Kernel Processing Research Articles

Maize: A Paramount Staple Crop in the Context of Global Nutrition.

The maize plant (Zea mays), characterized by an erect green stalk, is one of the 3 great grain crops of the world. Its kernels, like other seeds, are storage organs that contain essential components for plant growth and reproduction. Many of these kernel constituents, including starch, protein, and some micronutrients, are also required for human health. For this reason, and others, maize has become highly integrated into global agriculture, human diet, and cultural traditions. The nutritional quality and integrity of maize kernels are influenced by many factors including genetic background, environment, and kernel processing. Cooking procedures, including nixtamalization and fermentation, can increase accessibility of micronutrients such as niacin. However, man cannot live on maize alone. For one-third of the world's population, namely in sub-Saharan Africa, Southeast Asia, and Latin America, humans subsist on maize as a staple food but malnutrition pervades. Strategies to further improve kernel macronutrient and micronutrient quality and quantities are under intense investigation. The 2 most common routes to enhance grain nutritional value are exogenous and endogenous fortification. Although exogenous fortification, such as addition of multivitamin premixes to maize flour, has been successful, endogenous fortification, also known as "biofortification," may provide a more sustainable and practical solution for chronically undernourished communities. Recent accomplishments, such as low-phytate, high-lysine, and multivitamin maize varieties, have been created using novel genetic and agronomic approaches. Investigational studies related to biofortified maize are currently underway to determine nutrient absorption and efficacy related to human health improvement.

Highly effective technology and technique for extraction of oils from fruit-and-vegetable stones with use of renewable energy sources

The oil extraction processes from oil-bearing cultures’ seeds and stones is time and energy-intensive. The study shows that during processing kernels of oil-bearing cultures under influence of electromagnetic field the destruction process of cellar structure is intensified in 7-9 times than in existing moist-heat processing. Moreover, the process runs shorter and under comparatively low temperature regime that reduces the electric power expenses. Using electromagnetic processing of oil-bearing kernels provides increase of oil output up to 20-25% as well.

Highly effective technology and technique for extraction of oils from fruit-and-vegetable stones with use of renewable energy sources

The oil extraction processes from oil-bearing cultures’ seeds and stones is time and energy-intensive. The study shows that during processing kernels of oil-bearing cultures under influence of electromagnetic field the destruction process of cellar structure is intensified in 7-9 times than in existing moist-heat processing. Moreover, the process runs shorter and under comparatively low temperature regime that reduces the electric power expenses. Using electromagnetic processing of oil-bearing kernels provides increase of oil output up to 20-25% as well.

The Equity Capital Puzzle: A Consumption-Based Model

This paper examines Bansal, Fang, and Yaron's (2007) equity capital puzzle, which shows that expanding sectors in the economy do not provide increasing risk-reward compensation to investors who tie up larger fractions of their wealth in those sectors. I show the puzzle for broad definitions of net corporate payout (including all cashflows from the corporate sector) and aggregate wealth (including human capital). I then propose a continuous-time representative agent model with habit formation pricing kernel and heteroskedastic output processes for which sectoral share dynamics is linked to the state of the economy, solve it in semi-closed form, and calibrate it to the data. The model, which has simple ingredients, can quantitatively account for the basic properties of the asset markets and the equity capital puzzle.

Magnetic resonance imaging and analyses of tempering processes in rice kernels

This research involved a magnetic resonance imaging (MRI) technique that was applied to examine water distribution and migration in single rice kernels during the tempering process. The imaging experiments were performed in a Bruker 9.4T MRI system. Three-dimensional spin-echo (SE) imaging sequences were optimized by adjusting the scanning parameters of echo time (TE) and repetition time (TR) to obtain images with maximum contrast. The MR images showed that the moisture distribution in the rice kernel is non-uniform and compartmental. The embryo region exhibited much higher MR signal intensity than the starchy endosperm portion. The tempering process was analyzed with spatial-temporal signal intensities of the endosperm following the drying process of the rice kernel. The transient change of the signal intensities in the endosperm was well fitted with a double exponential function suggesting that both convection and diffusion contributed to the reduction of the moisture gradient within the rice kernel during tempering. This hypothesis was further supported by the experimental data of the insulated rice kernel whose convective mass transfer was excluded. The experimental results revealed that MR imaging of rice kernels could be used as an efficient tool to examine the mechanisms of moisture migration within cereal grains.

A Computational Digital Pixel Sensor Featuring Block-Readout Architecture for On-Chip Image Processing

In this paper, a computational digital pixel sensor (DPS) equipped with an on-chip image-processing capability has been developed. In order to resolve the interconnection bottleneck between the sensor array and on-chip processing units, a new block-readout architecture has been proposed and implemented on the chip. The data from the sensor array are read out in a form of a pixel block compatible to kernel image processing, and they are processed in parallel by on-chip processing units. Such an architecture has enabled us to carry out an efficient kernel processing using a linear array of single-instruction-multiple-data processing units. In order to demonstrate the advantage of such an architecture, a rank-order filtering circuit has been implemented on the chip as a case study of the on-chip image processing. In this paper, a binary-search rank-order filtering algorithm has been implemented in a simple circuitry. A proof-of-concept chip having an array of 64 times 48 pixels was designed and fabricated using a 0.35-mum CMOS technology, and the concept has been verified by the measuremet of fabricated chips.

Individual movement behavior, matrix heterogeneity, and the dynamics of spatially structured populations

The dynamics of spatially structured populations is characterized by within- and between-patch processes. The available theory describes the latter with simple distance-dependent functions that depend on landscape properties such as interpatch distance or patch size. Despite its potential role, we lack a good mechanistic understanding of how the movement of individuals between patches affects the dynamics of these populations. We used the theoretical framework provided by movement ecology to make a direct representation of the processes determining how individuals connect local populations in a spatially structured population of Iberian lynx. Interpatch processes depended on the heterogeneity of the matrix where patches are embedded and the parameters defining individual movement behavior. They were also very sensitive to the dynamic demographic variables limiting the time moving, the within-patch dynamics of available settlement sites (both spatiotemporally heterogeneous) and the response of individuals to the perceived risk while moving. These context-dependent dynamic factors are an inherent part of the movement process, producing connectivities and dispersal kernels whose variability is affected by other demographic processes. Mechanistic representations of interpatch movements, such as the one provided by the movement-ecology framework, permit the dynamic interaction of birth-death processes and individual movement behavior, thus improving our understanding of stochastic spatially structured populations.

Experimental validation studies on a multi-dimensional and multi-scale population balance model of batch granulation

In this study, a dynamic model is presented for the granulation process, employing a three-dimensional population balance framework. As a first attempt to account for the multi-scale character of the process, the nucleation and aggregation kernels used in the population balance model are derived using mechanistic representations of the underlying particle physics such as wetting kinetics and energy dissipation effects. Thus, the fundamental properties of the powder and the liquid were used as parameters in the model to predict the granulator dynamics and granule properties. The population balance model is validated against experimental data from a calcite / PVOH – H 2 O recipe obtained using a lab-scale drum granulator for granule size, fractional binder content and porosity. A reasonably good agreement between experimental and simulation results were obtained for the granule size distribution under different experimental conditions. In addition, accurate model predictions were made for the evolution of the average properties (i.e., size, fractional binder content and porosity) for various operating conditions.

WATER ABSORPTION CHARACTERISTICS OF APRICOT KERNELS DURING SOAKING

ABSTRACT The aim of this research was to investigate water absorption characteristics of apricot kernels using Peleg's model between temperatures of 20 and 50C. The Peleg constant K1 decreased from 5.52 × 10−2 to 1.63 × 10−2/h% for apricot kernels with increasing temperature from 20 to 50C. An inverse linear relationship was found for the soaking temperature and Peleg constant K1, while Peleg constant K2 was unaffected by the soaking temperature. The predictive capability of Peleg's equation for apricot kernels was tested, and differences between experimental and predicted moisture content values were not significant at 5% level (P < 0.05). The average activation energy (Ea) for K1 was 29.4 kJ/mol.PRACTICAL APPLICATIONSTechnological processing of shells and kernels includes a washing, sorting, cracking and separation process. Apricot kernels are subject to major quality loss during processing. Especially the relationship between kernels and water is important during the washing process. The diffusion of moisture into the kernel during moisture addition is influenced by the water temperature. In such operations, it is desirable to predict the diffusion of moisture as a function of time and temperature.

Probabilistic Methodology for Long-Term Assessment of Volcanic Hazards

Because of the difficulty of describing the complex spatial and temporal patterns inherent to volcanism, the use of solely deterministic models is not sufficient for long-term estimation of volcanic hazards. In order to account for the intrinsic uncertainty of volcanism that occurs in space and time and with respect to event types and their intensity, the use of probabilistic models becomes quite natural for long-term hazard assessment. Here, we discuss a range of probabilistic approaches to forecast the future spatial distribution of volcanism, including kernel, adaptive kernel, and Cox process methods. An application to the volcanic arc of Tohoku illustrates the proposed methodology.

Influence of atmospheric and sea-surface corrections on retrieval of bottom depth and reflectance using a semi-analytical model: a case study in Kaneohe Bay, Hawaii

Hyperspectral instruments provide the spectral detail necessary for extracting multiple layers of information from inherently complex coastal environments. We evaluate the performance of a semi-analytical optimization model for deriving bathymetry, benthic reflectance, and water optical properties using hyperspectral AVIRIS imagery of Kaneohe Bay, Hawaii. We examine the relative impacts on model performance using two different atmospheric correction algorithms and two different methods for reducing the effects of sunglint. We also examine the impact of varying view and illumination geometry, changing the default bottom reflectance, and using a kernel processing scheme to normalize water properties over small areas. Results indicate robust model performance for most model formulations, with the most significant impact on model output being generated by differences in the atmospheric and deglint algorithms used for preprocessing.

Fate of fumonisin B 1 in the processing of whole maize kernels during dry-milling

The aim of this research was to evaluate how the amount of fumonisins in a kernel is re-distributed over the different processing products. The study focused on the description of the dry-milling process, with details on the products and by-products, milling yield, and the granulometric and chemical composition. Maize kernels and four derived milling fractions from twenty-four lots were sampled from 2002 and 2006. The main results were: (a) the animal meal and germ had a higher fumonisin content than the unprocessed grain, while human meals were less contaminated; (b) there is an inverse relationship between the particle size and fumonisin contents in meals; (c) toxin tends to concentrate in the bran and germ, while the endosperm is only partially contaminated.

Technical Note: A Near-Infrared Reflectance Spectroscopy Technique to Predict Particle Size of Starch Within Corn Silage

Starch particle size characteristics of 81 diverse corn silage samples, which included 27 combinations of hybrid, planting dates, and harvest dates subjected to 3 different degrees of kernel processing, were determined via vertical shaking through 9 screens with nominal square apertures of 19.0, 13.2, 9.5, 6.7, 4.75, 3.35, 2.36, 1.18, and 0.6mm and a pan. Starch content of dry matter remaining on each screen and on the pan for each corn silage was determined, and geometric mean particle size (GMPS, μm), starch particles(SP)/g, starch surface area (SSA, cm2/g), kernel processing score (KPS), % starch<4.75mm, and the percentage of total starch remaining on each screen of the vertical shakers were calculated. Near-infrared reflectance spectra were obtained by scanning 3 types of samples: 1mm of dried ground corn silage; whole undried, unground corn silage; and undried, unground corn silage that passed through a 19-mm screen. Calibrations to predict GMPS, SP, SSA, and KPS characteristics of corn silage starch were attempted from each spectral origin. Calibrations to predict GMPS, SP, SSA, KPS, and the percentage of total starch retained on screens of the vertical shaker was unattainable (R2<0.45) using spectra obtained from 1mm of dried ground corn silage or whole undried, unground corn silage. However, reasonable near-infrared reflectance spectra equations (R2>0.81) for GMPS, SSA, and KPS were attained using spectra from undried, unground corn silage that passed through a 19-mm screen. This technique holds promise as a rapid and efficient method to determine particle size characteristics of starch within corn silage.

Effects of Nitrogen and Potassium Fertilizers on Rice (Oryza sativa L.) Genotypes Processing Characteristics

In order to consider effects of various levels of nitrogen and potassium application on kernel processing characteristics of rice cultivars, an experiment was developed in 2004 and 2005 using Tarrom (a local Iranian landrace) and Neda (an Iranian improved cultivar). In this experiment four levels of nitrogen fertilizer (0, 50, 100 and 150 kg N ha(-1) from urea source) and four levels of potassium fertilizer (0, 75, 150 and 225 kg K2O ha(-1) from potassium sulfate source) have been applied using a split factorial design with 3 replications. Nitrogen fertilizer have been applied in three stages (1/3 in transplanting stage, 1/3 in tillering stage and finally 1/3 in flowering initiation stage) and potassium fertilizer have been applied in two stages (1/2 in transplanting stage and 1/2 in shooting stage). Results showed that application of nitrogen cause an increase in amount of bran production and have shown significant effects on percentages of bran, head and brewers rice, husking efficiency and transformation degree. However, potassium application has increased percent of bran and husking efficiency and has decrease percentages of brewers rice and has not demonstrated significant effects on percentages of husk, head rice and transformation degree. Furthermore, simultaneous application of nitrogen and potassium in Tarrom genotype has not shown significantly effects on percentages of husk, head and brewers rice and transformation degree. In Neda, cultivar has not also shown significant effects on percentages of bran production, head and brewers rice and husking efficiency, respectively. In Tarrom genotype amount of husk, bran, brewers rice and transformation degree were higher than in Neda cultivar, however, amount of head rice and husking efficiency in Neda cultivar were higher than in Tarrom genotype.

Modeling of n-butane ignition, combustion, and preflame oxidation in the 20-l vessel

The objective of the study reported herein is to simulate various physical and chemical phenomena accompanying fuel-rich n-butane–oxygen mixture preparation, ignition, preflame oxidation, and combustion in the standard 20-l explosion vessel, by applying mathematical models. Based on the computational fluid dynamics (CFD) simulations of the mixing process and natural convection of the ignition kernel, as well as on the analysis of the detailed reaction mechanism of n-butane oxidation, laminar flame propagation, and self-ignition, possible explanations for the phenomena observed experimentally have been suggested. The results of the study indicate that seemingly inflammable mixtures can become hazardous depending on the mixture preparation procedure and forced ignition timing.

Simulation of drying process of corn kernels during microwave and convective treatment

AbstractDrying is a necessary technology and a very energy‐demanding process in the area of meat and vegetable processing; it is a tool for finishing semiprocessed or processed goods. Taking the given conditions into consideration, development of technology is necessary, which serves several aims that are often in disagreement with each other (in terms of improvement of availability value, avoidance of artificial additives, energy optimization, reduction of other cost factors, etc.). Until now, several scientific works have been published serving solutions for one specific problem of practice. The main idiosyncrasy of these works is the difference between their methods and availability; hence these are unsuitable to give a uniform model for products with different physical‐biological properties: because, it goes without saying, circumstances of their birth as well as their aims differ so much. Computer support nowadays allows us to build a uniform model based on previous research and auxiliary measurement results, which can simulate the drying process of some of the most important agricultural products. Copyright © 2007 Curtin University of Technology and John Wiley &amp; Sons, Ltd.

Alternative posterior consistency results in nonparametric binary regression using Gaussian process priors

We establish consistency of posterior distribution when a Gaussian process prior is used as a prior distribution for the unknown binary regression function. Specifically, we take the work of Ghosal and Roy [2006. Posterior consistency of Gaussian process prior for nonparametric binary regression. Ann. Statist. 34, 2413–2429] as our starting point, and then weaken their assumptions on the smoothness of the Gaussian process kernel while retaining a stronger yet applicable condition about design points. Furthermore, we extend their results to multi-dimensional covariates under a weaker smoothness condition on the Gaussian process. Finally, we study the extent to which posterior consistency can be achieved under a general model where, when additional hyperparameters in the covariance function of a Gaussian process are involved.

Development of combined biological technology for treatment of high-strength organic wastewater and results of case studies

Our study group has developed a unique combined biological technology to treat high-strength organic wastewaters from the industries of dyestuff, pharmaceutical, chemical engineering and zymolysis by using the principles of anaerobic ecological niche and bio-phase separation. The study obtained five national invention patents and eight patent equipments. This technology contains four kernel processes - two-phase anaerobic-aerobic process, hydrolysis-acidification-oxidation process, UASBAF-oxidation process, and internal cycling-hydrolysis-oxidation process. Fifteen pilot projects were accomplished in the basins of Tai Lake, Huai River, Liao River and Songhua River, and their total capital investment reached 185.214 million Yuan (RMB). Compared to conventional wastewater treatment technology, the innovative technology is more cost-effective for high-strength organic wastewater treatment, can save capital investment by 15% – 30%, lessen land usage by 20% to 40% and decrease the operating cost by 10% to 25%. The operating cost of treatment per cubic meter industrial wastewater could be below 0.6 to 1.4 Yuan (RMB).

A Theory of Volatility Spreads

This study formalizes the departure between risk-neutral and physical index return volatilities, termed volatility spreads. Theoretically, the departure between risk-neutral and physical index volatility is connected to the higher-order physical return moments and the parameters of the pricing kernel process. This theory predicts positive volatility spreads when investors are risk averse, and when the physical index distribution is negatively skewed and leptokurtic. Our empirical evidence is supportive of the theoretical implications of risk aversion, exposure to tail events, and fatter left-tails of the physical index distribution in markets where volatility is traded.

A Theory of Volatility Spreads

This study formalizes the departure between risk-neutral and physical index return volatilities, termed volatility spreads. Theoretically, the departure between risk neutral and physical index volatility is connected to the higher-order physical return moments and the parameters of the pricing kernel process. This theory predicts positive volatility spreads when investors are risk averse, and when the physical index distribution is negatively skewed and leptokurtic. Our empirical evidence is supportive of the theoretical implications of risk aversion, exposure to tail events, and fatter left-tails of the physical index distribution in markets where volatility is traded.