Jinglu Wang

TL;DR: The challenges and prospective of crop phenomics are discussed in order to provide suggestions to develop new methods of mining genes associated with important agronomic traits, and propose new intelligent solutions for precision breeding.

TL;DR: The newly-built CLI was demonstrated to be a more robust indicator than mechanical properties, FWS, and RI when evaluating lodging resistance in terms of both reliability and resolution and provides technical support for accurate identification of lodging-resistant phenotypic traits.

TL;DR: A standard process for stem micro‐CT data acquisition and an automatic CT image process pipeline are developed to obtain vascular bundle traits of stems including geometry‐related, morphology‐related and distribution‐related traits and useful information is provided for understanding the genetic controls of vascular bundle formation and development.

TL;DR: This study demonstrates the utility of VesselParser 2.0 in assessing stalk mechanical properties, showing that micro phenotypes of vascular bundles are good predictors of maize stalk mechanical Properties that may be important indices for the evaluation and identification of the biomechanical properties to improve lodging resistance of future maize varieties.

TL;DR: Compared with traditional manual measurement of vascular bundles of maize materials, the proposed protocols significantly improve the efficiency and accuracy of micron-scale phenotypic quantification.