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Tetteh, G.

Publications and source records attributed to Tetteh, G..

2 recordsLinked to original sources

Potential of Bacillus subtilis as a biological control agent against three rot-causing pathogens in seed yams

Ghana is the largest exporter of yams in West Africa. However, yam production, particularly seed yam production, is constrained by storage rot during the off-season. Farmers seldom use synthetic pesticides to control seed yam rot. However, these are costly and pose adverse health risks to farmers. Biological antagonists offer a sustainable, relatively cost-effective, and safe alternative to synthetic pesticides. Therefore, this study aimed to test the efficacy of Bacillus subtilis as an alternative to synthetic pesticides. Bacillus subtilis supplied through the biofungicide Serenade ASO (Bayer) was assayed against three storage-rot pathogens: Lasiodiplodia theobromae, Aspergillus niger, and Rhizopus sp. These pathogens were previously isolated from the tissues of rotten seed yams. The efficacy of the bacterium was tested at concentrations of 17 %, 33 %, and 50 % in both in vitro and in vivo bioassays. B. subtilis (50 %) completely inhibited the growth (100 %) of L. theobromae in the in vitro studies. In contrast, there was little to no growth inhibition of the other two test fungi. In the in vivo assay, B. subtilis (50%) significantly (P < 0.01) inhibited L. theobromae, resulting in minimal rot lesions. However, B. subtilis (50 %) was ineffective against the other two test pathogens, resulting in large rot lesions on the seed yams. This suggests that B. subtilis could be an ideal alternative to synthetic pesticides for controlling L. theobromae on seed yams.

plant biology↗

Automated analysis of whole brain vasculature using machine learning

Tissue clearing methods enable imaging of intact biological specimens without sectioning. However, reliable and scalable analysis of such large imaging data in 3D remains a challenge. Towards this goal, we developed a deep learning-based framework to quantify and analyze the brain vasculature, named Vessel Segmentation & Analysis Pipeline (VesSAP). Our pipeline uses a fully convolutional network with a transfer learning approach for segmentation. We systematically analyzed vascular features of the whole brains including their length, bifurcation points and radius at the micrometer scale by registering them to the Allen mouse brain atlas. We reported the first evidence of secondary intracranial collateral vascularization in CD1-Elite mice and found reduced vascularization in the brainstem as compared to the cerebrum. VesSAP thus enables unbiased and scalable quantifications for the angioarchitecture of the cleared intact mouse brain and yields new biological insights related to the vascular brain function.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC=\"FIGDIR/small/613257_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (51K):\norg.highwire.dtl.DTLVardef@8c79eborg.highwire.dtl.DTLVardef@984d3aorg.highwire.dtl.DTLVardef@f62d9borg.highwire.dtl.DTLVardef@2c20bc_HPS_FORMAT_FIGEXP M_FIG Supporting material of VesSAP is available at http://DISCOtechnologies.org/VesSAP\n\nC_FIG

neuroscience↗