Beaufils ranges to assess the cotton nutrient status in the southern region of Mato Grosso

The relationships between nutrient contents and indices of the Diagnosis and Recommendation Integrated System (DRIS) are a useful basis to determine appropriate ranges for the interpretation of leaf nutrient contents. The purpose of this study was to establish Beaufils ranges from statistical models of the relationship between foliar concentrations and DRIS indices, generated by two systems of DRIS norms - the F value and natural logarithm transformation - and assess the nutritional status of cotton plants, based on these Beaufils ranges. Yield data from plots (average acreage 100 ha) and foliar concentrations of macro and micronutrients of cotton (Gossypium hirsutum r. latifolium) plants, in the growing season 2004/2005, were stored in a database. The criterion to define the reference population consisted of plots with above-average yields + 0.5 standard deviation (over 4,575 kg ha-1 seed cotton yield). The best-fitting statistical model of the relationship between foliar nutrient concentrations and DRIS indices was linear, with R² > 0.8090, p < 0.01, except for N, with R² = 0.5987, p < 0.01. The two criteria were effective to diagnose the plant nutritional status. The diagnoses were not random, but based on the effectiveness of the chi-square-tested method. The agreement between the methods to assess the nutritional status was 92.59-100 %, except for S, with 74.07 % agreement.

Dynamics of ammonium and pH in the solution of soils with different salinity levels, growing irrigated rice

Rice in Rio Grande do Sul State is grown mostly under flooding, which induces a series of chemical, physical and biological changes in the root environment. These changes, combined with the presence of rice plants, affect the availability of exchangeable ammonium (NH4+) and pH of soil solution, whereas the dynamics of both variables can be influenced by soil salinity, a common problem in the coastal region. This study was conducted to evaluate the dynamics of exchangeable NH4+ and pH in the soil solution, and their relation in the solution of Albaqualf soils with different salinity levels, under rice. Four field experiments were conducted with soils with exchangeable Na percentage (ESP) of 5.6, 9.0, 21.2, and 32.7 %. Prior to flooding, soil solution collectors were installed at depths of 5, 10 and 20 cm. The soil solution was collected weekly, from 7 to 91 days after flooding (DAF), to analyze exchangeable NH4+ and pH in the samples. Plant tissue was sampled 77 DAF, to determine N uptake and estimate the contribution of other N forms to rice nutrition. The content of exchangeable NH4+ decreased over time at all sites and depths, with a more pronounced reduction in soils with lower salinity levels, reaching values close to zero. A possible contribution of non-exchangeable NH4+ forms and N from soil organic matter to rice nutrition was observed. Soil pH decreased with time in soils with ESP 5.6 and 9.0 %, being positively correlated with the decreasing NH4+ levels at these sites.

Least limiting water range in assessing compaction in a Brazilian Cerrado latosol growing sugarcane

In the south-central region of Brazil, there is a trend toward reducing the sugarcane inter-harvest period and increasing traffic of heavy harvesting machinery on soil with high water content, which may intensify the compaction process. In this study, we assessed the structural changes of a distroferric Red Latosol (Oxisol) by monitoring soil water content as a function of the Least Limiting Water Range (LLWR) and quantified its effects on the crop yield and industrial quality of the first ratoon crop of sugarcane cultivars with different maturation cycles. Three cultivars (RB 83-5054, RB 84-5210 and RB 86-7515) were subjected to four levels of soil compaction brought about by a differing number of passes of a farm tractor (T0 = soil not trafficked, T2 = 2 passes, T10 = 10 passes, and T20 = 20 passes of the tractor in the same place) in a 3 × 4 factorial arrangement with three replications. The deleterious effects on the soil structure from the farm machinery traffic were limited to the surface layer (0-10 cm) of the inter-row area of the ratoon crop. The LLWR dropped to nearly zero after 20 tractor passes between the cane rows. We detected differences among the cultivars studied; cultivar RB 86-7515 stood out for its industrial processing quality, regardless of the level of soil compaction. Monitoring of soil moisture in the crop showed exposure to water stress conditions, although soil compaction did not affect the production variables of the sugarcane cultivars. We thus conclude that the absence of traffic on the plant row maintained suitable soil conditions for plant development and may have offset the harmful effects of soil compaction shown by the high values for bulk density between the rows of the sugarcane cultivars.

ORGANIC MATTER FRACTIONS IN A QUARTZIPSAMMENT UNDER CULTIVATION OF IRRIGATED MANGO IN THE LOWER SÃO FRANCISCO VALLEY REGION, BRAZIL

Improper land use has lead to deterioration and depletion of natural resources, as well as a significant decline in agricultural production, due to decreased soil quality. Removal of native vegetation to make way for agricultural crops, often managed inadequately, results in soil disruption, decreased nutrient availability, and decomposition of soil organic matter, making sustainable agricultural production unviable. Thus, the aim of the present study was to evaluate the impact of growing irrigated mango (over a 20 year period) on the organic carbon (OC) stocks and on the fractions of soil organic matter (SOM) in relation to the native caatinga (xeric shrubland) vegetation in the Lower São Francisco Valley region, Brazil. The study was carried out on the Boa Esperança Farm located in Petrolina, Pernambuco, Brazil. In areas under irrigated mango and native caatinga, soil samples were collected at the 0-10 and 10-20 cm depths. After preparing the soil samples, we determined the OC stocks, carbon of humic substances (fulvic acid fractions, humic acid fractions, and humin fractions), and the light and heavy SOM fractions. Growing irrigated mango resulted in higher OC stocks; higher C stocks in the fulvic acid, humic acid, and humin fractions; and higher C stocks in the heavy and light SOM fraction in comparison to nativecaatinga, especially in the uppermost soil layer.

Comparative performance of supertree algorithms in large data sets using the soapberry family (Sapindaceae) as a case study.

For the last 2 decades, supertree reconstruction has been an active field of research and has seen the development of a large number of major algorithms. Because of the growing popularity of the supertree methods, it has become necessary to evaluate the performance of these algorithms to determine which are the best options (especially with regard to the supermatrix approach that is widely used). In this study, seven of the most commonly used supertree methods are investigated by using a large empirical data set (in terms of number of taxa and molecular markers) from the worldwide flowering plant family Sapindaceae. Supertree methods were evaluated using several criteria: similarity of the supertrees with the input trees, similarity between the supertrees and the total evidence tree, level of resolution of the supertree and computational time required by the algorithm. Additional analyses were also conducted on a reduced data set to test if the performance levels were affected by the heuristic searches rather than the algorithms themselves. Based on our results, two main groups of supertree methods were identified: on one hand, the matrix representation with parsimony (MRP), MinFlip, and MinCut methods performed well according to our criteria, whereas the average consensus, split fit, and most similar supertree methods showed a poorer performance or at least did not behave the same way as the total evidence tree. Results for the super distance matrix, that is, the most recent approach tested here, were promising with at least one derived method performing as well as MRP, MinFlip, and MinCut. The output of each method was only slightly improved when applied to the reduced data set, suggesting a correct behavior of the heuristic searches and a relatively low sensitivity of the algorithms to data set sizes and missing data. Results also showed that the MRP analyses could reach a high level of quality even when using a simple heuristic search strategy, with the exception of MRP with Purvis coding scheme and reversible parsimony. The future of supertrees lies in the implementation of a standardized heuristic search for all methods and the increase in computing power to handle large data sets. The latter would prove to be particularly useful for promising approaches such as the maximum quartet fit method that yet requires substantial computing power.

Bone histomorphometry of broilers submitted to different phosphorus sources in growing and finisher rations

The objective of this work was to identify alterations in the histomorphology of the cortical bone tissue of broilers submitted to growing and finisher rations formulated with five different sources of phosphorus: dicalcium phosphate, simple superphosphate, triple superphosphate, monoammonium phosphate and Araxá rock phosphate. Histological images had their components segmented, and were called regions of interest (ROI). Images were analyzed through developed algorithms, using the SCILAB mathematical environment. Eleven features were considered in order to obtain a complete description of the bone images: percentage of bone by area, ROI area, ROI perimeters, ROI elongation, ROI angle and their respective standard deviations, besides entropy of ROI angles and a texture-oriented measure (lacunarity). The substitution of dicalcium phosphate in growing and finisher rations for any other tested source of phosphorus caused significant changes on the hystomorphology of the cortical broilers bones, for example: diminution of bone percentage by area, increase of lacuna area and worse matrix homogeneity. Changes were more pronounced in the Araxá rock phosphate treatments, with the highest fluorine content, than in simple superphosphate, triple superphosphate and monoammonium phosphate treatments, which were similar.

Energy balance measurements over a banana orchard in the Semiarid region in the Northeast of Brazil

The objective of this work was to evaluate the reliability of eddy covariance measurements, analyzing the energy balance components, evapotranspiration and energy balance closure in dry and wet growing seasons, in a banana orchard. The experiment was carried out at a farm located within the irrigation district of Quixeré, in the Lower Jaguaribe basin, in Ceará state, Brazil. An eddy covariance system was used to measure the turbulent flux. An automatic weather station was installed in a grass field to obtain the reference evapotranspiration (ET0) from the combined FAO-Penman-Monteith method. Wind speed and vapor pressure deficit are the most important variables on the evaporative process in both growing seasons. In the dry season, the heat fluxes have a similar order of magnitude, and during the wet season the latent heat flux is the largest. The eddy covariance system had acceptable reliability in measuring heat flux, with actual evapotranspiration results comparing well with those obtained by using the water balance method. The energy balance closure had good results for the study area, with mean values of 0.93 and 0.86 for the dry and wet growing seasons respectively.

Climatic potential for wine grape production in the tropical north region of Minas Gerais State, Brazil

The tropical north region of Minas Gerais State is one of the least developed of Brazil and viticulture could be an alternative to develop its agriculture zone. The objective of this work was to evaluate the climatic potential of that region for wine grape production. The evaluations were carried out applying the Multicriteria Climatic Classification System (Geoviticulture MCC System), that utilizes three reference climatic indexes (Dryness Index - DI, Heliothermal Index - HI and Cool Night Index - CI). Three locations - Pirapora (17º 21'S, 44º56'W, 489m), Montes Claros (16º43'S, 43º52'W, 647m) and Diamantina (18º15'S, 43º36'W, 1297m) - and two potential production cycles along the year - October to March (spring-summer period) and April to September (autumn-winter period) - were evaluated. The results showed that in the spring-summer period (SS period) Pirapora and Montes Claros presented a 'humid, very warm and with warm nights' of viticultural climate, according to MCC System. For the autumn-winter period (AW period), those two regions presented a 'moderately dry, warm and with temperate nights' according to MCC System. Otherwise, the Diamantina SS period presented a 'humid, temperate warm and with temperate nights' viticultural climate. In the AW period, the Diamantina climatic condition values represent a 'subhumid, temperate and with cool nights' viticultural climate. Based on those results it can be concluded that the North Region of Minas Gerais State has a great climatic potential to became a grape-growing region for wine-making, specially in the autumn-winter period.

Variation of grain nitrogen content in relation with grain yield in old and modern Spanish wheats grown under a wide range of agronomic conditions in a Mediterranean region

Wheat yield and grain nitrogen concentration (GNC; mg N/g grain) are frequently negatively correlated. In most growing conditions, this is mainly due to a feedback process between GNC and the number of grains/m2. In Mediterranean conditions, breeders may have produced cultivars with conservative grain set. The present study aimed at clarifying the main physiological determinants of grain nitrogen accumulation (GNA) in Mediterranean wheat and to analyse how breeding has affected them. Five field experiments were carried out in north-eastern Spain in the 2005/06 and 2006/ 07 growing seasons with three cultivars released at different times and an advanced line. Depending on the experiment, source-sink ratios during grain filling were altered by reducing grain number/m2 either through pre-anthesis shading (unshaded control or 0.75 shading only between jointing and anthesis) or by directly trimming the spikes after anthesis and before the onset of the effective grain filling period (un-trimmed control or spikes halved 7–10 days after anthesis). Grain nitrogen content (GN content ; mg N/grain) decreased with the year of release of the genotypes. As the number of grains/m2 was also increased by breeding there was a clear dilution effect on the amount of nitrogen allocated to each grain. However, the increase in GN content in old genotypes did not compensate for the loss in grain nitrogen yield (GNY) due to the lower number of grains/m2. GN content of all genotypes increased (increases ranged from 0.13 to 0.40 mg N/grain, depending on experiment and genotype) in response to the post-anthesis spike trimming or pre-anthesis shading. The degree of source-limitation for GNA increased with the year of release of the genotypes (and thus with increases in grain number/m2) from 0.22 (mean of the four manipulative experiments) in the oldest cultivar to 0.51 (mean of the four manipulative experiments) in the most modern line. It was found that final GN content depended strongly on the source-sink ratio established at anthesis between the number of grains set and the amount of nitrogen absorbed at this stage. Thus, Mediterranean wheat breeding that improved yield through increases in grain number/m2 reduced the GN content by diluting a rather limited source of nitrogen into more grains. This dilution effect produced by breeding was further confirmed by the reversal effect produced by grain number/m2 reductions due to either pre-anthesis shading or post-anthesis spike trimming.

Applying precision feeding techniques in growing-finishing pig operations

The high cost of feed ingredients, the use of non-renewable sources of phosphate and the dramatic increase in the environmental load resulting from the excessive land application of manure are major challenges for the livestock industry. Precision feeding is proposed as an essential approach to improve the utilization of dietary nitrogen, phosphorus and other nutrients and thus reduce feeding costs and nutrient excretion. Precision feeding requires accurate knowledge of the nutritional value of feedstuffs and animal nutrient requirements, the formulation of diets in accordance with environmental constraints, and the gradual adjustment of the dietary nutrient supply to match the requirements of the animals. After the nutritional potential of feed ingredients has been precisely determined and has been improved by the addition of enzymes (e.g. phytases) or feed treatments, the addition of environmental objectives to the traditional feed formulation algorithms can promote the sustainability of the swine industry by reducing nutrient excretion in swine operations with small increases in feeding costs. Increasing the number of feeding phases can also contribute to significant reductions in nutrient excretion and feeding costs. However, the use of precision feeding techniques in which pigs are fed individually with daily tailored diets can further improve the efficiency with which pigs utilize dietary nutrients. Precision feeding involves the use of feeding techniques that allow the provision of the right amount of feed with the right composition at the right time to each pig in the herd. Using this approach, it has been estimated that feeding costs can be reduced by more than 4.6%, and nitrogen and phosphorus excretion can both be reduced by more than 38%. Moreover, the integration of precision feeding techniques into large-group production systems can provide real-time off-farm monitoring of feed and animals for optimal slaughter and production strategies, thus improving the environmental sustainability of pork production, animal well-being and meat-product quality.

Impact of anthracnose on the yield of soybean subjected to chemical control in the north region of Brazil

ABSTRACT Losses due to soybean anthracnose, caused by Colletotrichum truncatum, have not been systematically quantified in the field, and the efficacy of chemical control of this disease is not known. This study shows an estimate of losses associated with the disease in soybean crops in the north of the country. Two trials with cv. M9144 RR were carried out in commercial fields in Tocantins State in the 2010/2011 and 2011/2012 growing seasons, in randomized blocks, with four replicates. Foliar applications were performed on plants at R1/R2 and R5.2 stages, employing CO2-pressurized equipment and application volume of 200 L ha-1. Nine fungicides and one untreated control were compared, and the disease gradients in the two seasons were obtained. The percentage of infected pods was calculated at the R6 stage. Grain yield ranged from 3,288 to 3,708 kg/ha in the untreated plots in 2010/2011 and 2011/2012, respectively, and from 3,282 to 4,110 kg/ha in the treated plots. In the 2010/2011 season, only azoxystrobin + cyproconazole significantly reduced the disease incidence, compared to untreated control plots, not differing from the remaining treatments. In the 2011/2012 season, there were no significant differences between treated and untreated plots. Highly significant correlations (p < 0.01) were found between yield and soybean anthracnose incidence on pods in both years (r = -0.85). For each 1% increment in the disease incidence, c. 90 kg/ha of soybean grain were lost. The current study determined that significant losses due to anthracnose occur in commercial crops in the north of the country and highlighted the limitation of chemical control as anthracnose management method.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Opportunity meets uncertainty. Towards sustainable business in the Arctic region

The Arctic region is experiencing a significant change in terms of climate change and a growing economic interest towards its natural resources and emerging business opportunities. The purpose of this study is to explore how can Finnish companies create sustainable business in the Arctic. This is done by examining the arctic business environment, identifying sectors with growth potential, addressing challenges related to operating in the Arctic and suggesting how to ensure sustainability and succeed in the globally competed arctic market. The theoretical framework is based on theories of sustainable development, corporate social responsibility and the role of strategy in creating sustainable business. Empirical data was collected by using qualitative research methods: first, background knowledge was formed based on written documents and, secondly, six expert interviews were conducted in early 2014. The interviewees represented the viewpoints of companies, political decision makers and NGO’s. The analysis of the data was conducted using thematic categorization. The empirical findings of the study suggest that in order to create sustainable business in the Arctic companies should adopt a long-term perspective, embrace a holistic approach to sustainability, understand interdependencies between the dimensions of sustainability and aim at high-level engagement in responsible behavior. To succeed in the arctic market core competencies, customer needs, multivendor cooperation and long-term presence need to be invested in on a company level. In addition, to promote and advance arctic development on a national level support is needed in terms of investments in infrastructure, funding research and design, creating a regulative framework and removing barriers of trade.

The Terroir of Winter Hardiness: Investigation of Winter Hardiness, Water Metrics, and Yield of Riesling and Cabernet Franc in the Niagara Region Using Geomatic Technologies

Grapevine winter hardiness is a key factor in vineyard success in many cool climate wine regions. Winter hardiness may be governed by a myriad of factors in addition to extreme weather conditions – e.g. soil factors (texture, chemical composition, moisture, drainage), vine water status, and yield– that are unique to each site. It was hypothesized that winter hardiness would be influenced by certain terroir factors , specifically that vines with low water status [more negative leaf water potential (leaf ψ)] would be more winter hardy than vines with high water status (more positive leaf ψ). Twelve different vineyard blocks (six each of Riesling and Cabernet franc) throughout the Niagara Region in Ontario, Canada were chosen. Data were collected during the growing season (soil moisture, leaf ψ), at harvest (yield components, berry composition), and during the winter (bud LT50, bud survival). Interpolation and mapping of the variables was completed using ArcGIS 10.1 (ESRI, Redlands, CA) and statistical analyses (Pearson’s correlation, principal component analysis, multilinear regression) were performed using XLSTAT. Clear spatial trends were observed in each vineyard for soil moisture, leaf ψ, yield components, berry composition, and LT50. Both leaf ψ and berry weight could predict the LT50 value, with strong positive correlations being observed between LT50 and leaf ψ values in eight of the 12 vineyard blocks. In addition, vineyards in different appellations showed many similarities (Niagara Lakeshore, Lincoln Lakeshore, Four Mile Creek, Beamsville Bench). These results suggest that there is a spatial component to winter injury, as with other aspects of terroir, in the Niagara region.

Revisiting optimization algorithms for maximum likelihood estimation

Parmi les méthodes d’estimation de paramètres de loi de probabilité en statistique, le maximum de vraisemblance est une des techniques les plus populaires, comme, sous des conditions l´egères, les estimateurs ainsi produits sont consistants et asymptotiquement efficaces. Les problèmes de maximum de vraisemblance peuvent être traités comme des problèmes de programmation non linéaires, éventuellement non convexe, pour lesquels deux grandes classes de méthodes de résolution sont les techniques de région de confiance et les méthodes de recherche linéaire. En outre, il est possible d’exploiter la structure de ces problèmes pour tenter d’accélerer la convergence de ces méthodes, sous certaines hypothèses. Dans ce travail, nous revisitons certaines approches classiques ou récemment d´eveloppées en optimisation non linéaire, dans le contexte particulier de l’estimation de maximum de vraisemblance. Nous développons également de nouveaux algorithmes pour résoudre ce problème, reconsidérant différentes techniques d’approximation de hessiens, et proposons de nouvelles méthodes de calcul de pas, en particulier dans le cadre des algorithmes de recherche linéaire. Il s’agit notamment d’algorithmes nous permettant de changer d’approximation de hessien et d’adapter la longueur du pas dans une direction de recherche fixée. Finalement, nous évaluons l’efficacité numérique des méthodes proposées dans le cadre de l’estimation de modèles de choix discrets, en particulier les modèles logit mélangés.