessment of heat stress-induced changes in Arabidopsis (bioRxiv)

With global temperatures rising, tolerance to heat is becoming increasingly important as a breeding target for crop plants, but it is a highly complex response that includes processes including plant cooling capacity, growth recovery, and maintenance of photosynthesis. Using Arabidopsis, Gao et al. developed…

Shared genetic control of root system architecture between Zea mays and Sorghum bicolor (Plant Physiol)

Root research got a boost from Arabidopsis grown on Petri plants, but what do you do if you study something bigger, or want to see how roots grow in soil? Zheng et al. developed a new set of tools they call CREAMD-COFE [Core Root Excavation using Compressed-air (to extract the roots from soil), and Core…