Visweswara Rao Pasupuleti

Bio: Visweswara Rao Pasupuleti is an academic researcher from Universiti Malaysia Sabah. The author has contributed to research in topics: Chemistry & In vivo. The author has an hindex of 3, co-authored 14 publications receiving 51 citations.

A critical review on computer vision and artificial intelligence in food industry

Abstract: Emerging technologies such as computer vision and Artificial Intelligence (AI) are estimated to leverage the accessibility of big data for active training and yielding operational real time smart machines and predictable models. This phenomenon of applying vision and learning methods for the improvement of food industry is termed as computer vision and AI driven food industry. This review contributes to provide an insight into state-of-the-art AI and computer vision technologies that can assist farmers in agriculture and food processing. This paper investigates various scenarios and use cases of machine learning, machine vision and deep learning in global perspective with the lens of sustainability. It explains the increasing demand towards the AgTech industry using computer vision and AI which might be a path towards sustainable food production to feed the future. Also, this review tosses some implications regarding challenges and recommendations in inclusion of technologies in real time farming, substantial global policies and investments. Finally, the paper discusses the possibility of using Fourth Industrial Revolution [4.0 IR] technologies such as deep learning and computer vision robotics as a key for sustainable food production.

Ultrasonication-mediated nitrogen-doped multiwalled carbon nanotubes involving carboxy methylcellulose composite for solid-state supercapacitor applications

Abstract: In this study, a novel nanohybrid composite containing nitrogen-doped multiwalled carbon nanotubes/carboxymethylcellulose (N-MWCNT/CMC) was synthesized for supercapacitor applications. The synthesized composite materials were subjected to an ultrasonication-mediated solvothermal hydrothermal reaction. The synthesized nanohybrid composite electrode material was characterized using analytical methods to confirm its structure and morphology. The electrochemical properties of the composite electrode were investigated using cyclic voltammetry (CV), galvanic charge–discharge, and electrochemical impedance spectroscopy (EIS) using a 3 M KOH electrolyte. The fabricated composite material exhibited unique electrochemical properties by delivering a maximum specific capacitance of approximately 274 F g−1 at a current density of 2 A g−1. The composite electrode displayed high cycling stability of 96% after 4000 cycles at 2 A g−1, indicating that it is favorable for supercapacitor applications.

Synthesis of novel cytotoxic tetracyclic acridone derivatives and study of their molecular docking, ADMET, QSAR, bioactivity and protein binding properties.

Abstract: Acridone based synthetic and natural products with inherent anticancer activity advancing the research and generating a large number of structurally diversified compounds. In this sequence we have designed, synthesized a series of tetracyclic acridones with amide framework viz., 3-(alkyloyl/ aryloyl/ heteroaryloyl/ heteroaryl)-2,3-dihydropyrazino[3,2,1-de]acridin-7(1H)-ones and screened for their in vitro anti-cancer activity. The in vitro study revealed that compounds with cyclopropyl-acetyl, benzoyl, p-hydroxybenzoyl, p-(trifluoromethyl)benzoyl, p-fluorobenzoyl, m-fluorobenzoyl, picolinoyl, 6-methylpicolinoyl and 3-nicotinoyl groups are active against HT29, MDAMB231 and HEK293T cancer cell lines. The molecular docking studies performed for them against 4N5Y, HT29 and 2VWD revealed the potential ligand-protein binding interactions among the neutral aminoacid of the enzymes and carbonyl groups of the title compounds with a binding energy ranging from - 8.1394 to - 6.9915 kcal/mol. In addition, the BSA protein binding assay performed for them has confirmed their interaction with target proteins through strong binding to BSA macromolecule. The additional studies like ADMET, QSAR, bioactivity scores, drug properties and toxicity risks ascertained them as newer drug candidates. This study had added a new collection of piperazino fused acridone derivatives to the existing array of other nitrogen heterocyclic fused acridone derivatives as anticancer agents.

Multifaceted phytogenic silver nanoparticles by an insectivorous plant Drosera spatulata Labill var. bakoensis and its potential therapeutic applications

Abstract: The current investigation highlights the green synthesis of silver nanoparticles (AgNPs) by the insectivorous plant Drosera spatulata Labill var. bakoensis, which is the first of its kind. The biosynthesized nanoparticles revealed a UV visible surface plasmon resonance (SPR) band at 427 nm. The natural phytoconstituents which reduce the monovalent silver were identified by FTIR. The particle size of the Ds-AgNPs was detected by the Nanoparticle size analyzer confirms that the average size of nanoparticles was around 23 ± 2 nm. Ds-AgNPs exhibit high stability because of its high negative zeta potential (− 34.1 mV). AFM studies also revealed that the Ds-AgNPs were spherical in shape and average size ranges from 10 to 20 ± 5 nm. TEM analysis also revealed that the average size of Ds-AgNPs was also around 21 ± 4 nm and the shape is roughly spherical and well dispersed. The crystal nature of Ds-AgNPs was detected as a face-centered cube by the XRD analysis. Furthermore, studies on antibacterial and antifungal activities manifested outstanding antimicrobial activities of Ds-AgNPs compared with standard antibiotic Amoxyclav. In addition, demonstration of superior free radical scavenging efficacy coupled with potential in vitro cytotoxic significance on Human colon cancer cell lines (HT-29) suggests that the Ds-AgNPs attain excellent multifunctional therapeutic applications.

Image Processing

Abstract: MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

The digitization of agricultural industry – a systematic literature review on agriculture 4.0

Abstract: • SLR is conducted using PRISMA approach and148 articles are selected and critically analyzed. • The results show the extent of digital technologies adoption in agriculture. • The potential benefits of digital technologies and roadblocks hindering their implementation in agriculture sector are identified and discussed. • The study will positively impact the research around agriculture 4.0. Agriculture is considered one of the most important sectors that play a strategic role in ensuring food security. However, with the increasing world's population, agri-food demands are growing — posing the need to switch from traditional agricultural methods to smart agriculture practices, also known as agriculture 4.0. To fully benefit from the potential of agriculture 4.0, it is significant to understand and address the problems and challenges associated with it. This study, therefore, aims to contribute to the development of agriculture 4.0 by investigating the emerging trends of digital technologies in the agricultural industry. For this purpose, a systematic literature review based on Protocol of Preferred Reporting Items for Systematic Reviews and Meta-Analyses is conducted to analyse the scientific literature related to crop farming published in the last decade. After applying the protocol, 148 papers were selected and the extent of digital technologies adoption in agriculture was examined in the context of service type, technology readiness level, and farm type. The results have shown that digital technologies such as autonomous robotic systems, internet of things, and machine learning are significantly explored and open-air farms are frequently considered in research studies (69%), contrary to indoor farms (31%). Moreover, it is observed that most use cases are still in the prototypical phase. Finally, potential roadblocks to the digitization of the agriculture sector were identified and classified at technical and socio-economic levels. This comprehensive review results in providing useful information on the current status of digital technologies in agriculture along with prospective future opportunities.

Internet of Nonthermal Food Processing Technologies (IoNTP): Food Industry 4.0 and Sustainability

Abstract: With the introduction of Industry 4.0, and smart factories accordingly, there are new opportunities to implement elements of industry 4.0 in nonthermal processing. Moreover, with application of Internet of things (IoT), smart control of the process, big data optimization, as well as sustainable production and monitoring, there is a new era of Internet of nonthermal food processing technologies (IoNTP). Nonthermal technologies include high power ultrasound, pulsed electric fields, high voltage electrical discharge, high pressure processing, UV-LED, pulsed light, e-beam, and advanced thermal food processing techniques include microwave processing, ohmic heating and high-pressure homogenization. The aim of this review was to bring in front necessity to evaluate possibilities of implementing smart sensors, artificial intelligence (AI), big data, additive technologies with nonthermal technologies, with the possibility to create smart factories together with strong emphasis on sustainability. This paper brings an overview on digitalization, IoT, additive technologies (3D printing), cloud data storage and smart sensors including two SWOT analysis associated with IoNTPs and sustainability. It is of high importance to perform life cycle assessment (LCA), to quantify (En)—environmental dimension; (So)—social dimension and (Ec)—economic dimension. SWOT analysis showed: potential for energy saving during food processing; optimized overall environmental performance; lower manufacturing cost; development of eco-friendly products; higher level of health and safety during food processing and better work condition for workers. Nonthermal and advanced thermal technologies can be applied also as sustainable techniques working in line with the sustainable development goals (SDGs) and Agenda 2030 issued by United Nations (UN).