Short communication. Collection and characterisation of a population of Triticum boeoticum Boiss., a wild wheat species not previously found in the Mediterranean western region

En julio del 2010 se recolectó una población de trigo silvestre en una zona abandonada cerca de Madrid, España. Esta zona posee una biodiversidad botánica elevada y un tipo de suelo muy peculiar denominado “arcillas verdes”. Se recogió una muestra de trigo y se multiplicó y caracterizó para varios caracteres agro-morfológicos y subunidades de gluteninas. El número cromosómico 2n de las semillas demostró que es una especie diploide de trigo y los datos de caracterización indicaron que es Triticum boeoticum Boiss. Esta especie llegó probablemente como mala hierba del cultivo de escaña que se producía en la zona hasta al menos la primera mitad del s. xix. Las características edáficas y climáticas del lugar y el hecho de que no haya referencias hasta ahora de esta especie en la zona oeste de la región Mediterránea aumentan el valor de esta adquisición para la mejora del trigo. La nueva accesión se conserva en el Centro Nacional de Recursos Fitogenéticos y se ha depositado una hoja de herbario en el Real Jardín Botánico de Madrid

Dietary xylanase increases hepatic vitamin E concentration of chickens fed wheat based diet

The study examined the effect of xylanase supplementation on apparent metabolizable energy (AME) and hepatic vitamin E and carotenoids in broiler chickens fed wheat based diets. A total of one hundred forty four male Ross 308 chickens were used in this study. Birds were randomly assigned to 3 dietary treatments (8 cages per treatment of 6 male broilers each) for 14 days from 7 to 21 day old. The control treatment was based on wheat-soyabean meal and was either unsupplemented or supplemented with either 1000 or 2000 xylanase units per kg diet. Orthogonal polynomial contrasts were used to test linear response to dietary xylanase activity. There was a positive linear relationship (P < 0.05) between dietary AME and doses of supplementary xylanase. A linear relationship (P < 0.05) was also observed between dosage of xylanase supplementation and hepatic vitamin E concentration and retention. In conclusion, xylanase supplementation improved dietary AME and increased hepatic vitamin E concentration which may have positive effects on the antioxidative status of the birds.

Partioning of dietary energy of chickens fed maize or wheat-based diets with and without a commercial blend of phytogenic feed additives

The aim of the study was to investigate the effects of a standardized mixture of a commercial blend of phytogenic feed additives containing 5% carvacrol, 3% cinnamaldehyde, and 2% capsicum on utilization of dietary energy and performance in broiler chickens. Four experimental diets were offered to the birds from 7 to 21 d of age. These included 2 basal control diets based on either wheat or maize that contained 215 g CP/kg and 12.13 MJ/kg ME and another 2 diets using the basal control diets supplemented with the plant extracts combination at 100 mg/kg diet. Each diet was fed to 16 individually penned birds following randomization. Dietary plant extracts improved feed intake and weight gain (P < 0.05) and slightly (P < 0.1) improved feed efficiency of birds fed the maize-based diet. Supplementary plant extracts did not change dietary ME (P > 0.05) but improved (P < 0.05) dietary NE by reducing the heat increment (P < 0.05) per kilogram feed intake. Feeding phytogenics improved (P < 0.05) total carcass energy retention and the efficiency of dietary ME for carcass energy retention. The number of interactions between type of diet and supplementary phytogenic feed additive suggest that the chemical composition and the energy to protein ratio of the diet may influence the efficiency of phytogenics when fed to chickens. The experiment showed that although supplementary phytogenic additives did not affect dietary ME, they caused a significant improvement in the utilization of dietary energy for carcass energy retention but this did not always relate to growth performance.

Hyperspectral to multispectral imaging for detection of tree nuts and peanut traces in wheat flour

In current industrial environments there is an increasing need for practical and inexpensive quality control systems to detect the foreign food materials in powder food processing lines. This demand is especially important for the detection of product adulteration with traces of highly allergenic products, such as peanuts and tree nuts. Manufacturing industries dealing with the processing of multiple powder food products present a substantial risk for the contamination of powder foods with traces of tree nuts and other adulterants, which might result in unintentional ingestion of nuts by the sensitised population. Hence, the need for an in-line system to detect nut traces at the early stages of food manufacturing is of crucial importance. In this present work, a feasibility study of a spectral index for revealing adulteration of tree nut and peanut traces in wheat flour samples with hyperspectral images is reported. The main nuts responsible for allergenic reactions considered in this work were peanut, hazelnut and walnut. Enhanced contrast between nuts and wheat flour was obtained after the application of the index. Furthermore, the segmentation of these images by selecting different thresholds for different nut and flour mixtures allowed the identification of nut traces in the samples. Pixels identified as nuts were counted and compared with the actual percentage of peanut adulteration. As a result, the multispectral system was able to detect and provide good visualisation of tree nut and peanut trace levels down to 0.01% by weight. In this context, multispectral imaging could operate in conjuction with chemical procedures, such as Real Time Polymerase Chain Reaction and Enzyme-Linked Immunosorbent Assay to save time, money and skilled labour on product quality control. This approach could enable not only a few selected samples to be assessed but also to extensively incorporate quality control surveyance on product processing lines.

Detection and quantification of peanut traces in wheat flour by near infrared hyperspectral imaging spectroscopy using principal-component analysis

The use of a common environment for processing different powder foods in the industry has increased the risk of finding peanut traces in powder foods. The analytical methods commonly used for detection of peanut such as enzyme-linked immunosorbent assay (ELISA) and real-time polymerase chain reaction (RT-PCR) represent high specificity and sensitivity but are destructive and time-consuming, and require highly skilled experimenters. The feasibility of NIR hyperspectral imaging (HSI) is studied for the detection of peanut traces down to 0.01% by weight. A principal-component analysis (PCA) was carried out on a dataset of peanut and flour spectra. The obtained loadings were applied to the HSI images of adulterated wheat flour samples with peanut traces. As a result, HSI images were reduced to score images with enhanced contrast between peanut and flour particles. Finally, a threshold was fixed in score images to obtain a binary classification image, and the percentage of peanut adulteration was compared with the percentage of pixels identified as peanut particles. This study allowed the detection of traces of peanut down to 0.01% and quantification of peanut adulteration from 10% to 0.1% with a coefficient of determination (r2) of 0.946. These results show the feasibility of using HSI systems for the detection of peanut traces in conjunction with chemical procedures, such as RT-PCR and ELISA to facilitate enhanced quality-control surveillance on food-product processing lines.

Numerical Simulation of the Aerodynamic Behavior of High Velocity Trains under Synthetic Crosswinds of Different Shear and Turbulence Characteristics

A numerical simulation of the aerodynamic behavior of high-speed trains under synthetic crosswinds at a 90º yaw angle is presented. The train geometry is the aerodynamic train model (ATM). Flow description based on numerical simulations is obtained using large eddy simulation (LES) and the commercial code ANSYSFluent V14.5. A crosswind whose averaged velocity and turbulence characteristics change with distance to the ground is imposed. Turbulent fluctuations that vary temporally and spatially are simulated with TurbSim code. The crosswind boundary condition is calculated for the distance the train runs during a simulation period. The inlet streamwise velocity boundary condition is generated using Taylor?s frozen turbulence hypothesis. The model gives a time history of the force and moments acting on the train; this includes averaged values, standard deviations and extreme values. Of particular interest are the spectra of the forces and moments, and the admittance spectra. For comparison, results obtained with LES and a uniform wind velocity fluctuating in time, and results obtained with Reynolds averaged Navier Stokes equations (RANS), and the averaged wind conditions, are also presented.

Examining wheat yield sensitivity to temperature and precipitation changes for a large ensemble of crop models using impact response surfaces

Impact response surfaces (IRSs) depict the response of an impact variable to changes in two explanatory variables as a plotted surface. Here, IRSs of spring and winter wheat yields were constructed from a 25-member ensemble of process-based crop simulation models. Twenty-one models were calibrated by different groups using a common set of calibration data, with calibrations applied independently to the same models in three cases. The sensitivity of modelled yield to changes in temperature and precipitation was tested by systematically modifying values of 1981-2010 baseline weather data to span the range of 19 changes projected for the late 21st century at three locations in Europe.

Hyperspectral to multispectral imaging for detection of tree nuts and peanut traces in wheat flour.

In current industrial environments there is an increasing need for practical and inexpensive quality control systems to detect the foreign food materials in powder food processing lines. This demand is especially important for the detection of product adulteration with traces of highly allergenic products, such as peanuts and tree nuts. Manufacturing industries dealing with the processing of multiple powder food products present a substantial risk for the contamination of powder foods with traces of tree nuts and other adulterants, which might result in unintentional ingestion of nuts by the sensitised population. Hence, the need for an in-line system to detect nut traces at the early stages of food manufacturing is of crucial importance. In this present work, a feasibility study of a spectral index for revealing adulteration of tree nut and peanut traces in wheat flour samples with hyperspectral images is reported. The main nuts responsible for allergenic reactions considered in this work were peanut, hazelnut and walnut. Enhanced contrast between nuts and wheat flour was obtained after the application of the index. Furthermore, the segmentation of these images by selecting different thresholds for different nut and flour mixtures allowed the identification of nut traces in the samples. Pixels identified as nuts were counted and with the actual percentage of peanut adulteration. As a result, the multispectral system was able to detect and provide good visualisation of tree nut and peanut trace levels down to 0.01% by weight. In this context, multispectral imaging could operate in conjuction with chemical procedures, such as Real Time Polymerase Chain Reaction and Enzyme-Linked Immunosorbent Assay to save time, money and skilled labour on product quality control. This approach could enable not only a few selected samples to be assessed but also to extensively incorporate quality control surveyance on product processing lines.

Application of Independent Components Analysis with the JADE algorithm and NIR hyperspectral imaging for revealing food adulteration

In recent years, Independent Components Analysis (ICA) has proven itself to be a powerful signal-processing technique for solving the Blind-Source Separation (BSS) problems in different scientific domains. In the present work, an application of ICA for processing NIR hyperspectral images to detect traces of peanut in wheat flour is presented. Processing was performed without a priori knowledge of the chemical composition of the two food materials. The aim was to extract the source signals of the different chemical components from the initial data set and to use them in order to determine the distribution of peanut traces in the hyperspectral images. To determine the optimal number of independent component to be extracted, the Random ICA by blocks method was used. This method is based on the repeated calculation of several models using an increasing number of independent components after randomly segmenting the matrix data into two blocks and then calculating the correlations between the signals extracted from the two blocks. The extracted ICA signals were interpreted and their ability to classify peanut and wheat flour was studied. Finally, all the extracted ICs were used to construct a single synthetic signal that could be used directly with the hyperspectral images to enhance the contrast between the peanut and the wheat flours in a real multi-use industrial environment. Furthermore, feature extraction methods (connected components labelling algorithm followed by flood fill method to extract object contours) were applied in order to target the spatial location of the presence of peanut traces. A good visualization of the distributions of peanut traces was thus obtained

Numerical simulation of a synthetic jet with OpenFoam

Numerical simulations of flow surrounding a synthetic jet actuating device are presented. By modifying a dynamic mesh technique available in OpenFoam-a well-documented open-source solver for fluid dynamics, detailed computations of the sinusoidal motion of the synthetic jet diaphragm were possible. Numerical solutions were obtained by solving the two dimensional incompressible viscous N-S equations, with the use of a second order implicit time marching scheme and a central finite volume method for spatial discretization in both streamwise and crossflow directions. A systematic parametric study is reported here, in which the external Reynolds number, the diaphragm amplitude and frequency, and the slot dimensions are varied.

Selecting crop models for decision making in wheat insurance

In crop insurance, the accuracy with which the insurer quantifies the actual risk is highly dependent on the availability on actual yield data. Crop models might be valuable tools to generate data on expected yields for risk assessment when no historical records are available. However, selecting a crop model for a specific objective, location and implementation scale is a difficult task. A look inside the different crop and soil modules to understand how outputs are obtained might facilitate model choice. The objectives of this paper were (i) to assess the usefulness of crop models to be used within a crop insurance analysis and design and (ii) to select the most suitable crop model for drought risk assessment in semi-arid regions in Spain. For that purpose first, a pre-selection of crop models simulating wheat yield under rainfed growing conditions at the field scale was made, and second, four selected models (Aquacrop, CERES- Wheat, CropSyst and WOFOST) were compared in terms of modelling approaches, process descriptions and model outputs. Outputs of the four models for the simulation of winter wheat growth are comparable when water is not limiting, but differences are larger when simulating yields under rainfed conditions. These differences in rainfed yields are mainly related to the dissimilar simulated soil water availability and the assumed linkages with dry matter formation. We concluded that for the simulation of winter wheat growth at field scale in such semi-arid conditions, CERES-Wheat and CropSyst are preferred. WOFOST is a satisfactory compromise between data availability and complexity when detail data on soil is limited. Aquacrop integrates physiological processes in some representative parameters, thus diminishing the number of input parameters, what is seen as an advantage when observed data is scarce. However, the high sensitivity of this model to low water availability limits its use in the region considered. Contrary to the use of ensembles of crop models, we endorse that efforts be concentrated on selecting or rebuilding a model that includes approaches that better describe the agronomic conditions of the regions in which they will be applied. The use of such complex methodologies as crop models is associated with numerous sources of uncertainty, although these models are the best tools available to get insight in these complex agronomic systems.

Selection, training and validation process of a sensory panel for bread analysis: Influence of cultivar on the quality of breads made from common wheat and spelta wheat

A protocol of selection, training and validation of the members of the panel for bread sensory analysis is proposed to assess the influence of wheat cultivar on the sensory quality of bread. Three cultivars of bread wheat and two cultivars of spelt wheat organically-grown under the same edaphoclimatic conditions were milled and baked using the same milling and baking procedure. Through the use of triangle tests, differences were identified between the five breads. Significant differences were found between the spelt breads and those made with bread wheat for the attributes ?crumb cell homogeneity? and ?crumb elasticity?. Significant differences were also found for the odor and flavor attributes, with the bread made with ?Espelta Navarra? being the most complex, from a sensory point of view. Based on the results of this study, we propose that sensory properties should be considered as breeding criteria for future work on genetic improvement.

Pulmonary Artery-Vein Segmentation in Real and Synthetic CT Images = Segmentación Arteria-Vena Pulmonares en Imágenes de CT Reales y Sintéticas

La tomografía axial computerizada (TAC) es la modalidad de imagen médica preferente para el estudio de enfermedades pulmonares y el análisis de su vasculatura. La segmentación general de vasos en pulmón ha sido abordada en profundidad a lo largo de los últimos años por la comunidad científica que trabaja en el campo de procesamiento de imagen; sin embargo, la diferenciación entre irrigaciones arterial y venosa es aún un problema abierto. De hecho, la separación automática de arterias y venas está considerado como uno de los grandes retos futuros del procesamiento de imágenes biomédicas. La segmentación arteria-vena (AV) permitiría el estudio de ambas irrigaciones por separado, lo cual tendría importantes consecuencias en diferentes escenarios médicos y múltiples enfermedades pulmonares o estados patológicos. Características como la densidad, geometría, topología y tamaño de los vasos sanguíneos podrían ser analizados en enfermedades que conllevan remodelación de la vasculatura pulmonar, haciendo incluso posible el descubrimiento de nuevos biomarcadores específicos que aún hoy en dípermanecen ocultos. Esta diferenciación entre arterias y venas también podría ayudar a la mejora y el desarrollo de métodos de procesamiento de las distintas estructuras pulmonares. Sin embargo, el estudio del efecto de las enfermedades en los árboles arterial y venoso ha sido inviable hasta ahora a pesar de su indudable utilidad. La extrema complejidad de los árboles vasculares del pulmón hace inabordable una separación manual de ambas estructuras en un tiempo realista, fomentando aún más la necesidad de diseñar herramientas automáticas o semiautomáticas para tal objetivo. Pero la ausencia de casos correctamente segmentados y etiquetados conlleva múltiples limitaciones en el desarrollo de sistemas de separación AV, en los cuales son necesarias imágenes de referencia tanto para entrenar como para validar los algoritmos. Por ello, el diseño de imágenes sintéticas de TAC pulmonar podría superar estas dificultades ofreciendo la posibilidad de acceso a una base de datos de casos pseudoreales bajo un entorno restringido y controlado donde cada parte de la imagen (incluyendo arterias y venas) está unívocamente diferenciada. En esta Tesis Doctoral abordamos ambos problemas, los cuales están fuertemente interrelacionados. Primero se describe el diseño de una estrategia para generar, automáticamente, fantomas computacionales de TAC de pulmón en humanos. Partiendo de conocimientos a priori, tanto biológicos como de características de imagen de CT, acerca de la topología y relación entre las distintas estructuras pulmonares, el sistema desarrollado es capaz de generar vías aéreas, arterias y venas pulmonares sintéticas usando métodos de crecimiento iterativo, que posteriormente se unen para formar un pulmón simulado con características realistas. Estos casos sintéticos, junto a imágenes reales de TAC sin contraste, han sido usados en el desarrollo de un método completamente automático de segmentación/separación AV. La estrategia comprende una primera extracción genérica de vasos pulmonares usando partículas espacio-escala, y una posterior clasificación AV de tales partículas mediante el uso de Graph-Cuts (GC) basados en la similitud con arteria o vena (obtenida con algoritmos de aprendizaje automático) y la inclusión de información de conectividad entre partículas. La validación de los fantomas pulmonares se ha llevado a cabo mediante inspección visual y medidas cuantitativas relacionadas con las distribuciones de intensidad, dispersión de estructuras y relación entre arterias y vías aéreas, los cuales muestran una buena correspondencia entre los pulmones reales y los generados sintéticamente. La evaluación del algoritmo de segmentación AV está basada en distintas estrategias de comprobación de la exactitud en la clasificación de vasos, las cuales revelan una adecuada diferenciación entre arterias y venas tanto en los casos reales como en los sintéticos, abriendo así un amplio abanico de posibilidades en el estudio clínico de enfermedades cardiopulmonares y en el desarrollo de metodologías y nuevos algoritmos para el análisis de imágenes pulmonares. ABSTRACT Computed tomography (CT) is the reference image modality for the study of lung diseases and pulmonary vasculature. Lung vessel segmentation has been widely explored by the biomedical image processing community, however, differentiation of arterial from venous irrigations is still an open problem. Indeed, automatic separation of arterial and venous trees has been considered during last years as one of the main future challenges in the field. Artery-Vein (AV) segmentation would be useful in different medical scenarios and multiple pulmonary diseases or pathological states, allowing the study of arterial and venous irrigations separately. Features such as density, geometry, topology and size of vessels could be analyzed in diseases that imply vasculature remodeling, making even possible the discovery of new specific biomarkers that remain hidden nowadays. Differentiation between arteries and veins could also enhance or improve methods processing pulmonary structures. Nevertheless, AV segmentation has been unfeasible until now in clinical routine despite its objective usefulness. The huge complexity of pulmonary vascular trees makes a manual segmentation of both structures unfeasible in realistic time, encouraging the design of automatic or semiautomatic tools to perform the task. However, this lack of proper labeled cases seriously limits in the development of AV segmentation systems, where reference standards are necessary in both algorithm training and validation stages. For that reason, the design of synthetic CT images of the lung could overcome these difficulties by providing a database of pseudorealistic cases in a constrained and controlled scenario where each part of the image (including arteries and veins) is differentiated unequivocally. In this Ph.D. Thesis we address both interrelated problems. First, the design of a complete framework to automatically generate computational CT phantoms of the human lung is described. Starting from biological and imagebased knowledge about the topology and relationships between structures, the system is able to generate synthetic pulmonary arteries, veins, and airways using iterative growth methods that can be merged into a final simulated lung with realistic features. These synthetic cases, together with labeled real CT datasets, have been used as reference for the development of a fully automatic pulmonary AV segmentation/separation method. The approach comprises a vessel extraction stage using scale-space particles and their posterior artery-vein classification using Graph-Cuts (GC) based on arterial/venous similarity scores obtained with a Machine Learning (ML) pre-classification step and particle connectivity information. Validation of pulmonary phantoms from visual examination and quantitative measurements of intensity distributions, dispersion of structures and relationships between pulmonary air and blood flow systems, show good correspondence between real and synthetic lungs. The evaluation of the Artery-Vein (AV) segmentation algorithm, based on different strategies to assess the accuracy of vessel particles classification, reveal accurate differentiation between arteries and vein in both real and synthetic cases that open a huge range of possibilities in the clinical study of cardiopulmonary diseases and the development of methodological approaches for the analysis of pulmonary images.

Economics of Wheat in Egypt

Este estudio pretende estimar la eficiencia y la productividad de las principales provincias de la producción de trigo en Egipto. Los datos utilizados en este estudio son datos de panel a nivel de provincias del período 1990-2012, obtenidos del Ministerio de Agricultura y Recuperación Tierras, y de la Agencia Central de Movilización Pública y Estadística, Egipto. Se aplica el enfoque de fronteras estocásticas para medir la eficiencia (función de producción de Cobb-Douglas) y se emplean las especificaciones de Battese y Coelli (1992) y (1995). También se utiliza el índice de Malmquist como una aproximación no paramétrica (Análisis de Envolvente de Datos) para descomponer la productividad total de los factores de las principales provincias productoras de trigo en Egipto en cambio técnico y cambio de eficiencia. El coeficiente de tierra es positivo y significativo en los dos especificaciones Battese y Coelli (1992) y (1995), lo que implica que aumentar la tierra para este cultivo aumentaría significativamente la producción de trigo. El coeficiente de trabajo es positivo y significativo en la especificación de Battese y Coelli (1992), mientras que es positivo y no significativo en la especificación de Battese y Coelli (1995). El coeficiente de la maquinaria es negativo y no significativo en las dos especificaciones de Battese y Coelli (1992) y (1995). El coeficiente de cambio técnico es positivo y no significativo en la especificación de Battese y Coelli (1992), mientras que es positiva y significativo en la especificación de Battese y Coelli (1995). Las variables de efectos del modelo de ineficiencia Battese y Coelli (1995) indican que no existe impacto de las diferentes provincias en la producción de trigo en Egipto; la ineficiencia técnica de la producción de trigo tendió a disminuir durante el período de estudio; y no hay ningún impacto de género en la producción de trigo en Egipto. Los niveles de eficiencia técnica varían entre las diferentes provincias para las especificaciones de Battese y Coelli (1992) y (1995); el nivel mínimo medio de eficiencia técnica es 91.61% en la provincia de Fayoum, mientras que el nivel máximo medio de la eficiencia técnica es 98.69% en la provincia de Dakahlia. La eficiencia técnica toma un valor medio de 95.37%, lo que implica poco potencial para mejorar la eficiencia de uso de recursos en la producción de trigo. La TFPCH de la producción de trigo en Egipto durante el período 1990-2012 tiene un valor menor que uno y muestra un declive. Esta disminución es debida más al componente de cambio técnico que al componente de cambio de eficiencia. La disminución de TFPCH mejora con el tiempo. La provincia de Menoufia tiene la menor disminución en TFPCH, 6.5%, mientras que dos provincias, Sharkia y Dakahlia, son las que más disminuyen en TFPCH, 13.1%, en cada uno de ellas. Menos disminución en TFPCH ocurre en el período 2009-2010, 0.3%, mientras que más disminución se produce en TFPCH en el período 1990-1991, 38.9%. La disminución de la PTF de la producción de trigo en Egipto se atribuye principalmente a la mala aplicación de la tecnología. ABSTRACT The objectives of this study are to estimate the efficiency and productivity of the main governorates of wheat production in Egypt. The data used in this study is a panel data at the governorates level, it represents the time period 1990-2012 and taken from the Ministry of Agriculture and Land Reclamation, and the Central Agency for Public Mobilization and Statistics, Egypt. We apply the stochastic frontier approach for efficiency measurement (Cobb-Douglas production function) and the specifications of Battese and Coelli (1992) and (1995) are employed. Also we use Malmquist TFP index as a non-parametric approach (DEA) to decompose total factor productivity of the main governorates of wheat production in Egypt into technical change and efficiency change. The coefficient of land is positive and significant at Battese and Coelli (1992) and (1995) specifications, implying that increasing the wheat area could significantly enhance the production of wheat. The coefficient of labor is positive and significant at Battese and Coelli (1992) specification, while it is positive and insignificant at Battese and Coelli (1995) specification. The coefficient of machinery is negative and insignificant at the specifications of Battese and Coelli (1992) and (1995). The technical change coefficient is positive and insignificant at Battese and Coelli (1992) specification, while it is positive and significant at Battese and Coelli (1995) specification. The variables of the inefficiency effect model indicate that there is no impact from the location of the different governorates on wheat production in Egypt, the technical inefficiency of wheat production tended to decrease through the period of study, and there is no impact from the gender on wheat production in Egypt. The levels of technical efficiency vary among the different governorates for the specifications of Battese and Coelli (1992) and (1995); the minimum mean level of technical efficiency is 91.61% at Fayoum governorate, while the maximum mean level of technical efficiency is 98.69% at Dakahlia governorate. The technical efficiency takes an average value of 95.37%, this implying that little potential exists to improve resource use efficiency in wheat production. The TFPCH of wheat production in Egypt during the time period 1990-2012 has a value less than one and shows a decline; this decline is due mainly to the technical change component than the efficiency change component. The decline in TFPCH is generally improves over time. Menoufia governorate has the least declining in TFPCH by 6.5%, while two governorates, Sharkia and Dakahlia have the most declining in TFPCH by 13.1% for each of them. The least declining in TFPCH occurred at the period 2009- 2010 by 0.3%, while the most declining in TFPCH occurred at the period 1990-1991 by 38.9%. The declining in TFP of wheat production in Egypt is attributed mainly to poor application of technology.

Wheat allergy in celiac children

Gluten is the main structural protein complex of wheat with equivalent toxic proteins found in other cereals (rye, barley, and oats) which are responsible for different immunologic responses with different clinical expressions of disease. The spectrum of gluten-related disorders has been classified according to pathogenic, clinical, and epidemiological differences in three main forms: (i) wheat allergy (WA), an IgE-mediated disease; (ii) autoimmune disease, including celiac disease (CD), dermatitis herpetiformis, and gluten ataxia; and (iii) possibly immune-mediated, gluten sensitivity [1]. WA is an immunologic Th2 response with typical manifestations which can vary from dermatological, respiratory, and/or intestinal to anaphylactic reactions. In contrast, CD is an autoimmune disorder, a gliadin-specific T-cell response which is enhanced by the action of intestinal tissue transglutaminase (tTG), with a wide clinical spectrum including symptomatic cases with either intestinal (e.g., chronic diarrhea, weight loss) or extraintestinal features (e.g., anemia, osteoporosis, neurologic disturbances) and silent forms that are occasionally discovered as a result of serological screening [1]. We studied wheat allergy in two children with early diagnosis of CD, who developed immediate allergic symptoms after eating small amounts of wheat flour.