Association between grain yield, grain quality and morpho-physiological traits along ten cycles of recurrent selection in bread wheat (triticum aestivum L.)

The objective of the present investigation was to examine the relationships between agronomical behavior and grain quality along ten cycles of a recurrent selection program performed under rainfed condition. Twenty-four lines, four for each one of the 0, 2, 4, 6, 8 and 10 cycles of recurrent selection, were evaluated for two consecutive years (2011 and 2012). The experimental lines were evaluated under conventional (CT) and no tillage (NT) systems. Grain yield and grain weight were determined and harvest index and grain number estimated. Flour protein content, sodium dodecyl sulphate sedimentation (IS-SDS) and lactic acid SRC (LASRC) were considered as end-use quality predictive tests. The Spearman correlation coefficient was used to measure the relationships among yield, its components and grain quality parameters. Within the context of CT, flour protein content was negatively associated with all the agronomic variables. The IS-SDS has a negative association with the grain weight; meanwhile, LASRC associated positively with all the agronomic variables. When wheat was grown in NT, the relationship between IS-SDS and harvest index, like LASRC with all agronomic traits, was positive. Confining the discussion to the CT results, after ten cycles of recurrent selection the highest grain yield achieved was accompanied by a decrease in protein percentage. However, the decrease in the percentage of protein in more advanced selection cycles was offset by an improvement of its quality.Fil: Maich, Ricardo Héctor. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; ArgentinaFil: Steffolani, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; ArgentinaFil: Di Rienzo, Julio Alejandro. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; ArgentinaFil: Leon, Alberto Edel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; Argentin

Qeco: Una aplicación de arquitectura abierta para el desarrollo de aplicaciones de R con interfaz gráfica

Qeco surge para dar respuesta a los requerimientos de la comunidad de ecólogos para implementar métodos estadísticos y cuantitativos modernos basados en R en el marco de una aplicación con una interfaz gráfica. La principal característica que hace a Qeco diferente es que une lo mejor de las aplicaciones basadas en menús con el poder de R en una aplicación de arquitectura abierta diseñada para crecer de acuerdo a las necesidades y el conocimiento de los usuarios. Esta arquitectura permite crear aplicaciones personalizadas que pueden aprovechar el esfuerzo de múltiples desarrolladores, favoreciendo el nacimiento de proyectos colaborativos.Sociedad Argentina de Informática e Investigación Operativ

Network and biosignature analysis for the integration of transcriptomic and metabolomic data to characterize leaf senescence process in sunflower

In recent years, high throughput technologies have led to an increase of datasets from omics disciplines allowing the understanding of the complex regulatory networks associated with biological processes. Leaf senescence is a complex mechanism controlled by multiple genetic and environmental variables, which has a strong impact on crop yield. Transcription factors (TFs) are key proteins in the regulation of gene expression, regulating different signaling pathways; their function is crucial for triggering and/or regulating different aspects of the leaf senescence process. The study of TF interactions and their integration with metabolic profiles under different developmental conditions, especially for a non-model organism such as sunflower, will open new insights into the details of gene regulation of leaf senescence.Fil: Moschen, Sebastián Nicolás. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Higgins, Janet. The Genome Analysis Centre; Reino UnidoFil: Di Rienzo, Julio Alejandro. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; ArgentinaFil: Heinz, Ruth Amelia. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Fernández, Paula del Carmen. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Corn Geospatial strategy: a more deeply understanding of hybrid competitiveness and performance by combining digital tools and data modeling

The comparative performance trials (CPT) of experimental and commercial cultivars in multi-environment trials, allow the determination of genotype (G) response to the different environment (E) and interaction (GxE). The final goal is to provide selection guidelines to identify the best genotypes to advance in the pipeline of the breeding program. Nowadays, the use of the digital information technologies to monitoring yield can be used in the CPTs to accurate measuring and recording of grain yield as well as the local environmental context. This research was carried out at 138 locations corresponding to commercial fields located in Argentina. The harvested was made with yield monitor and weighing machine wagon. To compare the grain yield of hybrids within each E and GXE interaction, the MLM of ANAVA with spatial correlation was adjusted for each location. Whereas, for CPT-without spatial data the ANAVA simple was applicate. The new analytic strategy showed greater power to: (a) find significant differences (p<0.05) in the GxE interaction, (b) increase 2.5 times the amount of information generated, i.e. than 1 CPT (1 location) analyzed with the new strategy. The new approach improves the data-driven decision making to support advancement processes from precommercial to commercial.Sociedad Argentina de Informática e Investigación Operativ

Transcriptomic identification of candidate genes involved in sunflower responses to chilling and salt stresses based on cDNA microarray analysis

<p>Abstract</p> <p>Background</p> <p>Considering that sunflower production is expanding to arid regions, tolerance to abiotic stresses as drought, low temperatures and salinity arises as one of the main constrains nowadays. Differential organ-specific sunflower ESTs (expressed sequence tags) were previously generated by a subtractive hybridization method that included a considerable number of putative abiotic stress associated sequences. The objective of this work is to analyze concerted gene expression profiles of organ-specific ESTs by fluorescence microarray assay, in response to high sodium chloride concentration and chilling treatments with the aim to identify and follow up candidate genes for early responses to abiotic stress in sunflower.</p> <p>Results</p> <p>Abiotic-related expressed genes were the target of this characterization through a gene expression analysis using an organ-specific cDNA fluorescence microarray approach in response to high salinity and low temperatures. The experiment included three independent replicates from leaf samples. We analyzed 317 unigenes previously isolated from differential organ-specific cDNA libraries from leaf, stem and flower at R1 and R4 developmental stage. A statistical analysis based on mean comparison by ANOVA and ordination by Principal Component Analysis allowed the detection of 80 candidate genes for either salinity and/or chilling stresses. Out of them, 50 genes were up or down regulated under both stresses, supporting common regulatory mechanisms and general responses to chilling and salinity. Interestingly 15 and 12 sequences were up regulated or down regulated specifically in one stress but not in the other, respectively. These genes are potentially involved in different regulatory mechanisms including transcription/translation/protein degradation/protein folding/ROS production or ROS-scavenging. Differential gene expression patterns were confirmed by qRT-PCR for 12.5% of the microarray candidate sequences.</p> <p>Conclusion</p> <p>Eighty genes isolated from organ-specific cDNA libraries were identified as candidate genes for sunflower early response to low temperatures and salinity. Microarray profiling of chilling and NaCl-treated sunflower leaves revealed dynamic changes in transcript abundance, including transcription factors, defense/stress related proteins, and effectors of homeostasis, all of which highlight the complexity of both stress responses. This study not only allowed the identification of common transcriptional changes to both stress conditions but also lead to the detection of stress-specific genes not previously reported in sunflower. This is the first organ-specific cDNA fluorescence microarray study addressing a simultaneous evaluation of concerted transcriptional changes in response to chilling and salinity stress in cultivated sunflower.</p

Comparative Pathogenesis of Generalist AcMNPV and Specific RanuNPV in Larvae of Rachiplusia nu (Lepidoptera: Noctuidae) Following Single and Mixed Inoculations

The South American soybean pest, Rachiplusia nu (Guenée), is naturally infected by Autographa californica multiple nucleopolyhedrovirus (AcMNPV) and Rachiplusia nu nucleopolyhedrovirus (RanuNPV). We compared their pathogenicity to fourth-instar R. nu larvae, by evaluating time to death and virus spread throughout the tissues in single and mixed infections. Bioassays showed that generalist AcMNPV had a faster speed of kill than specific RanuNPV, while the mixed-virus treatment did not statistically differ from AcMNPV alone. Histopathology evidenced similar tissue tropism for both viruses, but co-inoculation resulted in mostly AcMNPV-infected cells. In sequential inoculations, however, the first virus administered predominated over the second one. Implications on baculovirus interactions and biocontrol potential are discussed.Instituto de Microbiología y Zoología Agrícola (IMYZA)Fil: Decker Franco, Cecilia. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Microbiología y Zoología Agrícola; ArgentinaFil: Decker Franco, Cecilia. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Taibo, Catalina Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Centro de Investigación en Ciencias Veterinarias y Agronómicas. Laboratorio Integral de Microscopía; ArgentinaFil: Di Rienzo, Julio A. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias. Cátedra de Estadística y Biometría; ArgentinaFil: Alfonso, Victoria. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Alfonso, Victoria. Instituto Nacional de Tecnología Agropecuaria (INTA). Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; ArgentinaFil: Arneodo, Joel D. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Microbiología y Zoología Agrícola; ArgentinaFil: Arneodo, Joel D. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; Argentin

Selección de atributos en clasificación supervisada. Uso de la entropía condicional.

Ponencia presentada en el IV Encuentro Iberoamericano de Biometría y XVIII Reunión Científica del Grupo Argentino de Biometría. Mar del Plata, Argentina, 25 al 27 de septiembre de 2013Las bases de datos de alta dimensionalidad pueden encontrarse en diferentes áreas de conocimiento. Los datos provenientes de microarreglos de ADN son buenos representantes de estos contextos y tienen, además, la particularidad de poseer mayor cantidad de atributos que de observaciones. Si bien, la clasificación supervisada suele ser una de las técnicas más usadas en estos casos, el “ruido” debido a las particularidades expuestas provocan que los clasificadores convencionales tengan resultados inestables. En este trabajo se propone el uso de la entropía condicional como medida para realizar la selección del subconjunto de atributos que distingan entre tratamientos en contextos de microarreglos de ADN. La entropía mide la cantidad media de información que es necesaria proveer para no tener incertidumbre sobre una variable determinada y tiene la ventaja de poder aplicarse a contextos con variables pertenecientes a cualquier escala de medición. Se desarrolló un algoritmo en R y se simularon diferentes escenarios de microarreglos de ADN. Las conclusiones se obtuvieron considerando el tamaño promedio del subconjunto seleccionado y el porcentaje de atributos seleccionados que efectivamente son diferenciales. Entre los resultados preliminares puede mencionarse que: en la mayoría de los casos, la entropía condicional con el subconjunto de atributos seleccionados es 0; a mayor cantidad de réplicas, mayor es el tamaño del subconjunto y mayor el porcentaje de atributos efectivamente diferenciales; y que, a mayor porcentaje de atributos diferenciales, menor es el tamaño del subconjunto de atributos seleccionados y mayor es el porcentaje de atributos efectivamente diferenciales.Fil: Romero, María del Carmen. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Económicas; Argentina.Fil: Di Rienzo, Julio Alejandro. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias. Cátedra de Estadística y Biometría; Argentina.Fil: Clausse, Alejandro. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Plasmas Densos Magnetizados (PLADEMA); Argentina