Recent Posts

Effect of leaf temperature on the estimation of photosynthetic and other traits of wheat leaves from hyperspectral reflectance (J. Exp. Bot.)

Efficient phenotyping is important for plant breeding. For wheat, leaf reflectance spectra can be used to calculate leaf traits that impact crop yield, particularly constituent (leaf mass per area, nitrogen/chlorophyll content) and physiological (Rubisco carboxylation activity, electron transport…

Leaf angle control across the sorghum canopy (Plant Physiol.)

In a rosette-forming plant like Arabidopsis, leaf radial angle is optimized to prevent self-shielding. By contrast, in a plant such as sorghum, leaf vertical angle affects self-shading. A “smart canopy” model has been proposed in which upper leaves have a more upright orientation to allow more light…

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

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Transdisciplinary Plant Phenomics and Phenotyping for Maize Crop Improvement Recorded Tuesday, January 21, 2020 About This Webinar Emerging tools in plant phenomics and high-throughput field phenotyping are redefining possibilities for decisions in plant breeding and agronomy…

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

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Functional Phenomics: Studying Root Physiology Using Affordable Open Source Tools Recorded December 17, 2019   About This Webinar Functional phenomics is an emerging discipline that utilizes phenotyping, physiology, multivariate statistics, and simulation modeling to generate and test new…