In silico design of crop ideotypes under a wide range of water availability

Given the changing climate and increasing impact of agriculture on global resources, it is important to identify phenotypes which are global and sustainable optima. Here, an in silico framework is constructed by coupling evolutionary optimization with thermodynamically sound crop physiology, and its ability to rationally design phenotypes with maximum productivity is demonstrated, within well‐defined limits on water availability. Results reveal that in mesic environments, such as the North American Midwest, and semi‐arid environments, such as Colorado, phenotypes optimized for maximum productivity and survival under drought are similar to those with maximum productivity under irrigated conditions. In hot and dry environments like California, phenotypes adapted to drought produce 40% lower yields when irrigated compared to those optimized for irrigation. In all three representative environments, the trade‐off between productivity under drought versus that under irrigation was shallow, justifying a successful strategy of breeding crops combining best productivity under irrigation and close to best productivity under drought

Self-Supervised Maize Kernel Classification and Segmentation for Embryo Identification

These are companion data of manuscript "Self-Supervised Maize Kernel Classification and Segmentation for Embryo Identification" that was submitted to Frontiers in Plant Science. The data is organized into three main folders: 'class_full_imgs', 'seg_full_imgs', and 'unlabeled'. The 'class_full_imgs' folder contains labeled data used to train the classification model, which is divided into train, validation, and test subfolders. Each of these subfolders contains 'oriented' and 'non-oriented' images. The 'seg_full_imgs' folder contains labeled data used to train the segmentation model. The 'InputImages' subfolder contains raw images, and the 'OutputImages' subfolder contains the segmented images. The 'unlabeled' folder contains images without any labels. These images were used for self-supervised pretraining of classification and segmentation models.This work was partially supported by the AI Institute for Resilient Agriculture (USDA-NIFA #2021-67021-35329), COALESCE: COntext Aware LEarning for Sustainable CybEr-Agricultural Systems (CPS Frontier # 1954556), and support from a PSI faculty fellowship

Protocols for In Vivo Doubled Haploid (DH) Technology in Maize Breeding: From Haploid Inducer Development to Haploid Genome Doubling

Doubled haploid (DH) technology reduces the time required to obtain homozygous genotypes and accelerates plant breeding among other advantages. It is established in major crop species such as wheat, barley, maize, and canola. DH lines can be produced by both in vitro and in vivo methods and the latter is focused here. The major steps involved in in vivo DH technology are haploid induction, haploid selection/identification, and haploid genome doubling. Herein, we elaborate on the various steps of DH technology in maize breeding from haploid induction to haploid genome doubling to produce DH lines. Detailed protocols on the following topics are discussed: in vivo haploid inducer line development, haploid selection using seed and root color markers and automated seed sorting based on embryo oil content using QSorter, artificial genome doubling, and the identification of genotypes with spontaneous haploid genome doubling (SHGD) ability.This is a manuscript of a chapter published as Aboobucker S.I. et al. (2022) Protocols for In Vivo Doubled Haploid (DH) Technology in Maize Breeding: From Haploid Inducer Development to Haploid Genome Doubling. In: Lambing C. (eds) Plant Gametogenesis. Methods in Molecular Biology, vol 2484. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2253-7_16. Posted with permission

A new fabrication technique to form complex polymethylmethacrylate microchannel for bioseparation

Recent studies show that reduction in cross-sectional area can be used to improve the concentration factor in microscale bioseparations. Due to simplicity in fabrication process, a step reduction in cross-sectional area is generally implemented in microchip to increase the concentration factor. But the sudden change in cross-sectional area can introduce significant band dispersion and distortion. This paper reports a new fabrication technique to form a gradual reduction in cross-sectional area in polymethylmethacrylate (PMMA) microchannel for both anionic and cationic isotachophoresis (ITP). The fabrication technique is based on hot embossing and surface modification assisted bonding method. Both one-dimensional and two-dimensional gradual reduction in cross-sectional area microchannels were formed on PMMA with high fidelity using proposed techniques. ITP experiments were conducted to separate and preconcentrate fluorescent proteins in these microchips. Thousand fold and ten thousand fold increase in concentrations were obtained when 10 × and 100 × gradual reduction in cross-sectional area microchannels were used for ITP