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  • 1
    Online Resource
    Online Resource
    Inter Simple Sequence Repeat-Based Genetic Divergence and Varietal Identification of Banana in Pakistan
    MDPI AG ; 2022
    In:  Agronomy Vol. 12, No. 12 ( 2022-11-23), p. 2932-
    Details
    In: Agronomy, MDPI AG, Vol. 12, No. 12 ( 2022-11-23), p. 2932-
    Abstract: Banana is one of the major cash and fruit crops of Pakistan. The lack of information concerning genetic diversity and purity within locally cultivated banana varieties is a major bottleneck in improving its genetics. Due to the existence of a narrow genetic background, it’s quite important to find genomic variations in banana varieties. DNA marker-based techniques have been used to effectively characterize banana varieties. In the current study, Inter Simple Sequence Repeat (ISSR) markers were used to characterize banana cultivars and to assess the genetic diversity of 14 local banana varieties grown in Pakistan. Out of the 45 primers used, 40 primers revealed reproducible results and produced 121 polymorphic bands, which contributed a ratio of 47.87 polymorphism. The ISSR UBC-835 and UBC-834 possessed the highest PIC ranged between (86–88%) in banana varieties, while the lowest PIC (46%) was detected in the case of UBC−857 marker with (100–1500 bp) PCR product size. Pairwise Jaccard’s similarity coefficient values were also calculated, and these were ranged from 0.56–0.88. Multivariate analysis divided 14 banana varieties into two distinct groups—A and B respectively—and furthermore into subgroups, clusters, and sub−clusters. Our results indicated that at the molecular level, the banana varieties in group—A were found to be 66% similar whereas in group B were 88% similar. Nei’s genetic diversity, PCA analysis, and a minimum spanning tree depicted Fenjiao, Dajiao, and NIGAB-2 as the most diverse members as compared to all other varieties of the three populations. Out of 14 varieties used, 11 varieties were uniquely identified by 54 polymorphic ISSR bands of different sizes. Some varieties like NIGAB-2 and NIGAB-3 were uniquely identified only with one band while others were tagged by multiple unique bands. In future, this study will be utilized to establish a molecular-based protocol for the identification of banana varieties.
    Type of Medium: Online Resource
    ISSN: 2073-4395
    URL: Article
    DOI: 10.3390/agronomy12122932
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2607043-1
    SSG: 23
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  • 2
    Online Resource
    Online Resource
    Crop Establishment Methods and Weed Management Practices Affect Grain Yield and Weed Dynamics in Temperate Rice
    MDPI AG ; 2021
    In:  Agronomy Vol. 11, No. 11 ( 2021-10-26), p. 2137-
    Details
    In: Agronomy, MDPI AG, Vol. 11, No. 11 ( 2021-10-26), p. 2137-
    Abstract: Higher demand and cost of labor and water shortage have forced the farmers to look for an alternate method of cultivation in rice as a substitute to the existing conventional transplanting. Dry direct seeding and water seeding have emerged as better alternatives over transplanting method. These methods not only result in labor saving, but also result in significant water saving in rice. These are important adaptation strategies to the impending climate change. However, the direct seeding method is confronted with severe weed infestation and yield losses if weeds are not managed well. Against this backdrop, a field study was undertaken during kharif seasons of 2019 and 2020 to evaluate the effect of crop establishment methods and weed management practices on rice and its associated weed flora. The results demonstrated that grain yields obtained under water seeding (WS) were statistically at par with transplanting (CT), but significantly superior to dry direct seeding (DDSR). Yield attributes were significantly superior in WS as compared DDSR, but were at par with CT. Weed density followed the order of DDSR 〉 WS 〉 CT. With the advancement in age of the crop, sedges dominated in DDSR, whereas broad-leafweeds (BLW) dominated in WS and CT methods of establishment. All the herbicides reduced the weed density significantly as compared to weedy check. Penoxulam (PE) reduced the weed density and weed dry matter on an average by 91% and 92% at 30 DAS/DAT over weedy check, respectively. PE proved significantly superior in controlling all the sedges and grasses but was less effective against BLW. Maximum reduction in yield due to weeds was observed in weedy check (WC) (58%) and the lowest was observed in PE (3%). Application of PE @ 22.5 g ha−1 under the WS method of crop establishment resulted in highest average weed control efficiency and grain yield.
    Type of Medium: Online Resource
    ISSN: 2073-4395
    URL: Article
    DOI: 10.3390/agronomy11112137
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2607043-1
    SSG: 23
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  • 3
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    Online Resource
    Bioactive Secondary Metabolites from Trichoderma spp. against Phytopathogenic Fungi
    MDPI AG ; 2020
    In:  Microorganisms Vol. 8, No. 6 ( 2020-05-29), p. 817-
    Details
    In: Microorganisms, MDPI AG, Vol. 8, No. 6 ( 2020-05-29), p. 817-
    Abstract: Phytopathogenic fungi, causing significant economic and production losses, are becoming a serious threat to global food security. Due to an increase in fungal resistance and the hazardous effects of chemical fungicides to human and environmental health, scientists are now engaged to explore alternate non-chemical and ecofriendly management strategies. The use of biocontrol agents and their secondary metabolites (SMs) is one of the potential approaches used today. Trichoderma spp. are well known biocontrol agents used globally. Many Trichoderma species are the most prominent producers of SMs with antimicrobial activity against phytopathogenic fungi. Detailed information about these secondary metabolites, when grouped together, enhances the understanding of their efficient utilization and further exploration of new bioactive compounds for the management of plant pathogenic fungi. The current literature provides the information about SMs of Trichoderma spp. in a different context. In this review, we summarize and group different antifungal SMs of Trichoderma spp. against phytopathogenic fungi along with a comprehensive overview of some aspects related to their chemistry and biosynthesis. Moreover, a brief overview of the biosynthesis pathway, action mechanism, and different approaches for the analysis of SMs and the factors affecting the regulation of SMs in Trichoderma is also discussed.
    Type of Medium: Online Resource
    ISSN: 2076-2607
    URL: Article
    DOI: 10.3390/microorganisms8060817
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2720891-6
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  • 4
    Online Resource
    Online Resource
    Incorporating Noise Robustness in Speech Command Recognition by Noise Augmentation of Training Data
    MDPI AG ; 2020
    In:  Sensors Vol. 20, No. 8 ( 2020-04-19), p. 2326-
    Details
    In: Sensors, MDPI AG, Vol. 20, No. 8 ( 2020-04-19), p. 2326-
    Abstract: The advent of new devices, technology, machine learning techniques, and the availability of free large speech corpora results in rapid and accurate speech recognition. In the last two decades, extensive research has been initiated by researchers and different organizations to experiment with new techniques and their applications in speech processing systems. There are several speech command based applications in the area of robotics, IoT, ubiquitous computing, and different human-computer interfaces. Various researchers have worked on enhancing the efficiency of speech command based systems and used the speech command dataset. However, none of them catered to noise in the same. Noise is one of the major challenges in any speech recognition system, as real-time noise is a very versatile and unavoidable factor that affects the performance of speech recognition systems, particularly those that have not learned the noise efficiently. We thoroughly analyse the latest trends in speech recognition and evaluate the speech command dataset on different machine learning based and deep learning based techniques. A novel technique is proposed for noise robustness by augmenting noise in training data. Our proposed technique is tested on clean and noisy data along with locally generated data and achieves much better results than existing state-of-the-art techniques, thus setting a new benchmark.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s20082326
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2052857-7
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  • 5
    Online Resource
    Online Resource
    Kalman Filtering and Bipartite Matching Based Super-Chained Tracker Model for Online Multi Object Tracking in Video Sequences
    MDPI AG ; 2022
    In:  Applied Sciences Vol. 12, No. 19 ( 2022-09-23), p. 9538-
    Details
    In: Applied Sciences, MDPI AG, Vol. 12, No. 19 ( 2022-09-23), p. 9538-
    Abstract: Object tracking has gained importance in various applications especially in traffic monitoring, surveillance and security, people tracking, etc. Previous methods of multiobject tracking (MOT) carry out detections and perform object tracking. Although not optimal, these frameworks perform the detection and association of objects with feature extraction separately. In this article, we have proposed a Super Chained Tracker (SCT) model, which is convenient and online and provides better results when compared with existing MOT methods. The proposed model comprises subtasks, object detection, feature manipulation, and using representation learning into one end-to-end solution. It takes adjacent frames as input, converting each frame into bounding boxes’ pairs and chaining them up with Intersection over Union (IoU), Kalman filtering, and bipartite matching. Attention is made by object attention, which is in paired box regression branch, caused by the module of object detection, and a module of ID verification creates identity attention. The detections from these branches are linked together by IoU matching, Kalman filtering, and bipartite matching. This makes our SCT speedy, simple, and effective enough to achieve a Multiobject Tracking Accuracy (MOTA) of 68.4% and Identity F1 (IDF1) of 64.3% on the MOT16 dataset. We have studied existing tracking techniques and analyzed their performance in this work. We have achieved more qualitative and quantitative tracking results than other existing techniques with relatively improved margins.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app12199538
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704225-X
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  • 6
    Online Resource
    Online Resource
    Multi-Layered Non-Local Bayes Model for Lung Cancer Early Diagnosis Prediction with the Internet of Medical Things
    MDPI AG ; 2023
    In:  Bioengineering Vol. 10, No. 2 ( 2023-01-20), p. 138-
    Details
    In: Bioengineering, MDPI AG, Vol. 10, No. 2 ( 2023-01-20), p. 138-
    Abstract: The Internet of Things (IoT) has been influential in predicting major diseases in current practice. The deep learning (DL) technique is vital in monitoring and controlling the functioning of the healthcare system and ensuring an effective decision-making process. In this study, we aimed to develop a framework implementing the IoT and DL to identify lung cancer. The accurate and efficient prediction of disease is a challenging task. The proposed model deploys a DL process with a multi-layered non-local Bayes (NL Bayes) model to manage the process of early diagnosis. The Internet of Medical Things (IoMT) could be useful in determining factors that could enable the effective sorting of quality values through the use of sensors and image processing techniques. We studied the proposed model by analyzing its results with regard to specific attributes such as accuracy, quality, and system process efficiency. In this study, we aimed to overcome problems in the existing process through the practical results of a computational comparison process. The proposed model provided a low error rate (2%, 5%) and an increase in the number of instance values. The experimental results led us to conclude that the proposed model can make predictions based on images with high sensitivity and better precision values compared to other specific results. The proposed model achieved the expected accuracy (81%, 95%), the expected specificity (80%, 98%), and the expected sensitivity (80%, 99%). This model is adequate for real-time health monitoring systems in the prediction of lung cancer and can enable effective decision-making with the use of DL techniques.
    Type of Medium: Online Resource
    ISSN: 2306-5354
    URL: Article
    DOI: 10.3390/bioengineering10020138
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2746191-9
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  • 7
    Online Resource
    Online Resource
    Systematic Assessment of Visible-Light-Driven Microspherical V2O5 Photocatalyst for the Removal of Hazardous Organosulfur Compounds from Diesel
    MDPI AG ; 2021
    In:  Nanomaterials Vol. 11, No. 11 ( 2021-10-30), p. 2908-
    Details
    In: Nanomaterials, MDPI AG, Vol. 11, No. 11 ( 2021-10-30), p. 2908-
    Abstract: The organosulfur compounds present in liquid fuels are hazardous for health, asset, and the environment. The photocatalytic desulfurization technique works at ordinary conditions and removes the requirement of hydrogen, as it is an expensive gas, highly explosive, with a broader flammability range and is declared the most hazardous gas within a petroleum refinery, with respect to flammability. The projected work is based on the synthesis of V2O5 microspheres for photocatalytic oxidation for the straight-run diesel (SRD) and diesel oil blend (DOB). The physicochemical properties of V2O5 microspheres were examined by FT-IR, Raman, UV-vis DRS, SEM, and Photoluminescence evaluations. The as-synthesized photocatalyst presented a trivial unit size, a narrow bandgap, appropriate light-capturing capability, and sufficient active sites. The desulfurization study discovered that the anticipated technique is substantial in desulfurizing DOB up to 37% in 180 min using methanol as an interfacing agent. Furthermore, the outcome of employing a range of polar interfacing solvents was examined, and the 2-ethoxyethanol elevated the desulfurization degree up to 51.3%. However, the anticipated technology is constrained for its application in sulfur removal from SRD. Additionally, the mechanism for a photocatalytic reaction was seen in strong agreement with pseudo-first-order kinetics. The investigated photocatalyst exhibited a compromised recyclability and regeneration tendency.
    Type of Medium: Online Resource
    ISSN: 2079-4991
    URL: Article
    DOI: 10.3390/nano11112908
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2662255-5
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