Avaliação da atividade anti-inflamatória intestinal do extrato das folhas jovens de Triticum aestivum L. obtido por cultivo em Casa de Vegetação: subtitulo

O uso disseminado do suco de folhas jovens de trigo (Triticum aestivum L.) para diversos fins terapêuticos foi proposto por Dra. Ann Wigmore há mais de 40 anos nos Estados Unidos e popularizado de tal forma que é utilizado para o tratamento alternativo de doenças autoimunes e gastrointestinais, dentre outras. Baseado nessas informações populares, o presente estudo teve como objetivo avaliar a composição química e a atividade anti-inflamatória intestinal do extrato aquoso de folhas jovens de trigo na fase aguda do modelo experimental de doença inflamatória intestinal induzida por TNBS (ácido trinitrobenzenosulfônico) em ratos. Os animais foram tratados durante cinco dias antes da indução do processo inflamatório, sendo testadas as doses de 100, 50, 25 e 5 mg/Kg e azatioprina como droga de referência. Após 48 horas da indução do processo inflamatório, os animais foram mortos e seus cólons extraídos para a realização dos estudos macroscópicos e bioquímicos. Paralelamente foi realizado um estudo para a caracterização da composição química do extrato, através de testes para a determinação das principais classes de substâncias presentes, bem como o doseamento de compostos fenólicos e atividade sequestradora de radicais livres. O estudo demonstrou que o extrato aquoso de folhas jovens de trigo a 5 mg/Kg apresentou uma tendência em melhorar os parâmetros macroscópicos e bioquímicos avaliados, porém sem diferenças estatísticas. A caracterização fitoquímica do extrato mostrou que o suco de trigo é uma fonte importante de compostos antioxidantes, os quais podem estar relacionados com a melhora no processo inflamatório colônico

Preliminary report of epiphytic and endophytic colonization of black oat (Avena strigosa) and wheat (Triticum aestivum) by Curtobacterium flaccumfaciens pv. flaccumfaciens in Brazil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Caracterización del patrón de gluteninas de bajo peso molecular de trigo pan (Triticum aestivum L.) y su efecto sobre el potencial uso final de la harina

El trigo pan [Tritivum aestivum L.]tiene diversos usos en la industria alimenticia debido a las características particulares de la harina y es el ingrediente principal en la elaboración de pan, galletitas, productos de repostería, pastas frescas, etc. La calidad intrínseca de las harinas está influenciada por la cantidad y calidad de proteínas del gluten: Gluteninas de alto [HMW-Gs]y bajo peso molecular [LMW-Gs]y Gliadinas [Gli]. A su vez, la calidad reológica está afectada por factores ambientales y la relación Genotipo x Ambiente. Por lo mencionado, resulta importante conocer los efectos de los patrones proteicos sobre la calidad industrial de trigo pan y comprender la incidencia de la disponibilidad de Nitrógeno y temperaturas elevadas durante el llenado de los granos sobre las fracciones proteicas que componen el gluten y la reolgía de las masas. Se utilizaron proteinogramas [SDS-PAGE, unidimensionales]para la identificación proteica de 74 cultivares argentinos de trigo pan y el test de sedimentación [SDSS]para estimar la fuerza de gluten, como indicador de calidad intrínseca y para ver el efecto del ambiente se utilizaron 26 cultivares de trigo pan sembrados en el mismo sitio y con las mismas condiciones de manejo, en dos años [2008 y 2009]con temperaturas contrastantes durante el llenado de los granos y dos niveles de fertilización nitrogenada. La combinación total de las proteínas del gluten [HMW-Gs+LMWGs+Gli]tuvo más influencia sobre la calidad del gluten que cada fracción proteica en particular. En general, las altas temperaturas aumentaron la cantidad del Gli y la extensibilidad de las masas [L], en tanto que la disponibilidad de N incrementó todos los grupos proteicos, la fuerza [W]y la extensibilidad de la masa. Igualmente, se observó un efecto diferencial de dichos factores sobre los patrones proteicos y la calidad final, según la composición del gluten.

Combined use of gliadins and SSRs to analyse the genetic variability of the Spanish collection of cultivated diploid wheat (Triticum monococcum L. ssp. monococcum)

This work studied the combined use of gliadins and SSRs to analyse inter- and intra-accession variability of the Spanish collection of cultivated einkorn (Triticum monococcum L. ssp. monococcum) maintained at the CRF-INIA. In general, gliadin loci presented higher discrimination power than SSRs, reflecting the high variability of the gliadins. The loci on chromosome 6A were the most polymorphic with similar PIC values for both marker systems, showing that these markers are very useful for genetic variability studies in wheat. The gliadin results indicated that the Spanish einkorn collection possessed high genetic diversity, being the differentiation large between varieties and small within them. Some associations between gliadin alleles and geographical and agro-morphological data were found. Agro-morphological relations were also observed in the clusters of the SSRs dendrogram. A high concordance was found between gliadins and SSRs for genotype identification. In addition, both systems provide complementary information to resolve the different cases of intra-accession variability not detected at the agro-morphological level, and to identify separately all the genotypes analysed. The combined use of both genetic markers is an excellent tool for genetic resource evaluation in addition to agro-morphological evaluation.

Effects of N fertilisation, year and prolamin alleles on guten quality in durum wheat (Triticum turgidum L. ssp. turgidum) landraces from Spain

A subset of durum wheat Spanish landraces, previously evaluated for yield at low and high nitrogen (N) levels, was analysed for quality, protein content (P) and sodium dodecyl sulphate sedimentation (SDSS) test. The evaluation was carried out at the two N rates and in two years. The influence of prolamin alleles at the Glu-1, Glu-3, Glu-B2 and Gli-1 loci on quality parameters was also studied. The non significant Variety-by-Year or Variety-by-N interactions suggested that year and N affected all the varieties in a similar manner. Year and N effects were larger than variety effect for P, which increased with N. In contrast, variety genotype exhibited a stronger influence on SDSS test, which was not affected by year and fertilizer. Variety effects on P did not reflect the variety differences for SDSS test. A high positive influence of some prolamin alleles on quality parameters was detected, mainly for SDSS values. No correlation between yield and P was detected in the landraces adapted to low N. Based on the results of yield and quality evaluations, four landraces with high yield and high gluten strength were pre-selected for low N production.

Diversity and Genetic structure of the Spanish collection of durum wheat (Triticum turgidum L) landraces

The objectives of this study were to assess diversity and genetic structure of a collection of Spanish durum wheat (Triticum turgidum L) landraces, using SSRs, DArTs and gliadin-markers, and to correlate the distribution of diversity with geographic and climatic features, as well as agro-morphological traits. A high level of diversity was detected in the genotypes analyzed, which were separated into nine populations with a moderate to great genetic divergence among them. The three subspecies taxa, dicoccon, turgidum and durum, present in the collection, largely determined the clustering of the populations. Genotype variation was lower in dicoccon (one major population) and turgidum (two major populations) than in durum (five major populations). Genetic differentiation by the agro-ecological zone of origin was greater in dicoccon and turgidum than in durum. DArT markers revealed two geographic substructures, east-west for dicoccon and northeast-southwest for turgidum. The ssp. durum had a more complex structure, consisting of seven populations with high intra-population variation. DArT markers allowed the detection of subgroups within some populations, with agro-morphological and gliadin differences, and distinct agro-ecological zones of origin. Two different phylogenetic groups were detected; revealing that some durum populations were more related to ssp. turgidum from northern Spain, while others seem to be more related to durum wheats from North Africa

Estudio molecular de gluteninas de alto y bajo peso molecular en Triticum aestivum ssp. vulgare L. y su relación con la calidad panadera

El trigo blando (Triticum aestivum ssp vulgare L., AABBDD, 2n=6x=42) presenta propiedades viscoélasticas únicas debidas a la presencia en la harina de las prolaminas: gluteninas y gliadinas. Ambos tipos de proteínas forman parte de la red de gluten. Basándose en la movilidad en SDS-PAGE, las gluteninas se clasifican en dos grupos: gluteninas de alto peso molecular (HMW-GS) y gluteninas de bajo peso molecular (LMW-GS). Los genes que codifican para las HMW-GS se encuentran en tres loci del grupo 1 de cromosomas: Glu-A1, Glu-B1 y Glu-D1. Cada locus codifica para uno o dos polipéptidos o subunidades. La variación alélica de las HMW-GS es el principal determinante de de la calidad harino-panadera y ha sido ampliamente estudiado tanto a nivel de proteína como de ADN. El conocimiento de estas proteínas ha contribuido sustancialmente al progreso de los programas de mejora para la calidad del trigo. Comparadas con las HMW-GS, las LMW-GS forman una familia proteica mucho más compleja. La mayoría de los genes LMW se localizan en el grupo 1 de cromosomas en tres loci: Glu-A3, Glu-B3 y Glu-D3 que se encuentran estrechamente ligados a los loci que codifican para gliadinas. El número de copias de estos genes ha sido estimado entre 10-40 en trigo hexaploide, pero el número exacto aún se desconoce debido a la ausencia de un método eficiente para diferenciar los miembros de esta familia multigénica. La nomenclatura de los alelos LMW-GS por electroforesis convencional es complicada, y diferentes autores asignan distintos alelos a la misma variedad lo que dificulta aún más el estudio de esta compleja familia. El uso de marcadores moleculares para la discriminación de genes LMW, aunque es una tarea dificil, puede ser muy útil para los programas de mejora. El objetivo de este trabajo ha sido profundizar en la relación entre las gluteninas y la calidad panadera y desarrollar marcadores moleculares que permitan ayudar en la correcta clasificación de HMW-GS y LMW-GS. Se han obtenido dos poblaciones de líneas avanzadas F4:6 a partir de los cruzamientos entre las variedades ‘Tigre’ x ‘Gazul’ y ‘Fiel’ x ‘Taber’, seleccionándose para los análisis de calidad las líneas homogéneas para HMW-GS, LMW-GS y gliadinas. La determinación alélica de HMW-GS se llevó a cabo por SDS-PAGE, y se complementó con análisis moleculares, desarrollándose un nuevo marcador de PCR para diferenciar entre las subunidades Bx7 y Bx7*del locus Glu-B1. Resumen 2 La determinación alélica para LMW-GS se llevó a cabo mediante SDS-PAGE siguiendo distintas nomenclaturas y utilizando variedades testigo para cada alelo. El resultado no fue concluyente para el locus Glu-B3, así que se recurrió a marcadores moleculares. El ADN de los parentales y de los testigos se amplificó usando cebadores diseñados en regiones conservadas de los genes LMW y fue posteriormente analizado mediante electroforesis capilar. Los patrones de amplificación obtenidos fueron comparados entre las distintas muestras y permitieron establecer una relación con los alelos de LMW-GS. Con este método se pudo aclarar la determinación alélica de este locus para los cuatro parentales La calidad de la harina fue testada mediante porcentaje de contenido en proteína, prueba de sedimentación (SDSS) y alveógrafo de Chopin (parámetros P, L, P/L y W). Los valores fueron analizados en relación a la composición en gluteninas. Las líneas del cruzamiento ‘Fiel’ x ‘Taber’ mostraron una clara influencia del locus Glu-A3 en la variación de los valores de SDSS. Las líneas que llevaban el nuevo alelo Glu-A3b’ presentaron valores significativamente mayores que los de las líneas con el alelo Glu-A3f. En las líneas procedentes del cruzamiento ‘Tigre ’x ‘Gazul’, los loci Glu-B1 y Glu-B3 loci mostraron ambos influencia en los parámetros de calidad. Los resultados indicaron que: para los valores de SDSS y P, las líneas con las HMW-GS Bx7OE+By8 fueron significativamente mejores que las líneas con Bx17+By18; y las líneas que llevaban el alelo Glu-B3ac presentaban valores de P significativamente superiores que las líneas con el alelo Glu-B3ad y significativamente menores para los valores de L . El análisis de los valores de calidad en relación a los fragmentos LMW amplificados, reveló un efecto significativo entre dos fragmentos (2-616 y 2-636) con los valores de P. La presencia del fragmento 2-636 estaba asociada a valores de P mayores. Estos fragmentos fueron clonados y secuenciados, confirmándose que correspondían a genes del locus Glu-B3. El estudio de la secuencia reveló que la diferencia entre ambos se hallaba en algunos SNPs y en una deleción de 21 nucleótidos que en la proteína correspondería a un InDel de un heptapéptido en la región repetida de la proteína. En este trabajo, la utilización de líneas que difieren en el locus Glu-B3 ha permitido el análisis de la influencia de este locus (el peor caracterizado hasta la fecha) en la calidad panadera. Además, se ha validado el uso de marcadores moleculares en la determinación alélica de las LMW-GS y su relación con la calidad panadera. Summary 3 Bread wheat (Triticum aestivum ssp vulgare L., AABBDD, 2n=6x=42) flour has unique dough viscoelastic properties conferred by prolamins: glutenins and gliadins. Both types of proteins are cross-linked to form gluten polymers. On the basis of their mobility in SDS-PAGE, glutenins can be classified in two groups: high molecular weight glutenins (HMW-GS) and low molecular weight glutenins (LMW-GS). Genes encoding HMW-GS are located on group 1 chromosomes in three loci: Glu-A1, Glu-B1 and Glu-D1, each one encoding two polypeptides, named subunits. Allelic variation of HMW-GS is the most important determinant for bread making quality, and has been exhaustively studied at protein and DNA level. The knowledge of these proteins has substantially contributed to genetic improvement of bread quality in breeding programs. Compared to HMW-GS, LMW-GS are a much more complex family. Most genes encoded LMW-GS are located on group 1 chromosomes. Glu-A3, Glu-B3 and Glu-D3 loci are closely linked to the gliadin loci. The total gene copy number has been estimated to vary from 10–40 in hexaploid wheat. However, the exact copy number of LMW-GS genes is still unknown, mostly due to lack of efficient methods to distinguish members of this multigene family. Nomenclature of LMW-GS alleles is also unclear, and different authors can assign different alleles to the same variety increasing confusion in the study of this complex family. The use of molecular markers for the discrimination of LMW-GS genes might be very useful in breeding programs, but their wide application is not easy. The objective of this work is to gain insight into the relationship between glutenins and bread quality, and the developing of molecular markers that help in the allele classification of HMW-GS and LMW-GS. Two populations of advanced lines F4:6 were obtained from the cross ‘Tigre’ x ‘Gazul’ and ‘Fiel’ x ‘Taber’. Lines homogeneous for HMW-GS, LMW-GS and gliadins pattern were selected for quality analysis. The allele classification of HMW-GS was performed by SDS-PAGE, and then complemented by PCR analysis. A new PCR marker was developed to undoubtedly differentiate between two similar subunits from Glu-B1 locus, Bx7 and Bx7*. The allele classification of LMW-GS was initially performed by SDS-PAGE following different established nomenclatures and using standard varieties. The results were not completely concluding for Glu-B3 locus, so a molecular marker system was applied. DNA from parental lines and standard varieties was amplified using primers designed in conserved domains of LMW genes and analyzed by capillary electrophoresis. The pattern of amplification products obtained was compared among samples and related to the protein allele classification. It was possible to establish a correspondence between specific amplification products and almost all LMW alleles analyzed. With this method, the allele classification of the four parental lines was clarified. Flour quality of F4:6 advanced lines were tested by protein content, sedimentation test (SDSS) and alveograph (P, L, P/L and W). The values were analyzed in relation to the lines prolamin composition. In the ‘Fiel’ x ‘Taber’ population, Glu-A3 locus showed an influence in SDSS values. Lines carrying new allele Glu-A3b’, presented a significantly higher SDSS value than lines with Glu-A3f allele. In the ‘Tigre ’x ‘Gazul’ population, the Glu-B1 and Glu-B3 loci also showed an effect in quality parameters, in SDSS, and P and L values. Results indicated that: for SDSS and P, lines with Bx7OE+By8 were significantly better than lines with Bx17+By18; lines carrying Glu-B3ac allele had a significantly higher P values than Glu-B3ad allele values. lines with and lower L The analysis of quality parameters and amplified LMW fragments revealed a significant influence of two peaks (2-616 y 2-636) in P values. The presence of 2-636 peak gave higher P values than 2-616. These fragments had been cloned and sequenced and identified as Glu-B3 genes. The sequence analysis revealed that the molecular difference between them was some SNPs and a small deletion of 21 nucleotides that in the protein would produce an InDel of a heptapeptide in the repetitive region. In this work, the analysis of two crosses with differences in Glu-3 composition has made possible to study the influence of LMG-GS in quality parameters. Specifically, the influence of Glu-B3, the most interesting and less studied loci has been possible. The results have shown that Glu-B3 allele composition influences the alveograph parameter P (tenacity). The existence of different molecular variants of Glu-B3 alleles have been assessed by using a molecular marker method. This work supports the use of molecular approaches in the study of the very complex LMW-GS family, and validates their application in the analysis of advanced recombinant lines for quality studies.

Adapting wheat sowing dates to projected climate change in the Australian subtropics: analysis of crop water use and yield

Projected increases in atmospheric carbon dioxide concentration ([CO2]) and air temperature associated with future climate change are expected to affect crop development, crop yield, and, consequently, global food supplies. They are also likely to change agricultural production practices, especially those related to agricultural water management and sowing date. The magnitude of these changes and their implications to local production systems are mostly unknown. The objectives of this study were to: (i) simulate the effect of projected climate change on spring wheat (Triticum aestivum L. cv. Lang) yield and water use for the subtropical environment of the Darling Downs, Queensland, Australia; and (ii) investigate the impact of changing sowing date, as an adaptation strategy to future climate change scenarios, on wheat yield and water use. The multimodel climate projections from the IPCC Coupled Model Intercomparison Project (CMIP3) for the period 2030–2070 were used in this study. Climate scenarios included combinations of four changes in air temperature (08C, 18C, 28C, and 38C), three [CO2] levels (380 ppm, 500 ppm, and 600 ppm), and three changes in rainfall (–30%, 0%, and +20%), which were superimposed on observed station data. Crop management scenarios included a combination of six sowing dates (1 May, 10 May, 20 May, 1 June, 10 June, and 20 June) and three irrigation regimes (no irrigation (NI), deficit irrigation (DI), and full irrigation (FI)). Simulations were performed with the model DSSAT4.5, using 50 years of daily weather data.Wefound that: (1) grain yield and water-use efficiency (yield/evapotranspiration) increased linearly with [CO2]; (2) increases in [CO2] had minimal impact on evapotranspiration; (3) yield increased with increasing temperature for the irrigated scenarios (DI and FI), but decreased for the NI scenario; (4) yield increased with earlier sowing dates; and (5) changes in rainfall had a small impact on yield for DI and FI, but a high impact for the NI scenario.

Wheat breeding nurseries, target environments, and indirect selection for grain yield

Use of appropriate nursery environments will maximize gain from selection for yield of wheat (Triticum aestivum L.) in the target population of environments of a breeding program. The objective of this study was to investigate how well-irrigated (low-stress) nursery environments predict yield of lines in target environments that varied in degree of water limitation. Fifteen lines were sampled from the preliminary yield evaluation stage of the Queensland wheat breeding program and tested in 26 trials under on-farm conditions (Target Environments) across nine years (1985 to 1993) and also in 27 trials conducted at three research stations (Nursery Environments) in three years (1987 to 1989). The nursery environments were structured to impose different levels of water and nitrogen (N) limitation, whereas the target environments represented a random sample of on-farm conditions from the target population of environments. Indirect selection and pattern analysis methods were used to investigate selection for yield in the nursery environments and gain from selection in the target environments. Yield under low-stress nursery conditions was an effective predictor of yield under similar low-stress target environments (r = 0.89, P < 0.01). However, the value of the low-stress nursery as a predictor of yield in the water-limited target environments decreased with increasing water stress (moderate stress r = 0.53, P < 0.05, to r = 0.38, P > 0.05; severe stress r = -0.08, P > 0.05). Yield in the stress nurseries was a poor predictor of yield in the target environments. Until there is a clear understanding of the physiological-genetic basis of variation for adaptation of wheat to the water-limited environments in Queensland, yield improvement can best be achieved by selection for a combination of yield potential in an irrigated low-stress nursery and yield in on-farm trials that sample the range of water-limited environments of the target population of environments.

Optimal Irrigation and N-fertilizer Management for Sustainable Winter Wheat Production in Khorezm, Uzbekistan

The efficiency of the nitrogen (N) application rates 0, 120, 180 and 240 kg N ha−1 in combination with low or medium water levels in the cultivation of winter wheat (Triticum aestivum L.) cv. Kupava was studied for the 2005–2006 and 2006–2007 growing seasons in the Khorezm region of Uzbekistan. The results show an impact of the initial soil Nmin (NO3-N + NH4-N) levels measured at wheat seeding on the N fertilizer rates applied. When the Nmin content in the 0–50 cm soil layer was lower than 10 mg kg−1 during wheat seeding in 2005, the N rate of 180 kg ha−1 was found to be the most effective for achieving high grain yields of high quality. With a higher Nmin content of about 30 mg kg−1 as was the case in the 2006 season, 120 kg N ha−1 was determined as being the technical and economical optimum. The temporal course of N2O emissions of winter wheat cultivation for the two water-level studies shows that emissions were strongly influenced by irrigation and N-fertilization. Extremely high emissions were measured immediately after fertilizer application events that were combined with irrigation events. Given the high impact of N-fertilizer and irrigation-water management on N2O emissions, it can be concluded that present N-management practices should be modified to mitigate emissions of N2O and to achieve higher fertilizer use efficiency.

Spectral and thermal sensing for nitrogen and water status in rainfed and irrigated wheat environments

Variable-rate technologies and site-specific crop nutrient management require real-time spatial information about the potential for response to in-season crop management interventions. Thermal and spectral properties of canopies can provide relevant information for non-destructive measurement of crop water and nitrogen stresses. In previous studies, foliage temperature was successfully estimated from canopy-scale (mixed foliage and soil) temperatures and the multispectral Canopy Chlorophyll Content Index (CCCI) was effective in measuring canopy-scale N status in rainfed wheat (Triticum aestivum L.) systems in Horsham, Victoria, Australia. In the present study, results showed that under irrigated wheat systems in Maricopa, Arizona, USA, the theoretical derivation of foliage temperature unmixing produced relationships similar to those in Horsham. Derivation of the CCCI led to an r2 relationship with chlorophyll a of 0.53 after Zadoks stage 43. This was later than the relationship (r2 = 0.68) developed for Horsham after Zadoks stage 33 but early enough to be used for potential mid-season N fertilizer recommendations. Additionally, ground-based hyperspectral data estimated plant N (g kg)1) in Horsham with an r2 = 0.86 but was confounded by water supply and N interactions. By combining canopy thermal and spectral properties, varying water and N status can potentially be identified eventually permitting targeted N applications to those parts of a field where N can be used most efficiently by the crop.

Models for the field-based toxicity of copper and zinc salts to wheat in 11 Australian soils and comparison to laboratory-based models

Laboratory-based relationships that model the phytotoxicity of metals using soil properties have been developed. This paper presents the first field-based phytotoxicity relationships. Wheat(Triticum aestivum L) was grown at 11 Australian field sites at which soil was spiked with copper (Cu) and zinc (Zn) salts. Toxicity was measured as inhibition of plant growth at 8 weeks and grain yield at harvest. The added Cu and Zn EC10 values for both endpoints ranged from approximately 3 to 4760 mg/kg. There were no relationships between field-based 8-week biomass and grain yield toxicity values for either metal. Cu toxicity was best modelled using pH and organic carbon content while Zn toxicity was best modelled using pH and the cation exchange capacity. The best relationships estimated toxicity within a factor of two of measured values. Laboratory-based phytotoxicity relationships could not accurately predict field-based phytotoxicity responses.