Prediction of matrilineal specific patatin-like protein governing in-vivo maternal haploid induction in maize using support vector machine and di-peptide composition.

The mutant matrilineal (mtl) gene encoding patatin-like phospholipase activity is involved in in-vivo maternal haploid induction in maize. Doubling of chromosomes in haploids by colchicine treatment leads to complete fixation of inbreds in just one generation compared to 6-7 generations of selfing. Thus, knowledge of patatin-like proteins in other crops assumes great significance for in-vivo haploid induction.

A lightweight convolutional neural network for recognition of severity stages of maydis leaf blight disease of maize.

Maydis leaf blight (MLB) of maize (), a serious fungal disease, is capable of causing up to 70% damage to the crop under severe conditions. Severity of diseases is considered as one of the important factors for proper crop management and overall crop yield. Therefore, it is quite essential to identify the disease at the earliest possible stage to overcome the yield loss.

SlypNet: Spikelet-based yield prediction of wheat using advanced plant phenotyping and computer vision techniques.

The application of computer vision in agriculture has already contributed immensely to restructuring the existing field practices starting from the sowing to the harvesting. Among the different plant parts, the economic part, the yield, has the highest importance and becomes the ultimate goal for the farming community. It depends on many genetic and environmental factors, so this curiosity about knowing the yield brought several precise pre-harvest prediction methods using different ways.

Deep learning-based approach for identification of diseases of maize crop.

In recent years, deep learning techniques have shown impressive performance in the field of identification of diseases of crops using digital images. In this work, a deep learning approach for identification of in-field diseased images of maize crop has been proposed. The images were captured from experimental fields of ICAR-IIMR, Ludhiana, India, targeted to three important diseases viz.

Assessment of Different File Systems for Working Time Based on Glide Path, Operating Kinetics, and the Fracture Resistance.

Aim: This study was done to assess the time to achieve the working distance based on the size of the glide path, operating kinetics, and the fracture resistance of different file systems.

Materials And Method: One hundred and eighty mandibular premolars were divided into two groups of 90 each. Group I was subjected to continuous 360° rotary motion and group II to adaptive motion.

SpikeSegNet-a deep learning approach utilizing encoder-decoder network with hourglass for spike segmentation and counting in wheat plant from visual imaging.

Background: High throughput non-destructive phenotyping is emerging as a significant approach for phenotyping germplasm and breeding populations for the identification of superior donors, elite lines, and QTLs. Detection and counting of spikes, the grain bearing organs of wheat, is critical for phenomics of a large set of germplasm and breeding lines in controlled and field conditions. It is also required for precision agriculture where the application of nitrogen, water, and other inputs at this critical stage is necessary.

EdU incorporation is an alternative non-radioactive assay to [(3)H]thymidine uptake for in vitro measurement of mice T-cell proliferations.

Rationale: T lymphocyte proliferations can be measured by [(3)H]thymidine incorporation. However, many labs avoid this technique because of the need to use radioactive substrates. In addition, [(3)H]thymidine incorporation method does not permit simultaneous characterization of the proliferating cells.

Assessment of an anti-HIV-1 combination gene therapy strategy using the antisense RNA and multimeric hammerhead ribozymes.

A combination gene therapy strategy using an ASPsi-gag antisense RNA (targeted against the packaging signal and the gag-coding region) and a multimeric hammerhead ribozyme Rz1-9 (targeted against nine sites within the env-coding region) or Rz1-14 (targeted against 14 sites within the 5' leader and the pro-, pol-, vif- and env-coding regions) was assessed for inhibiting HIV-1 replication. A murine stem cell virus (MSCV)-based MGIN vector was used to express Rz1-9, Rz1-14, ASPsi-gag, Rz1-9ASPsi-gag, or Rz1-14ASPsi-gag RNA in a CD4+ T lymphoid cell line. Stable transductants were shown to express similar levels of interfering RNA.