Thermal properties of sweet sorghum bagasse as a function of moisture content

In this study, we examined the relationship between thermal properties and moisture content of sweet sorghum bagasse. A KD2 Pro Thermal Properties Analyzer was used to measure the thermal conductivity, thermal diffusivity, and volumetric specific heat of sweet sorghum bagasse across a range of moisture contents (8.52% - 28.62% w.b.). The thermal conductivity of sweet sorghum bagasse ranged from 0.0921 to 0.1096 W m-1 K-1 and increased with increase in moisture content through the range of 8.52% - 28.62% w.b. The thermal diffusivity ranged from 0.1225 to 0.1596 mm2 s-1 and increased with moisture content through the range of 8.52% - 28.62% w.b. The volumetric specific heat of sweet sorghum bagasse ranged from 0.7537 to 0.6869 MJ m-3 K-1 and decreased with moisture content through the range of 8.52% - 28.62% w.b. Quantitative empirical equations incorporating moisture content and room temperature dependent terms were developed to predict thermal conductivity, thermal diffusivity, and volumetric specific heat of sweet sorghum bagasse between 8.52% and 28.62% (w.b.) moisture content. The models are valid within the limits of the parameters used in the experiments.     

Effect of moisture content on thermal properties of cowpea flours

The effects of moisture content on thermal properties of cowpea flour were investigated on a range of 3.81% to 28.31% wet basis at 5% intervals, totaling six moisture levels, using a KD2 Pro Thermal Properties Analyzer.  The considered thermal properties were thermal conductivity, thermal diffusivity, and specific heat.  As the moisture content increased from 3.81% to 28.31 %, the thermal conductivity, thermal diffusivity, and specific heat increased from 0.109 to 0.213 W m-1 K-1, 0.099 to 0.136 mm2 s-1, and 1.092 to 1.573 MJ m-3 K-1, respectively.  The data are necessary for design of equipment for handling, transportation, processing, and storage of cowpea flour.   Keywords: cowpea, Vigna unguiculata, flour, thermal properties, KD2 Pro, moisture conten

Evaluation of an IUL Flash & Go Automated Colony Counter

An IUL Flash & Go automated colony counter was used to enumerate E. coli (ATCC 700728) colonies and its performance was compared with manual counting on spiral plates. A total of 85 plates were analyzed. Linear regression analysis and the log differences between the manual and automated counts were determined. The results were analyzed to evaluate the reliability and accuracy of the colony counter.  A correlation coefficient of 0.969, a slope of 0.932 and intercept of 0.25 all indicate a strong, linear relationship. The mean log value difference between the manual and Flash & Go count methods was -0.035. Of the 85 plates counted, 95% of the plates were within 0.15 log10 difference between the manual and Flash & Go automated counts. These results demonstrate that the Flash & Go automated colony counter is an effective, accurate and time saving alternative to the standard method of manual counting.      

Experimental determination of the electrical resistivity of beef

 A. K. Mahapatra, B. L. Jones, C. N. Nguyen, G. Kannan(Agricultural Research Station, Fort Valley State University, 1005 State University Drive, Fort Valley, GA 31030, USA) Abstract: Electrical resistivity properties of beef were investigated.  The resistivity behavior under three frequencies of 1, 10 and 100-kHz, different temperatures (5, 10, 15, and 20℃), different length and cross-sectional areas (width: 7 cm, two depths:  3 and 5 cm, and four lengths: 7, 11, 15, and 19 cm) were determined.  The electrical series circuit was found to be adequate to measure the resistivity properties of beef.  Samples with warmer temperatures offered much less resistance and the resistivity values obtained at temperatures 5℃ and below were not consistent.  Increasing temperature had a significant effect on the resistivity values of beef (p<0.05).  Increase in frequency did not have any significant effect on the resistivity properties of beef (p>0.05).  It was observed that resistivity was higher across the myofiber axes than along the myofiber axes.  However, there was no significant difference between the fiber directions in terms of resistivity (p>0.05).  The mean resistivity of beef at 20℃ for across the myofiber and along the myofiber directions was found to be 365.42 Ohms.cm and 346.67 Ohms.cm, respectively.Keywords: electrical resistivity, beef, anisotropy Citation: Mahapatra A. K., B. L. Jones, C. N. Nguyen, and G. Kannan.  Experimental determination of the electrical resistivity of beef.  Agric Eng Int: CIGR Journal, 2010, 12(3): 124-128. &nbsp

Physics Potential of the ICAL detector at the India-based Neutrino Observatory (INO)

The upcoming 50 kt magnetized iron calorimeter (ICAL) detector at the India-based Neutrino Observatory (INO) is designed to study the atmospheric neutrinos and antineutrinos separately over a wide range of energies and path lengths. The primary focus of this experiment is to explore the Earth matter effects by observing the energy and zenith angle dependence of the atmospheric neutrinos in the multi-GeV range. This study will be crucial to address some of the outstanding issues in neutrino oscillation physics, including the fundamental issue of neutrino mass hierarchy. In this document, we present the physics potential of the detector as obtained from realistic detector simulations. We describe the simulation framework, the neutrino interactions in the detector, and the expected response of the detector to particles traversing it. The ICAL detector can determine the energy and direction of the muons to a high precision, and in addition, its sensitivity to multi-GeV hadrons increases its physics reach substantially. Its charge identification capability, and hence its ability to distinguish neutrinos from antineutrinos, makes it an efficient detector for determining the neutrino mass hierarchy. In this report, we outline the analyses carried out for the determination of neutrino mass hierarchy and precision measurements of atmospheric neutrino mixing parameters at ICAL, and give the expected physics reach of the detector with 10 years of runtime. We also explore the potential of ICAL for probing new physics scenarios like CPT violation and the presence of magnetic monopoles.Comment: 139 pages, Physics White Paper of the ICAL (INO) Collaboration, Contents identical with the version published in Pramana - J. Physic

Challenges in QCD matter physics - The Compressed Baryonic Matter experiment at FAIR

Substantial experimental and theoretical efforts worldwide are devoted to explore the phase diagram of strongly interacting matter. At LHC and top RHIC energies, QCD matter is studied at very high temperatures and nearly vanishing net-baryon densities. There is evidence that a Quark-Gluon-Plasma (QGP) was created at experiments at RHIC and LHC. The transition from the QGP back to the hadron gas is found to be a smooth cross over. For larger net-baryon densities and lower temperatures, it is expected that the QCD phase diagram exhibits a rich structure, such as a first-order phase transition between hadronic and partonic matter which terminates in a critical point, or exotic phases like quarkyonic matter. The discovery of these landmarks would be a breakthrough in our understanding of the strong interaction and is therefore in the focus of various high-energy heavy-ion research programs. The Compressed Baryonic Matter (CBM) experiment at FAIR will play a unique role in the exploration of the QCD phase diagram in the region of high net-baryon densities, because it is designed to run at unprecedented interaction rates. High-rate operation is the key prerequisite for high-precision measurements of multi-differential observables and of rare diagnostic probes which are sensitive to the dense phase of the nuclear fireball. The goal of the CBM experiment at SIS100 (sqrt(s_NN) = 2.7 - 4.9 GeV) is to discover fundamental properties of QCD matter: the phase structure at large baryon-chemical potentials (mu_B > 500 MeV), effects of chiral symmetry, and the equation-of-state at high density as it is expected to occur in the core of neutron stars. In this article, we review the motivation for and the physics programme of CBM, including activities before the start of data taking in 2022, in the context of the worldwide efforts to explore high-density QCD matter.Comment: 15 pages, 11 figures. Published in European Physical Journal

Prediction of Stress Responses in Goats: Comparison of Artificial Neural Network and Multiple Regression Models

This study was conducted to determine if artificial neural networks (ANN) can be used to more accurately predict physiological stress responses in goats compared with statistical regression. Prediction models were developed for plasma cortisol and glucose concentrations, creatine kinase (CK) activity, neutrophil (N) and lymphocyte (L) counts, and N:L ratio as a function of time (0, 1, 2, 3, and 4 h; n = 16 goats/time) after a 2 h transportation (input 1) and stocking density (25 vs. 50 goats; input 2). However, input 2 was not included in the final models, since density did not have a significant effect. The NeuralWorks Predict Software and SAS were used to develop ANN and regression models, respectively. Backpropagation (BP) and Kalman filter (KF) learning rules were used to develop nonparametric models. Correlations between predicted and observed values were better with ANN-BP (R-values = 0.87, 0.67, 0.56, 0.27, 0.42, and 0.53) and ANN-KF (R-values = 0.84, 0.67, 0.58, 0.27, 0.42, and 0.50) models for cortisol, glucose, CK, N, L, and N:L ratio, respectively, than with regression models (R-values = 0.85, 0.52, 0.27, 0.13, 0.31, and 0.12). The results showed that the ANN models can predict responses more robustly compared with statistical regression.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Preharvest Management and Postharvest Intervention Strategies to Reduce Escherichia coli Contamination in Goat Meat: A Review

Goat meat is the main source of animal protein in developing countries, particularly in Asia and Africa. Goat meat consumption has also increased in the US in the recent years due to the growing ethnic population. The digestive tract of goat is a natural habitat for Escherichia coli organisms. While researchers have long focused on postharvest intervention strategies to control E. coli outbreaks, recent works have also included preharvest methodologies. In goats, these include minimizing animal stress, manipulating diet a few weeks prior to processing, feeding diets high in tannins, controlling feed deprivation times while preparing for processing, and spray washing goats prior to slaughter. Postharvest intervention methods studied in small ruminant meats have included spray washing using water, organic acids, ozonated water, and electrolyzed water, and the use of ultraviolet (UV) light, pulsed UV-light, sonication, low-voltage electricity, organic oils, and hurdle technologies. These intervention methods show a strong antimicrobial activity and are considered environmentally friendly. However, cost-effectiveness, ease of application, and possible negative effects on meat quality characteristics must be carefully considered before adopting any intervention strategy for a given meat processing operation. As discussed in this review paper, novel pre- and post-harvest intervention methods show significant potential for future applications in goat farms and processing plants