Publications by authors named "I Ganesh Moorthy"

20 Publications

Versatile image processing technique for fuel science: A review.

Sci Total Environ 2021 Aug 16;780:146469. Epub 2021 Mar 16.

School of Renewable Energy, Maejo University, Chiang Mai 50290, Thailand; College of Medical and Health Science, Asia University, Taichung, Taiwan. Electronic address:

The evolution of computer vision and image processing system paved the way that any technologists can extract quantitative data sets from the visual results of an image. Digital image processing (DIP) technique precisely measures and quantifies the image and eliminates the subjectivity of manual interpretation. DIP is a non-destructive, inexpensive and rapid method that has been used by many researchers in various applications of biofuel. In fuel science, DIP and artificial intelligence (AI) techniques have been successfully applied for the classification of biodiesel, selection of biomass for biofuel production. DIP can be used in the combustion process and its control parameters, gas leakage, monitoring fuel reactant conversion reactions, impurities present and adulteration of fuel, also automation process of a fuel injection system. This review gives an overview of the applications of image processing in fuel science.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.scitotenv.2021.146469DOI Listing
August 2021

Optimization of ultrasound assisted extraction of pectin from custard apple peel: Potential and new source.

Carbohydr Polym 2019 Dec 23;225:115240. Epub 2019 Aug 23.

Department of Molecular Microbiology, Madurai Kamaraj University, Palkalai Nagar, Madurai, Tamil Nadu, 625021, India.

Pectin was extracted from the waste custard apple peel using ultrasound technique and optimized the extraction process by RSM. The various significant process parameters such as liquid-solid ratio, ultra-sonication time, temperature and pH of solution were studied in the range of 10-25 mL g, 10-30 min, 50-80 °C, and 1-3, respectively. The maximum yield of pectin (8.93%) was attained at the optimum condition of 23.52 mL g of liquid-solid ratio, 18.04  min of ultra-sonication time, 63.22 °C of temperature and 2.3 pH of solution. The extracted and commercially available fresh pectin (for comparison purposes) were characterized by various analytical techniques namely, FTIR, DSC, XRD, SEM, and NMR to evaluate their functional groups, thermal properties, crystallinities, morphological and structural characteristics, respectively. The extracted pectin was a toxic free compound as determined by its anti nutritional property study and about 20 mg/mL of antioxidant presented in it.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.carbpol.2019.115240DOI Listing
December 2019

Estimating the global distribution of field size using crowdsourcing.

Glob Chang Biol 2019 01 22;25(1):174-186. Epub 2018 Nov 22.

University of Canterbury, Christchurch, New Zealand.

There is an increasing evidence that smallholder farms contribute substantially to food production globally, yet spatially explicit data on agricultural field sizes are currently lacking. Automated field size delineation using remote sensing or the estimation of average farm size at subnational level using census data are two approaches that have been used. However, both have limitations, for example, automatic field size delineation using remote sensing has not yet been implemented at a global scale while the spatial resolution is very coarse when using census data. This paper demonstrates a unique approach to quantifying and mapping agricultural field size globally using crowdsourcing. A campaign was run in June 2017, where participants were asked to visually interpret very high resolution satellite imagery from Google Maps and Bing using the Geo-Wiki application. During the campaign, participants collected field size data for 130 K unique locations around the globe. Using this sample, we have produced the most accurate global field size map to date and estimated the percentage of different field sizes, ranging from very small to very large, in agricultural areas at global, continental, and national levels. The results show that smallholder farms occupy up to 40% of agricultural areas globally, which means that, potentially, there are many more smallholder farms in comparison with the two different current global estimates of 12% and 24%. The global field size map and the crowdsourced data set are openly available and can be used for integrated assessment modeling, comparative studies of agricultural dynamics across different contexts, for training and validation of remote sensing field size delineation, and potential contributions to the Sustainable Development Goal of Ending hunger, achieve food security and improved nutrition and promote sustainable agriculture.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1111/gcb.14492DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7379266PMC
January 2019

A global reference database of crowdsourced cropland data collected using the Geo-Wiki platform.

Sci Data 2017 09 26;4:170136. Epub 2017 Sep 26.

Politecnico di Milano, Milano, Italy.

A global reference data set on cropland was collected through a crowdsourcing campaign using the Geo-Wiki crowdsourcing tool. The campaign lasted three weeks, with over 80 participants from around the world reviewing almost 36,000 sample units, focussing on cropland identification. For quality assessment purposes, two additional data sets are provided. The first is a control set of 1,793 sample locations validated by students trained in satellite image interpretation. This data set was used to assess the quality of the crowd as the campaign progressed. The second data set contains 60 expert validations for additional evaluation of the quality of the contributions. All data sets are split into two parts: the first part shows all areas classified as cropland and the second part shows cropland average per location and user. After further processing, the data presented here might be suitable to validate and compare medium and high resolution cropland maps generated using remote sensing. These could also be used to train classification algorithms for developing new maps of land cover and cropland extent.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/sdata.2017.136DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5613736PMC
September 2017

Optimization of dextran production by Weissella cibaria NITCSK4 using Response Surface Methodology-Genetic Algorithm based technology.

Carbohydr Polym 2017 Oct 21;174:103-110. Epub 2017 Jun 21.

Department of Chemical Engineering, National Institute of Technology Calicut, Kerala-673601, India. Electronic address:

The most influencing factor on dextran production by Weissella cibaria NITCSK4 were screened using Plackett Burman design at 95% confidence limit with higher value of co-efficient of determination (R) 99.58%. The combined effects of significant factors, namely, sucrose, temperature, dipotassium hydrogen phosphate (KHPO) and yeast extract were studied and optimized using Response Surface Methodology (RSM). The input parameters of non-linear models predicted by RSM were subsequently optimized using the genetic algorithm (GA) for obtaining a maximum dextran yield. The maximum yield was obtained with sucrose concentration of 15.78%, yeast extract 1.27%, KHPO 1.25%, and at 26°C. The predicted conditions were experimentally validated and 43.79mg/ml of dextran was produced. The dextran yield was 51% higher as compared to unoptimized medium. The molecular weight of resulting dextran produced at 26°C is >2000kDa. The NMR spectroscopic analysis demonstrated that the NITCSK4 produced linear dextran with predominant α (1-6) linkage.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.carbpol.2017.06.021DOI Listing
October 2017
-->