Períodos de interferência de plantas daninhas na cultura do girassol

The interference of weeds in sunflower cultivation can significantly reduce the productivity of achenes. The objective of this study was to determine the period before interference and total period of interference of the weed community on productivity and achene oil of sunflower cultivation. The experiment was conducted under field conditions in the fieldin Botucatu (SP) in the 2007/2008 agricultural year. The experimental design was a randomized complete block with four replications. The treatments were composed of portions represent periods of control and presence of weeds. For control periods, the culture was kept free of weeds by increasing periods of 7, 14, 21, 28, 35, 42, 49 and 110 days after the emergence (DAE) of sunflower. For periods of coexistence, the culture was maintained in the presence of the weed community for the same periods. We assessed the following variables: diameter of chapters, achene yield, oil yield of sunflower, density and dry matter of weeds and phytosociological indices. The period before the interference was 35 DAE culture to the productivity of achenes, and the total period of interference lasted until 24 DAE. For oil yield, the period before the interference was 25 DAE, whereas the total period of interference lasted for 14 DAE.

Parâmetros genéticos entre caracteres quantitativos no girassol como critério de seleção para produtividade de aquênios

Two experiments were conducted in southern Brazil in no-tillage system, in order to estimate genetic parameters and the direct and indirect effects of components for achene yield as a selection criterion in sunflower. We analyzed eight sunflower hybrids at two locations, in a randomized complete block design with four replicates, determined through quantitative descriptors: insertion height of the head, and head stem diameter, weight of 1000 achenes, number of achenes per head, mass by achene head and yield achene. Estimates of genetic parameters were based on combined analysis, decomposing interactions in genetic and environmental components. Considering the coefficient of genetic variation, indirect effects of components and heritability, there are higher possibilities for responses to selection in sunflower achenes by descriptors mass and mass of achenes per head, with its indirect association interrelated pathways for the increase in the achenes of yield.

Crescimento e produtividade do girassol na segunda aplicação de lodo de esgoto em diferentes manejos

Sewage sludge, as a soil fertilizer for crop production, has become a very important agricultural input since it is rich in nutrients, adds carbon to the soil and improves its chemical, physical, and biological characteristics. The aim of this study was to evaluate the effects of sewage sludge applied as a fertilizer for two consecutive years on sunflower plant growth and productivity. The experiment was conducted at the Experimental Farm of the College of Agriculture, a unit of the São Paulo State University (UNESP), in São Manuel, state of São Paulo, Brazil. The soil where the experiment was set is a Red Oxissol. The experiment consisted of 6 treatments with 5 replications. The experimental units were distributed in the field according to a randomized complete block design. ‘HELIO 251’ was the sunflower cultivar used in the experiment. The treatments were as follows: T0: check (no nitrogen applied); T1: conventional chemical fertilization; T2: 50% of the N dose from sewage sludge and 50% from a chemical fertilizer in side dress application; T3: 100% of the N dose from sewage sludge; T4: 150% of the N dose from sewage sludge; T5: 200% of the N dose from sewage sludge. The 150% of the N dose from sewage sludge treatment caused the plants to increase in height, in stem diameter, and in number of leaves per plant. The mixture in equal proportion of sewage sludge and a chemical fertilizer (treatment T2) resulted in an achene yield higher than that of the chemical fertilizer alone (treatment T1).

Correlation and path analysis as an indirect selection criterion for sunflower achene productivity

The study was conducted in two different locations in South Brazil, in tillage in the 2009/2010 season on eight sunflower hybrids, aiming to determine the path correlations and coefficients between primary and secondary characters on the main variable of achene productivity. The correlations were similar between environments. The characters of the head diameter and mass of a thousand achenes had a significant influence on sunflower productivity. Based on the magnitude of the direct and indirect effects, we highlighted all primary components on the main variable, beside the good determination coefficient and low residual effect. The secondary component, the number of achenes, despite the significant direct effect on productivity, was indirectly influenced by the primary components, making it an undesirable character for selection.

Yield-factor volatility models

The term structure of interest rates is often summarized using a handful of yield factors that capture shifts in the shape of the yield curve. In this paper, we develop a comprehensive model for volatility dynamics in the level, slope, and curvature of the yield curve that simultaneously includes level and GARCH effects along with regime shifts. We show that the level of the short rate is useful in modeling the volatility of the three yield factors and that there are significant GARCH effects present even after including a level effect. Further, we find that allowing for regime shifts in the factor volatilities dramatically improves the model’s fit and strengthens the level effect. We also show that a regime-switching model with level and GARCH effects provides the best out-of-sample forecasting performance of yield volatility. We argue that the auxiliary models often used to estimate term structure models with simulation-based estimation techniques should be consistent with the main features of the yield curve that are identified by our model.

Cultivar-specific effects of pathogen testing on storage root yield of sweet potato, Ipomoea batatas (L.) Lam.

The accumulation and perpetuation of viral pathogens over generations of clonal propagation in crop species such as sweet potato, Ipomoea batatas,inevitably result in a reduction in crop yield and quality. This study was conducted at Bundaberg, Australia to compare the productivity of field-derived and pathogen-tested (PT)clones of 14 sweet potato cultivars and the yield benefits of using healthy planting materials. The field-derived clonal materials were exposed to the endemic viruses, while the PT clones were subjected to thermotherapy and meristem-tip culture to eliminate viral pathogens. The plants were indexed for viruses using nitrocellulose membrane-enzyme-linked immunosorbent assay and graft-inoculations onto Ipomoea setosa. A net benefit of 38% in storage root yield was realised from using PT materials in this study.Conversely, in a similar study previously conducted at Kerevat, Papua New Guinea (PNG), a net deficit of 36% was realised. This reinforced our finding that the response to pathogen testing was cultivar dependent and that the PNG cultivars in these studies generally exhibited increased tolerance to the endemic viruses present at the respective trial sites as manifested in their lack of response from the use of PT clones. They may be useful sources for future resistance breeding efforts. Nonetheless, the potential economic gain from using PT stocks necessitates the use of pathogen testing on virus-susceptible commercial cultivars.

Manufacturing Yield Improvement by Clustering

Dealing with product yield and quality in manufacturing industries is getting more difficult due to the increasing volume and complexity of data and quicker time to market expectations. Data mining offers tools for quick discovery of relationships, patterns and knowledge in large databases. Growing self-organizing map (GSOM) is established as an efficient unsupervised datamining algorithm. In this study some modifications to the original GSOM are proposed for manufacturing yield improvement by clustering. These modifications include introduction of a clustering quality measure to evaluate the performance of the programme in separating good and faulty products and a filtering index to reduce noise from the dataset. Results show that the proposed method is able to effectively differentiate good and faulty products. It will help engineers construct the knowledge base to predict product quality automatically from collected data and provide insights for yield improvement.