Nucleotide and amino acid sequences on the On-DnaJ B9b gene. Table S2. Homology evaluation of your nucleotide and amino acid sequences of your On-DnaJ C3a gene. Figure S1. Homology model of On-DnaJB9b. (A) Comparison with a nonredundant set of PDB structures on the On-DnaJB9b model and (B) nearby quality plot. Figure S2. Model of On-DnaJC3a homology. (A) Comparison with a nonredundant set of PDB structures with the On-DnaJC3a model and (B) regional high quality plot. Figure S3. Phylogenetic trees in the Nile tilapia DnaJ B9b and DnaJ C3a genes. Author Contributions: Conceptualization, P.S.; methodology, P.S.; software, K.T. and P.S.; Bisindolylmaleimide XI manufacturer validation, K.T. and P.S.; formal evaluation, K.T., R.W. and P.S.; investigation, K.T., R.W. and P.S.; sources, P.S.; information curation, K.T. and P.S.; writing-original draft preparation, K.T. and P.S.; writing-review and editing, K.T. and P.S.; visualization, P.S.; supervision, P.S.; project administration, P.S.; funding acquisition, P.S. All authors have study and agreed for the published version in the manuscript. Funding: This perform was supported by Thailand Science Analysis and Innovation (TSRI) (RDG6220035). Institutional Review Board Statement: This study was carried out in accordance with all the principle on the Basel Declaration plus the suggestions with the Guide for the Care and Use of Perospirone supplier Laboratory Animals on the Ethical Committee of Kasetsart University, Thailand, with the approval quantity ACKU63-FIS-006 (approval date 10 August 2020). Informed Consent Statement: Not applicable. Acknowledgments: This work was supported by the Human Resource Improvement in Science Project (Science Achievement Scholarship of Thailand, SAST); the Workplace of your Larger Education Commission (OHEC); along with the Ministry of Education, Thailand and Kasetsart University Investigation and Development Institute (KURDI), Kasetsart University, Thailand. Conflicts of Interest: The authors declare no conflict of interest.
agricultureArticleA Comparative Study of Semantic Segmentation Models for Identification of Grape with Unique VarietiesYun Peng 1,two , Aichen Wang 1 , Jizhan Liu 1, and Muhammad FaheemKey Laboratory of Contemporary Agricultural Gear and Technology, Ministry of Education, Jiangsu University, Zhenjiang 212013, China; [email protected] (Y.P.); [email protected] (A.W.); [email protected] (M.F.) School of Electronic Engineering, Changzhou College of Details Technologies, Changzhou 213164, China Correspondence: [email protected]; Tel.: +86-511-Citation: Peng, Y.; Wang, A.; Liu, J.; Faheem, M. A Comparative Study of Semantic Segmentation Models for Identification of Grape with Distinct Varieties. Agriculture 2021, 11, 997. https://doi.org/10.3390/ agricultureAbstract: Precise fruit segmentation in pictures could be the prerequisite and essential step for precision agriculture. Within this report, aiming in the segmentation of grape cluster with distinctive varieties, three state-of-the-art semantic segmentation networks, i.e., Totally Convolutional Network (FCN), UNet, and DeepLabv3+ applied on six different datasets were studied. We investigated: (1) the segmentation overall performance difference in the three studied networks; (two) The impact of various input representations on segmentation overall performance; (three) The impact of image enhancement method to improve the poor illumination of images and further boost the segmentation efficiency; (4) The impact of the distance between grape clusters and camera on segmentation functionality. The experiment results show that.
