Effect of addition of proteins on the production of amorphous sucrose powder through spray drying
- Adhikari, Benu, Howes, Tony, Bhandari, Bhesh, Langrish, Tim
- Authors: Adhikari, Benu , Howes, Tony , Bhandari, Bhesh , Langrish, Tim
- Date: 2009
- Type: Text , Journal article
- Relation: Journal of Food Engineering Vol. 94, no. 2 (2009), p. 144 -153
- Full Text:
- Reviewed:
- Description: Spray drying trials were carried out to produce amorphous sucrose powder. Firstly, pure sucrose solutions were prepared and spray dried at inlet and outlet temperatures of 160 °C and 70 °C, respectively. No amorphous powder was obtained and only 18% of the feed solids were recovered in a crystalline form, with the remaining solids lost as wall deposits. Secondly, sodium caseinate (Na-C) and hydrolyzed whey protein isolate (WPI) were added in sucrose:protein solid ratios of (99.5:0.5) and (99.0:1.0) and drying trials were conducted maintaining the initial drying conditions. In both these cases, greater than 80% of the feed solids were recovered in an amorphous form. The increase in protein concentration from 0.5% to 1% on dry solid basis did not further improve the recovery. The remarkable increase in recovery from a small addition of protein is attributed to preferential migration of protein molecules to the droplet-air interface, and the subsequent transformation of the thin, protein-rich film into a non-sticky glassy state upon drying. This film overcomes both the particle-to-particle and particle-to-wall stickiness. The measured bulk glass rubber transition temperature (Tg-r) values of the bulk mixtures at various moisture contents were very close to the corresponding mean glass transition temperature (Tg) of the pure sucrose indicating that surface layer Tg rather than the bulk Tg is responsible for this. Electron spectroscopy for chemical analysis (ESCA) studies revealed that the particle surface was covered by 50-58% (by mass) proteins. The calculated glass transition temperature of the surface layer (Tg,surface layer), based on the surface elemental compositions, showed that the Tg,surface layer has increased to the extent that it remained within the safe drying envelope of spray drying. © 2009 Elsevier Ltd. All rights reserved.
- Authors: Adhikari, Benu , Howes, Tony , Bhandari, Bhesh , Langrish, Tim
- Date: 2009
- Type: Text , Journal article
- Relation: Journal of Food Engineering Vol. 94, no. 2 (2009), p. 144 -153
- Full Text:
- Reviewed:
- Description: Spray drying trials were carried out to produce amorphous sucrose powder. Firstly, pure sucrose solutions were prepared and spray dried at inlet and outlet temperatures of 160 °C and 70 °C, respectively. No amorphous powder was obtained and only 18% of the feed solids were recovered in a crystalline form, with the remaining solids lost as wall deposits. Secondly, sodium caseinate (Na-C) and hydrolyzed whey protein isolate (WPI) were added in sucrose:protein solid ratios of (99.5:0.5) and (99.0:1.0) and drying trials were conducted maintaining the initial drying conditions. In both these cases, greater than 80% of the feed solids were recovered in an amorphous form. The increase in protein concentration from 0.5% to 1% on dry solid basis did not further improve the recovery. The remarkable increase in recovery from a small addition of protein is attributed to preferential migration of protein molecules to the droplet-air interface, and the subsequent transformation of the thin, protein-rich film into a non-sticky glassy state upon drying. This film overcomes both the particle-to-particle and particle-to-wall stickiness. The measured bulk glass rubber transition temperature (Tg-r) values of the bulk mixtures at various moisture contents were very close to the corresponding mean glass transition temperature (Tg) of the pure sucrose indicating that surface layer Tg rather than the bulk Tg is responsible for this. Electron spectroscopy for chemical analysis (ESCA) studies revealed that the particle surface was covered by 50-58% (by mass) proteins. The calculated glass transition temperature of the surface layer (Tg,surface layer), based on the surface elemental compositions, showed that the Tg,surface layer has increased to the extent that it remained within the safe drying envelope of spray drying. © 2009 Elsevier Ltd. All rights reserved.
- Ryves, David, Mills, Keely, Bennike, Ole, Brodersen, Klaus Peter, Lamb, Angela, Leng, Melanie, Russell, James, Ssemmanda, Immaculate
- Authors: Ryves, David , Mills, Keely , Bennike, Ole , Brodersen, Klaus Peter , Lamb, Angela , Leng, Melanie , Russell, James , Ssemmanda, Immaculate
- Date: 2011
- Type: Text , Journal article
- Relation: Quaternary Science Reviews Vol. 30, no. 5-6 (2011), p. 555-569
- Full Text: false
- Reviewed:
- Description: The last millennium is a key period for understanding environmental change in eastern Africa, as there is clear evidence of marked fluctuations in climate (effective moisture) that place modern concern with future climate change in a proper context, both in terms of environmental and societal impacts and responses. Here, we compare sediment records from two small, nearby, closed crater lakes in western Uganda (Lake Kasenda and Lake Wandakara), spanning the last 700 (Wandakara) and 1200 years (Kasenda) respectively. Multiproxy analyses of chemical sedimentary parameters (including C/N ratios, δ13C of bulk organic matter and δ13C and δ18O of authigenic carbonates) and biotic remains (diatoms, aquatic macrofossils, chironomids) suggest that Kasenda has been sensitive to climate over much of this period, and has shown substantial fluctuations in conductivity, while Wandakara has a more muted response, likely due to the increasing dominance of human activity as a driver of change within the lake and catchment over the length of our record. Evidence from both records, however, supports the idea that lake levels were low from ~AD 700-1000 AD, with increasing aridity from AD 1100-1600, and brief wet phases around AD 1000 and 1400. Wetter conditions are recorded in the 1700s, but drought returned by the end of the century and into the early 1800s, becoming wetter again from the mid-1800s. Comparison with other records across eastern Africa suggests that while some events are widespread (e.g. aridity beginning ~ AD 1100), at other times there is a more complex spatial signature (e.g. in the 1200s to 1300s, and from the 1400s to 1600s). This study highlights the important role of catchment-specific factors (e.g. lakemorphometry, catchment size, and human impact) in modulating the sensitivity of proxies, and lake records, as indicators of environmental change, and potential hazards when regional inference is based on a single site or proxy. © 2011 Elsevier Ltd.
- Reynolds, Alicia, Verheyen, Vincent, Adeloju, Samuel, Chaffee, Alan, Meuleman, Erik
- Authors: Reynolds, Alicia , Verheyen, Vincent , Adeloju, Samuel , Chaffee, Alan , Meuleman, Erik
- Date: 2014
- Type: Text , Journal article
- Relation: Industrial and Engineering Chemistry Research Vol. 53, no. 12 (2014), p. 4805-4811
- Full Text: false
- Reviewed:
- Description: The availability of reliable analytical methods for measuring amine concentrations is necessary for optimum operation of aqueous amine CO 2 separation systems being employed for postcombustion capture (PCC) of CO2. A GC-FID (gas chromatography with flame ionization detection) method is described for the reliable quantification of 30% (w/w) monoethanolamine (MEA) in severely degraded solvent samples. The observation of intermittent splitting of the MEA peak was a major concern with this approach. The use of a wide-bore column led to improved MEA peak resolution and peak shape. The reliability and robustness of the GC-FID method were assessed by analyzing degraded 30% (w/w) MEA solvent samples from CSIRO's pilot plant at AGL's Loy Yang power station in Victoria, Australia. The results were compared with those obtained by titration and total organic carbon (TOC) measurements of the same samples. The MEA concentrations obtained by the GC-FID and titration methods were statistically similar. In contrast, the MEA concentrations calculated from TOC were consistently higher than those obtained by both GC-FID and titration. © 2014 American Chemical Society.
Effects of brown coal fly ash on 30% monoethanolamine CO₂ capture systems
- Authors: Chowdhury, Mohammad
- Date: 2019
- Type: Text , Thesis , PhD
- Full Text:
- Description: Accumulation of fly ash during post-combustion capture (PCC) of CO2 is an emerging concern. This work assesses concerns that soluble ash components (e.g. Na, Ca, Mg) increase conductivity of amine systems increasing corrosion rates, and decreasing CO2 capture e ciency; slightly soluble metals ions (e.g. Fe) may catalyse amine oxidation; and insoluble ash components cause erosion and blockages in the PCC plants as well as providing catalytic surfaces. Loy Yang brown-coal y ashes (using XRD, SEM, EDS and ICP-MS) are rst characterised and separated into soluble, insoluble and char fractions. The e ect of each fraction on MEA oxidation (measured by UV-vis and organic acid formation) and corrosion is determined using lab-scale experiments in static and stirred pressurised reactors at simulated PCC stripper conditions. Fly ash was three times more soluble in severely oxidising conditions compared to mild 30% MEA extractions. Vantho te represents 10-20% of the y ash and was the main source of sodium, calcium and magnesium ions while Szmolnockite was a source of iron. Iron solubility was dependent on conditions, with 5% soluble in aqueous MEA and 10% in simulated desorber conditions. The soluble fraction was the only ash fraction to signi cantly promote MEA oxidation. Aged pall rings from a PCC pilot plant had severe grain boundary corrosion and chromiumoxide depletion. Grain boundary corrosion was less severe in pall rings under severely oxidising conditions. The e ects of soluble ash were unclear while organic acids promoted pitting. Fly ash is an important source of soluble sodium, calcium and iron into 30% MEA. The insoluble fraction had minimal impact on MEA oxidation and corrosion, suggesting that it was inert. Soluble ash fractions increased corrosion severity and promoted MEA oxidation. This work shows that deep y ash removal prior to PCC is particularly important for ashes with high solubility in the CO2 absorption system.
- Description: Doctor of Philosophy
- Authors: Chowdhury, Mohammad
- Date: 2019
- Type: Text , Thesis , PhD
- Full Text:
- Description: Accumulation of fly ash during post-combustion capture (PCC) of CO2 is an emerging concern. This work assesses concerns that soluble ash components (e.g. Na, Ca, Mg) increase conductivity of amine systems increasing corrosion rates, and decreasing CO2 capture e ciency; slightly soluble metals ions (e.g. Fe) may catalyse amine oxidation; and insoluble ash components cause erosion and blockages in the PCC plants as well as providing catalytic surfaces. Loy Yang brown-coal y ashes (using XRD, SEM, EDS and ICP-MS) are rst characterised and separated into soluble, insoluble and char fractions. The e ect of each fraction on MEA oxidation (measured by UV-vis and organic acid formation) and corrosion is determined using lab-scale experiments in static and stirred pressurised reactors at simulated PCC stripper conditions. Fly ash was three times more soluble in severely oxidising conditions compared to mild 30% MEA extractions. Vantho te represents 10-20% of the y ash and was the main source of sodium, calcium and magnesium ions while Szmolnockite was a source of iron. Iron solubility was dependent on conditions, with 5% soluble in aqueous MEA and 10% in simulated desorber conditions. The soluble fraction was the only ash fraction to signi cantly promote MEA oxidation. Aged pall rings from a PCC pilot plant had severe grain boundary corrosion and chromiumoxide depletion. Grain boundary corrosion was less severe in pall rings under severely oxidising conditions. The e ects of soluble ash were unclear while organic acids promoted pitting. Fly ash is an important source of soluble sodium, calcium and iron into 30% MEA. The insoluble fraction had minimal impact on MEA oxidation and corrosion, suggesting that it was inert. Soluble ash fractions increased corrosion severity and promoted MEA oxidation. This work shows that deep y ash removal prior to PCC is particularly important for ashes with high solubility in the CO2 absorption system.
- Description: Doctor of Philosophy
Comparative analysis of machine and deep learning models for soil properties prediction from hyperspectral visual band
- Datta, Dristi, Paul, Manoranjan, Murshed, Manzur, Teng, Shyh Wei, Schmidtke, Leigh
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2023
- Type: Text , Journal article
- Relation: Environments Vol. 10, no. 5 (2023), p. 77
- Full Text:
- Reviewed:
- Description: Estimating various properties of soil, including moisture, carbon, and nitrogen, is crucial for studying their correlation with plant health and food production. However, conventional methods such as oven-drying and chemical analysis are laborious, expensive, and only feasible for a limited land area. With the advent of remote sensing technologies like multi/hyperspectral imaging, it is now possible to predict soil properties non-invasive and cost-effectively for a large expanse of bare land. Recent research shows the possibility of predicting those soil contents from a wide range of hyperspectral data using good prediction algorithms. However, these kinds of hyperspectral sensors are expensive and not widely available. Therefore, this paper investigates different machine and deep learning techniques to predict soil nutrient properties using only the red (R), green (G), and blue (B) bands data to propose a suitable machine/deep learning model that can be used as a rapid soil test. Another objective of this research is to observe and compare the prediction accuracy in three cases i. hyperspectral band ii. full spectrum of the visual band, and iii. three-channel of RGB band and provide a guideline to the user on which spectrum information they should use to predict those soil properties. The outcome of this research helps to develop a mobile application that is easy to use for a quick soil test. This research also explores learning-based algorithms with significant feature combinations and their performance comparisons in predicting soil properties from visual band data. For this, we also explore the impact of dimensional reduction (i.e., principal component analysis) and transformations (i.e., empirical mode decomposition) of features. The results show that the proposed model can comparably predict the soil contents from the three-channel RGB data.
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2023
- Type: Text , Journal article
- Relation: Environments Vol. 10, no. 5 (2023), p. 77
- Full Text:
- Reviewed:
- Description: Estimating various properties of soil, including moisture, carbon, and nitrogen, is crucial for studying their correlation with plant health and food production. However, conventional methods such as oven-drying and chemical analysis are laborious, expensive, and only feasible for a limited land area. With the advent of remote sensing technologies like multi/hyperspectral imaging, it is now possible to predict soil properties non-invasive and cost-effectively for a large expanse of bare land. Recent research shows the possibility of predicting those soil contents from a wide range of hyperspectral data using good prediction algorithms. However, these kinds of hyperspectral sensors are expensive and not widely available. Therefore, this paper investigates different machine and deep learning techniques to predict soil nutrient properties using only the red (R), green (G), and blue (B) bands data to propose a suitable machine/deep learning model that can be used as a rapid soil test. Another objective of this research is to observe and compare the prediction accuracy in three cases i. hyperspectral band ii. full spectrum of the visual band, and iii. three-channel of RGB band and provide a guideline to the user on which spectrum information they should use to predict those soil properties. The outcome of this research helps to develop a mobile application that is easy to use for a quick soil test. This research also explores learning-based algorithms with significant feature combinations and their performance comparisons in predicting soil properties from visual band data. For this, we also explore the impact of dimensional reduction (i.e., principal component analysis) and transformations (i.e., empirical mode decomposition) of features. The results show that the proposed model can comparably predict the soil contents from the three-channel RGB data.
- «
- ‹
- 1
- ›
- »