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Crop canopy optical reflectance and ultrasonic sensors provide a means of estimating the spatial variability of biomass and nitrogen uptake by sugarcane during the in-season period. The objective of this paper is to assess the crop canopy reflectance and ultrasonic crop height for predicting sugarcane biomass and N-uptake until the later fertilization stages. An ultrasonic sensor was deployed to measure canopy height, which were combined with optical reflectance sensor to characterize the spatial variability of the crop growth in four commercial fields in southeast Brazil during three different growing stages for dry and wet seasons. Ten sampling location points in each field were defined to determine plant biomass and N-uptake through traditional measurements. The points in each field were used to relate the actual biomass and N-uptake with the sensor data and compare them using the coefficient of determination and standard errors; this defined the best approach in each situation according to the multivariable statistics. It was found that both sensor systems enable to correlate its data with sugarcane biomass and N-uptake. Canopy reflectance sensor produced a better assessment of crop growth at the earlier growth stage whereas the ultrasonic sensor resulted in more accurate predictions at the later growing stages. It was proven that canopy height is season dependent whereas the reflectance data is growth stage dependent. The integration of both sensing systems improved the predictions of sugarcane biomass and N-uptake. It could be an alternative to guide local interventions by sugarcane industry during the growing season. [ABSTRACT FROM AUTHOR]

We characterized bovine viral diarrhea virus (BVDV)-related abortions in cattle and identified the species and subgenotypes in the state of Santa Catarina, southern Brazil. Our RT-PCR assay was positive for BVDV in 5 fetuses from different farms; however, 3 of the 5 fetuses were also PCR-positive for Neospora caninum. In the 5 BVDV-positive fetuses, gross lesions included fetal mummification (1), hepatomegaly (1), subcutaneous edema (1), and perirenal edema (1). Predominant histologic lesions included epicarditis and mild-to-moderate lymphoplasmacytic myocarditis (5), mild multifocal lymphoplasmacytic interlobular pneumonia (4), nephrosis associated with moderate multifocal interstitial nephritis (1), moderate multifocal lymphoplasmacytic necrotic hepatitis (1), and mild multifocal lymphoplasmacytic meningitis (1). The amplification products from the Pestivirus 5′UTR region of 4 of the 5 fetuses had 96.3–100% similarity between fetal strains and reference strains. The samples were distributed into 2 branches of the phylogenetic tree; strains UDESC:01, UDESC:02, and UDESC:05 clustered in the BVDV-1e branch, uncommon in the Americas, and strain UDESC:04 clustered in the BVDV-2b branch. The three 1e strains had 96.9–97.4% similarity. [ABSTRACT FROM AUTHOR]

Background and aims: There are controversies in the literature regarding the edaphic factors that may interfere with the occurrence of Rhizoctonia root rot in soybean, a disease caused by the soilborne fungus Rhizoctonia solani. The objective of this study was to determine which chemical and physical soil attributes are associated with the occurrence of Rhizoctonia root rot in soybean grown in a subtropical environment. Methods: Four fields with history of disease occurrence were selected, according to their soil class variability (Acrisol, Cambiol Ta, Cambisol Tb and Nitisol), in the municipality of Soledade, Rio Grande do Sul, Brazil. In each field, soil samples were collected in the 0–10 cm layer, inside and outside the bare patch with Rhizoctonia root rot, and in four repetitions for analysis of chemical and physical attributes. Results: The exchangeable contents and the saturation by aluminum and the extractable copper content were higher in the patch with the disease. On the other hand, the indicators of lower soil acidity (higher exchangeable calcium and magnesium content, pH value and base saturation) were the ones most associated with the area outside the patch. There was some association with soil texture regarding high clay content where the disease has been observed. Conclusion: Chemical attributes related to acidic soils are the ones most associated to the incidence of Rhizoctonia root rot in soybean grown in a subtropical environment in southern Brazil. [ABSTRACT FROM AUTHOR]

Coffee has high relevance in the Brazilian agricultural scenario, as Brazil is the largest producer and exporter of coffee in the world. Strategies to advance the production of coffee grains involve better understanding its spatial variability along fields. The objectives of this study were to adjust yield-prediction models based on a time series of satellite images and high-density yield data, and to indicate the best phenological stage of coffee crop to obtain satellite images for this purpose. The study was conducted during three seasons (2019, 2020 and 2021) in a commercial area (10.24 ha), located in the state of Minas Gerais, Brazil. Data were obtained using a harvester equipped with a yield monitor that measures the volume of coffee harvested with 3.0 m of spatial resolution. Satellite images from the PlanetScope (PS) platform were used. Random forest (RF) regression and multiple linear regression (MLR) models were fitted to different datasets composed of coffee yield and time series of satellite-image data ((1) Spectral bands—red, green, blue and near-infrared; (2) Normalized difference vegetation index (NDVI); or (3) Green normalized difference vegetation index (GNDVI)). Whether using RF or MLR, the spectral bands, NDVI and GNDVI reproduced the spatial variability of yield maps one year before harvest. This information can be of critical importance for management decisions across the season. For yield quantification, the RF model using spectral bands showed the best results, reaching R2 of 0.93 for the validation set, and the lowest errors of prediction. The most appropriate phenological stage for satellite-image data acquisition was the dormancy phase, observed during the dry season months of July and August. These findings can help to monitor the spatial and temporal variability of the fields and guide management practices based on the premises of precision agriculture. [ABSTRACT FROM AUTHOR]

In Brazil there is little information on the reaction of soybean cultivars to Globisporangium and Pythium species that can cause damping‐off. Thus, the objective of this study was to characterize the reactions to Globisporangium irregulare isolate UPFOM03, G. ultimum var. sporangiiferum isolate UPFPAN06 and Pythium conidiophorum isolate UPFSA03 of 50 cultivars adapted to southern Brazil. The experiment was carried out twice in a randomized complete block design with three replications. A root rot assay was performed in a growth chamber and emergence (%), emergence speed index (ESI), total dry mass per seedling (TDM; g) and root rot severity index (RRSI) were determined. There was a significant (p < 0.05) difference among the cultivars on all the variables. The least susceptible cultivars to G. irregulare were BRS 5804, BMX Compacta, FPS 1867, BMX Fibra, BMX Apolo, M6410, M6210, BMX Elite and BRS 5601. However, the least susceptible cultivars to G. ultimum var. sporangiiferum were M6410, M6210, BMX Tornado, NS 6601, NS 5258, NS 6909, BMX Fibra, FPS 1954, M5917, BMX Delta, FPS 1867, BMX Cromo, NEO 610, BMX Elite, DM 61i59, BMX Apolo, BMX Compacta and M5947. Thirty‐six soybean cultivars were less susceptible to P. conidiophorum, which was also less aggressive than G. irregulare and G. ultimum var. sporangiiferum. In conclusion, there are some soybean cultivars that are less susceptible to the three oomycete isolates and should be preferred in fields with a history of damping‐off. [ABSTRACT FROM AUTHOR]

Daily streamflow dynamics can be accurately simulated by conceptual models as simple as a single bucket in some catchments, while they require more complex configurations in other catchments. However, without resorting to calibration, anticipating where and why a given model structure may be appropriate remains difficult. In this work, we explored the feasibility of relating suitable model structures to the climate and streamflow characteristics of 508 catchments in Brazil. Specifically, we tested four model structures using up to three reservoirs, where each reservoir is intended to represent a catchment function: the rainfall‐runoff threshold, the fast, and the slow hydrograph response. We hypothesized a relationship between suitable model structures and hydrological signatures of aridity (IA) and baseflow index (IB). Our results show that different classes of signatures resulted in distinct patterns of model performance. Wet catchments (IA < 0.9) with low baseflow (IB < 0.4) were the easiest to model, with a single‐reservoir model presenting a relatively good performance. In the case of low baseflow, adding a rainfall‐runoff threshold reservoir resulted in better performance than adding a slow response reservoir, whereas in the case of high baseflow (IB < 0.6) the opposite occurred. In the case of low baseflow, the inclusion of a slow response reservoir helped the simulation of dry catchments (IA < 1.1), but not of wet ones, which we attributed to the impact of permeability in dry catchments. These results indicate a path toward model structure identification from streamflow signatures and potentially from landscape features. Key Points: Baseflow and aridity help classify suitable model structures for different catchments in BrazilA single bucket model performs relatively well in wet catchments with low baseflow, mainly in southern BrazilIndependently of model structure, performance is generally lower in drier than in wetter catchments [ABSTRACT FROM AUTHOR]

The intervention process in historical buildings involves the application of a scientific methodology for the materials characterization. In Porto Alegre — RS, Brazil, several buildings with patrimonial value from the nineteenth and early twentieth centuries were preserved. This study presents the physicochemical analysis of mortar coating samples obtained from two buildings, the commercial and residential building "Frasca House" (1911) and the Metropolitan Curia of Porto Alegre (1888). The visual investigation and aspects of the color and morphology of the samples were determined with a stereoscopic microscope. Chemical analyses provided information on the binder:aggregate proportion and qualitative soluble salts, correlated with deterioration caused by efflorescence. Microstructural analysis allowed to determine the nature of the binders, aggregates and fine particulates. It is expected to contribute, in restoration interventions, to the choice and quantity of materials compatible with the original evaluated here, preserving it and, thus, extending the service life of the building. [ABSTRACT FROM AUTHOR]

Given the uncertainty surrounding the safety of genetically modified organisms (GMOs), the precautionary principle and constitution provide that consumers should have the right to access adequate information on the presence of transgenics through food labelling. This article discusses the implications of proposed modifications to GM food labelling in Brazil. Current labelling legislation and the government agencies involved in labelling do not guarantee that food products not bearing GMO labels are free of transgenics. The approval of Chamber of Deputies Bill No. 34/2015 goes against the Consumer Protection Code by undermining consumer autonomy and choice. In addition, it is likely to weaken the country's biosurveillance capabilities to identify and seize products that have a harmful effect on the health of humans, animals and the environment. The proposed changes constitute a retrograde step in the regulation of food labelling in Brazil and violate the individual and collective rights enshrined in the Federal Constitution, Consumer Protection Code, and international agreements signed by Brazil. [ABSTRACT FROM AUTHOR]

Native vegetation in private lands plays an important role in providing ecosystem services and safeguarding biodiversity worldwide. Legal protection rules of this vegetation are thus crucial. In Brazil, since 1934, there has been a requirement for landowners to preserve a percentage of their land covered with native vegetation, the Legal Reserve. However, the 1934 legislation applies only to arboreal vegetation, while the protection of savannahs and grasslands begins after 1965 and 1989. The reference year for the application of Legal Reserves can thus have significant impacts on the amount of native vegetation legally protected. Here we tested the effects on Legal Reserve cover in São Paulo State, considering two different legal benchmarks as starting points: 1934 and 1965. Given that the 1934 law precedes the first aerial mapping in Brazil, we developed a methodology to estimate past native vegetation cover through a probabilistic approach. The forest deficit considering 1934 as the initial point is 3% lower than the one starting with the 1965 benchmark. Comparing both scenarios, the 1934 led to a reduction of 1255 farms with Legal Reserve deficit from a total of 30,417. For both scenarios, Legal Reserve deficits were concentrated in the West, Northwest, and Mid-west regions of the state. The outcomes showed that the benchmark change does not significantly affect the total area of Legal Reserves protection, the number of farms potentially benefited by this mechanism, and the amount of native vegetation deficit. However, the use of the 1934 as an initial date for considering protection of Legal Reserve can delay the implementation of the law due to a time-consuming farm-by-farm analysis, once the probabilistic map has an intrinsic limitation for an automatic process. Thus, the environmental gains with the adoption of 1934 as the initial date do not overcome the limitations of using a probabilistic map, suggesting that effective law enforcement depends on reliable and more recent baselines, allowing semi-automated analyses. This scientific evidence can be adopted by the other Brazilian States that have not yet defined the initial legal benchmark, balancing the advantages and disadvantages of adopting the 1934 Forest Act. • We compare scenarios for the Forest Act implementation considering different past vegetation cover benchmarks (1934 and 1965). • We developed a methodology for estimating native vegetation cover in 1934, because of lack of past spatialized land-use data. • The forest deficit for the benchmark of 1934 is only 3% higher than the one of the 1965 benchmark. • Given the uncertainties of the probabilistic map, the policy implementation can be delayed if 1934 benchmark is adopted. • Even with restrictions, this is the best possible map for the 1934 benchmark and can support decision-making. [ABSTRACT FROM AUTHOR]

Damping‐off of soybean is a common problem in some fields in southern Brazil. Frequently, Phytophthora sojae has been pointed out as the main causal agent. However, questions were raised as to whether other oomycetes could also be present. Hence, the objectives of this study were to isolate, identify, and determine the pathogenicity and aggressiveness of oomycetes isolated from soybean seedlings. Thirty‐three isolates were obtained from 13 fields. Isolates were identified based on morphology and molecular methods. Nine species were recovered: Pythium conidiophorum (n = 14, 42.4%), Globisporangium rostratifingens (n = 7, 21.2%), G. irregulare (n = 2, 6.1%), G. spinosum (n = 1, 3.0%), G. ultimum var. sporangiiferum (n = 2, 6.1%), Pythium acanthicum (n = 2, 6.1%), P. deliense (n = 1, 3.0%), P. inflatum (n = 1, 3.0%), and P. torulosum (n = 3, 9.1%). Pathogenicity and aggressiveness were determined with two soybean cultivars (DM57i52 and NEO530) in a seed rot assay and a root rot assay. All isolates were pathogenic to soybean with variable levels of aggressiveness in both assays. The range of seed disease severity index varied from 7.5 to 100 for DM57i52 and from 23.1 to 100 for NEO530. The mean root disease severity index of the soybean cultivars ranged from 29.4 to 92.8. This is the first official report of G. irregulare, G. rostratifingens, G. spinosum, G. ultimum var. sporangiiferum, P. acanthicum, P. conidiophorum, P. deliense, P. inflatum, and P. torulosum causing damping‐off of soybean in the state of Rio Grande do Sul in southern Brazil. [ABSTRACT FROM AUTHOR]

Nitrogen management in crops is a key activity for agricultural production. Methods that can determine the levels of this element in plants in a quick and non-invasive way are extremely important for improving production systems. Within several fronts of study on this subject, proximal and remote sensing methods are promising techniques. In this regard, this research sought to demonstrate the relationships between variations in leaf nitrogen content (LNC) and sugarcane spectral behaviour. The work was carried out in three experimental areas in São Paulo State, Brazil, with different soils, varieties and nitrogen rates during the 2012/13 and 2013/14 seasons. A significant correlation was observed between the LNC and variations in the sugarcane spectra. The green and red-edge spectral bands were the most consistent and stable predictors of LNC among the evaluated harvests. Stepwise multiple linear regression analysis (MSLR) generated better models for LNC estimation when calibrated with experimental area, independent of the variety. The present research demonstrates that specific wavelengths are associated with the variation in LNC in sugarcane, and these are reported in the green region (near 550 nm) and in the red-edge wavelengths (680 to 720 nm). These results may help in future research on the direct in situ application of nitrogen fertilizers. [ABSTRACT FROM AUTHOR]

Polyhalite, a source of potassium (K) and other nutrients, has been suggested as an alternative to fertilizer in Brazil. Two greenhouse pot experiments were carried out to evaluate the agronomic efficiency of polyhalite as a K and multinutrient source. Soil samples were collected from the Brazilian Cerrado. Pots were filled with 2 kg of soil. Treatments were composed of muriate of potash (MOP) and polyhalite was applied at rates of 20, 40, 80, 120, 160, and 200 mg K kg−1 soil in experiment I. A mix of soluble sources of K, sulfur (S), calcium (Ca), and magnesium (Mg) was compared to polyhalite at the same rates of 0.33, 0.66, 1.33, 2.00, 2.66, and 3.33 g pot−1 in experiment II. After 45 days of vegetative corn growth, plants and soil were collected. In experiment I, rates of K influenced yield of corn dry matter, but not the source of K. Corn dry matter yield in experiment II was higher with polyhalite. Polyhalite was similar or superior to conventional sources and was highly efficient at supplying K, Ca, Mg, and S to plants. [ABSTRACT FROM AUTHOR]

A high level of variation of biodiversity recovery within a landscape during forest restoration presents obstacles to ensure large‐scale, cost‐effective and long‐lasting ecological restoration. There is an urgent need to predict landscape variation in forest restoration success at a global scale.We conducted a meta‐analysis comprising 135 study landscapes to predict and map landscape variation in forest restoration success in tropical and temperate forest biomes. Our analysis was based on the amount of forest cover within a landscape — a key driver of forest restoration success. We contrasted 17 generalized linear models measuring forest cover at different landscape sizes (with buffers varying from 5 to 200 km radii). We identified the most plausible model to predict and map landscape variation in forest restoration success. We then weighted landscape variation by the amount of potentially restorable areas (agriculture and pasture land areas) within the same landscape. Finally, we estimated restoration costs of implementing Bonn Challenge commitments in three specific temperate and tropical forest biome types in the United States, Brazil and Uganda.Landscape variation decreased exponentially as the amount of forest cover increased in the landscape, with stronger effects within a 5 km radius. Thirty‐eight per cent of forest biomes have landscapes with more than 27% of forest cover and showed levels of landscape variation below 10%. Landscapes with less than 6% of forest cover showed levels of variation in forest restoration success above 50%.At the biome level, Tropical and Subtropical Moist Broadleaf Forests had the lowest (12.6%), whereas Tropical and Subtropical Dry Broadleaf Forests had the highest (22.9%) average of weighted landscape variation in forest restoration success. Our approach can lead to a reduction in implementation costs for each Bonn Challenge commitment between US$ 973 Mi and 9.9 Bi.Policy implications. Our approach identifies landscape characteristics that increase the likelihood of biodiversity recovery during forest restoration — and potentially the chances of natural regeneration and long‐term ecological sustainability and functionality. Identifying areas with low levels of landscape variation can help to reduce the risks and financial costs associated with implementing ambitious restoration commitments. [ABSTRACT FROM AUTHOR]

Site-specific management strategies are usually dependant on the understanding of the underlying cause and effect relationships that occur at the within-field level. The assessment of canopy geometry of tree crops has been facilitated in recent years through the development of light detection and ranging sensors mounted on terrestrial platforms. The main objective of this study was to uncover the factors driving orange tree variability in commercial orange groves. Secondly, this study sought to investigate whether tree geometry information derived from a terrestrial sensing platform is useful information to guide management zones delineation in such groves. A database of soil physical attributes, elevation, historical yield and canopy geometry (canopy volume and height) was analysed in three commercial orange groves in São Paulo, Brazil. Canopy geometry and historical yield were correlated with soil attributes in two of the three groves evaluated; in these groves, the correlation coefficient between yield and soil/landscape information was often above 0.6, depending on the year. Zones of different tree sizes presented different historical yield and soil properties in all three groves. In conclusion, assessing canopy volume provides useful information to delineate management zones and guide enhanced site-specific management strategies. [ABSTRACT FROM AUTHOR]

Characterizing crop spatial variability is crucial for estimating the opportunities for site-specific management practices. In the context of tree crops, ranging sensor technology has been developed to assess tree canopy geometry and control real-time variable rate application of plant protection products and fertilizers. The objective of this study was to characterize the variability of canopy geometry attributes in commercial orange groves in Brazil and therefore estimate the potential impact of sensor-based site-specific management. Using a mobile terrestrial laser scanner, canopy volume and canopy height were measured in 0.25 m length transversal sections along the rows across five large scale commercial orange groves in São Paulo, Brazil. The coefficient of variation of canopy volume ranged from 30 to 40%. Canopy height was less variable, but closely related to canopy volume. Histograms of canopy volume and height were usually negatively skewed indicating regions of the groves with smaller plants and punctual plant resets. In scenarios where input application rates followed canopy volume variability, input savings were around 40% compared to constant rates based on the maximum canopy volume. Maps of canopy geometry derived from mobile terrestrial laser scanning revealed significant canopy spatial variability, suggesting that the groves would benefit from strategies based on management zones and other forms of site-specific management. [ABSTRACT FROM AUTHOR]

This study provided a basis for new possibilities concerning the use of the sugarcane bagasse ash as a green pozzolanic addition to the Portland cement composite. To that effect, a simple micronization method using air jet milling without any other additional thermal procedure was used to control the characteristics of ash particles. This procedure not only maintains the required characteristics of the residues but can also improve some of them. Sugarcane bagasse ash is a residue produced on large scale in Brazil by ethanol and sugar plants as a result of the burning of sugarcane bagasse in energy cogeneration. The residue used in this study was initially characterized by scanning electron microscopy, granulometric and specific mass analyses, N2 adsorption measurements, X-ray diffraction, X-ray fluorescence spectroscopy, and thermogravimetric analysis with differential thermal analysis. Pozzolanic ash activity was evaluated according to the axial compressive strength at 28 days and the modified Chapelle methods. The results showed that the milling fly sugarcane bagasse ash samples presented satisfactory pozzolanic activity. [ABSTRACT FROM AUTHOR]

In 1974 China and Brazil began the building of a dialogue that consolidated, ever since, an important partnership for both countries, especially in areas of trade, infrastructure, finance, technology, energy and food. Such connection became closer after Brazil's inclusion as a member of BRICS, an entity formed by Brazil, Russia, India, China and South Africa. However, could it be said that relations were intensified from this inclusion? Giving the question, the purpose of this paper is to identify how the creation of the BRICS influenced in the relationship between China and Brazil, using a theoretical and exploratory research. Given the findings, it is understood that these diplomatic exchanges between the two states have been intensified due to interaction in the BRICS bloc, however, some warning signs are perceived about a Brazil's dependency on Chinese political and economic directions. [ABSTRACT FROM AUTHOR]

Objective: To identify ingredients from products and by-products derived from GM crops in packaged food products and to analyse the presence of these ingredients in the foods most commonly consumed by the Brazilian population.Design: Cross-sectional study.Setting: A search of the scientific literature to identify the use of products and by-products derived from GM crops in foods in Brazil and a study of food labels in a supermarket belonging to one of the ten largest supermarket chains in Brazil.Subjects: To identify the ingredients present in packaged food products and their nomenclatures, the labels of all packaged food products available for sale in a supermarket were analysed. Subsequently, the presence of potential GM ingredients in the foods most commonly consumed by the Brazilian population was analysed.Results: A total of twenty-eight GM crops' by-products with applications in the food industry (from soyabeans, corn, cotton and a yeast) were identified. Such by-products are presented as food ingredients or additives on food labels with 101 distinct nomenclatures. Most of the variety (63·8 %) and the quantity (64·5 %) of the foods most commonly consumed by Brazilians may contain a least one GM ingredient.Conclusions: The presence of at least one potential GM ingredient was observed in more than half of the variety of foods most commonly consumed by the Brazilian population. Such ingredients were identified with distinct nomenclatures and incomplete descriptions, which may make it difficult to identify potential GM foods and confuse consumers when making food choices. [ABSTRACT FROM AUTHOR]

Variable rate technology allows application of inputs according to the field spatial variability. Citrus fields can be significantly variable in either soil or plant aspects. Thus, variable rate fertilization seems to be an adequate approach to deal with this issue. However, its effects on input consumption, yield and other crop factors have not yet been assessed during long term experiments. The objective of this study was to evaluate the effects of variable rate fertilization on the input consumption, soil fertility and yield during a long term experiment in citrus. A strip experiment was established in two 25 ha citrus fields in São Paulo, Brazil, to compare variable rate against uniform rate fertilization. This experiment was carried out during 6 years. Variable rate prescriptions were based on soil and leaf grid sampling and on yield maps. Uniform applications were based on conventional soil sampling and average yield data. Variable rate treatment resulted in significant reduction in input consumption, but different soil fertility and yield responses were obtained by the variable rate in each field. Field 1 presented higher variability regarding soil and topography. Variable rate application resulted in a better soil fertility management and yield increase in this field. Field 2, which was less variable regarding soil and topography, got poorer results from variable rate treatment regarding soil fertility and yield response. Either way, variable rate technology resulted in higher fertilizer agronomic efficiency in both fields. N, P, and K fertilizers resulted in more fruit yield when applied site-specifically. [ABSTRACT FROM AUTHOR]

Copyright of Brazilian Journal of Oceanography is the property of Instituto Oceanografico da Universidade de Sao Paulo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Methyl-xanthines and adrenergic stimulants, such as caffeine and synephrine, are commonly added to food supplements due to their stimulating and thermogenic effects. In addition, the abusive consumption of food supplements with ergogenic and aesthetic purposes has been observed worldwide. This work describes the study of caffeine,p-synephrine, hordenine, octopamine, tyramine, ephedrine and salicin as stimulants in dietary supplements marketed in Brazil for weight loss and physical fitness claims. A total of 94 different products were acquired from 30 Brazilian websites. Thus, the sampling of marketed supplements was performed in virtual commerce (e-commerce) with claims of weight loss, appetite reduction, fat burning and metabolism acceleration. The developed analytical method involved the separation of the stimulants by HPLC with diode array detection (HPLC-DAD) by using a gradient elution of flow rate (0.7–2.5 ml min−1) and mobile phase composition (0.1% H3PO4/methanol). The validated method was applied to the study of 46 dietary supplements. Caffeine,p-synephrine and ephedrine were found to be present as stimulants in 52% of the studied samples marketed as encapsulated or bulk forms. Caffeine was found to be present in concentrations that represent doses from 25.0 to 1476.7 mg day–1. Synephrine was found in concentrations that represent doses from 59.1 to 127.0 mg day–1. Ephedrine was found to be associated with caffeine in one formulation at a concentration representing a 26.1 mg day–1dosage. [ABSTRACT FROM AUTHOR]

Nitrogen fertilization is challenging for sugarcane (Saccharum spp.) producers due to its complex interaction with the crop and soil. Thus, the main goal of this study was to develop a feasible approach to guide variable‐rate N application in sugarcane based on canopy sensor readings. This study was conducted for 5 yr. Several plot and strip N‐rate experiments were conducted under a wide range of crop conditions in Brazil and evaluated with the Crop Circle active canopy sensor (Holland Scientific Inc.). Because of variability in crop density and growth development within sugarcane fields, the use of an N‐rich reference area to estimate the crop response to N application was compromised. Biomass was the main crop parameter influencing canopy sensor readings, allowing yield estimation because biomass typically results in stalk yield. Thus, canopy sensor readings can efficiently predict relative sugarcane yield when working with data that are normalized to the mean for the field. Hence, an algorithm that takes into account this relationship was established. The concept of this algorithm is to apply higher N fertilization rates where the sugarcane yield potential is higher. Such an approach was determined to be useful to guide N application in sugarcane fields. Nevertheless, field validation is needed to confirm this N management strategy. Besides, more information about sugarcane biomass variability within fields may be required to increase algorithm efficiency. [ABSTRACT FROM AUTHOR]

The use of wind energy plays a vital role in society owing to its economic and environmental importance. Knowing the wind power generation within a specific time window is useful for facilitating decision making in terms of maintenance, electricity market clearing, and reload sharing. However, the effect of climatic and demographic factors on wind power generation sometimes makes time series forecasting a complex task. Thus, this study evaluates an ensemble learning model that combines bagging and stacking methods applied to time series forecasting with very short-term (10 and 30-minutes) and short-term (60 and 120-minutes) evaluations of wind power generation. Arithmetic and weighted average values were used to integrate the samples from bagging strategy. The weights are defined through multi-objective optimization using a non-dominated sorting genetic algorithm – version II, aiming to enhance the forecasting accuracy and stability simultaneously. To demonstrate the wide applicability of the non-linear ensemble learning model, it is extensively tested with measurement data collected from two wind farms in Bahia State, Brazil. The experimental results show that the proposed ensemble learning model achieves a better forecasting performance than single forecasting models, such as stacking, machine learning, artificial neural networks, and statistical models, with values of approximately 7.63%, 7.58%, 20.8%, and 25%, respectively, in terms of the errors for out-of-sample forecasting reduction. In addition, results with a weighted average are 87.5% superior to those with an arithmetic average for out-of-sample wind power forecasting in the evaluated forecasting horizons. The findings show that the integration of ensemble strategies can provide accurate forecasting results in the renewable energy field. • An improved stacking ensemble is proposed for wind power generation forecasting. • Bagging and stacking methods are combined in a competitive ensemble. • Multi-objective optimization is adopted to enhance the accuracy and stability. • Very-short and short-term forecasting are obtained. • The proposed model improves the forecasting accuracy through errors reduction. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Ciências Farmacêuticas Básica e Aplicada is the property of Revista de Ciencias Farmaceuticas Basica e Aplicada and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: Foot-and-mouth disease (FMD) control in Brazil includes a strict mandatory vaccination program with vaccines produced in certified laboratories subject to inspection by the Brazilian Ministry of Agriculture, Livestock, and Food Supply (MAPA). The FMD vaccine''s potency is tested through antibodies titration against structural viral proteins in sera from cattle that have not had any exposure to food-and-mouth disease virus (FMDV), at 28 days post-vaccination. Biological product testing using large animals is expensive and unwieldy. Thus, alternative testing procedures using laboratory animals have been proposed for quality control of these products. Such biological methods for vaccine evaluation using animals from vivarium facilities can have a significant impact through reduced costs, easier handling, and shorter testing times. The present study was designed to access Balb/C mice''s humoral immune responses to a FMDV experimental vaccine, the composition of which contains three virus serotypes of FMDV (O1 Campos, A24 Cruzeiro, and C3 Indaial). Balb/C mice were immunized at doses that were 5% and 10% of the vaccine volume administered in cattle. Immunized mice had their antibody titers probed at 14, 21, and 28 DPV (days post vaccination). The results obtained were compared to those previously known from cattle''s immune responses to the FMDV vaccine. An adequate immune response to the vaccine was seen with 10% formulation at 21 DPV. The study results are encouraging and indicate that the mouse model can be used for quality control in experimental vaccine testing. [Copyright &y& Elsevier]

Copyright of Brazilian Journal of Food & Nutrition / Alimentos e Nutrição is the property of Faculdade de Ciencias Farmaceuticas, UNESP and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: This paper presents a project under deployment inside the company Centrais Elétricas de Santa Catarina – CELESC, for the development of a model intended to process information related to geothermal energy generation, in the state of Santa Catarina, Brazil. In this model, are being used techniques for knowledge management and engineering over 3D geo-referenced data. The state of Santa Catarina has known to have a great geothermal potential, with initially five geographic areas specifically identified to apply processes for heat extraction. The development of a model directed to the geothermal energy field will bring immediate benefits to the state, like a clean and sustainable energetic matrix. [Copyright &y& Elsevier]

Copyright of Revista Brasileira de Engenharia Agricola e Ambiental - Agriambi is the property of Revista Brasileira de Engenharia Agricola e Ambiental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Brasileira de Engenharia Agricola e Ambiental - Agriambi is the property of Revista Brasileira de Engenharia Agricola e Ambiental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Precision agriculture (PA) technologies are being applied to crops in Brazil, which are important to ensure Brazil's position in agricultural production. However, there are no studies available at present to indicate the extent to which PA technologies are being used in the country. Therefore, the main objective of this research was to investigate how the sugar-ethanol industry in São Paulo state, which produces 60% of the domestic sugarcane, is adopting and using these techniques. For this purpose, primary data were used, which were obtained from a questionnaire sent to all companies operating in the sugar-ethanol industry in the region. The aim was to determine to what extent these companies are adopting and using PA technologies, and also to promote a more in-depth discussion of the topic within the sugar-ethanol industry. Information was obtained on the features of the companies, on sources of information that they use for adopting these technologies, on their impacts on these companies and on obstacles hindering their adoption. The main conclusions of this research suggest that companies that adopt and use PA practices reap benefits, such as managerial improvements, higher yields, lower costs, minimization of environmental impacts and improvements in sugarcane quality. [ABSTRACT FROM AUTHOR]

In Brazil, there are some commercial products composed of metalaxyl-M that can be used as seed treatment of soybean. Metalaxyl-M is a fungicide with efficacy against oomycetes, however, the concentrations and recommended doses of commercial products are not very effective. The objective of this study was to investigate the effect of increasing the dose of commercial products composed of metalaxyl-M for controlling root rot of soybean caused by two species of Globisporangium (G. irregulare and G. sporangiiferum var. ultimum) The treatments were arranged in a factorial scheme of 3 fungicides (Apron, Maxim Advanced and Maxim Quattro) x 7 doses (0.000, 0.003, 0.006, 0.012, 0.018, 0.024, 0.030 mg of metalaxyl-M per seed) x 2 soybean cultivars ('DM57i52' and 'NEO530'). Separate experiments were conducted for each species of Globisporangium. There was a significant effect of the doses on the reduction of root rot severity for both soybean cultivars. The response of root rot severity according to the doses followed either logistic or Weibull regression models. The effective concentrations of metalaxyl-M that reduced 50%, 70% and 90% of root rot severity for 'NEO530' were higher than 'DM57i52' independently of the product applied. Thus, it can be concluded that the increase in fungicide dose compared to what is already used in Brazil, can promote greater levels of control of root rot caused by G. ultimum var. sporangiiferum and G. irregulare in soybean. • Increasing the dose of metalaxyl-M provides greater control of root rot in soybean. • The more susceptible the cultivar, the higher the fungicide dose is required. • No phytotoxicity occurred by increasing the dose of fungicide-based products. [ABSTRACT FROM AUTHOR]

Copyright of Contrapontos is the property of Universidade do Vale do Itajai and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article presents a study on roller-compacted concrete (RCC) placement. RCC is used in the construction of dams and involves the use of concrete mixture with a dry consistency. Due to its dryness, studies on RCC raised concerns over the material's actual strength. Various data on the material need to be researched including its behavior especially during the placement of concrete layers. The article discusses a study which includes an experiment simulating the conditions of RCC placement. A comparison is also made between the result of the study and field tests in Brazil.

Globisporangium irregulare and G. ultimum var. sporangiiferum were recently reported to be associated with soybean damping-off in Brazil. Currently, there is no known information about fungicide seed treatments for soybean. Thus, the objective of this study was to evaluate the efficacy of commercial fungicide-based products to control soybean damping-off caused by G. irregulare and G. ultimum var. sporangiiferum. The experiments were performed with 15 seed treatments (non-treated check, Certeza N, Apron RFC, Maxim, Maxim XL, Maxim Quattro, Maxim Advanced, Vitavax Thiram, Standak Top, Spectro, Verango, Derosal Plus, Carbendazim, Attic and Rancona T) and two soybean cultivars ('DM57i52' and 'NEO530'). In vitro assays were performed to verify the effect of seed treatments on seed germination and seed rot, whereas growth chamber assays were conducted to evaluate the effect of seed treatments on emergence, root rot and seedling dry mass. Products that contain metalaxyl-M were the most effective at controlling damping-off caused by G. irregulare and G. utimum var. sporangiiferum followed by products that contain thiram. Overall, Apron RFC, Maxim Advanced and Maxim Quattro had higher efficacy to reduce damping-off caused by either G. irregulare or G. ultimum var. sporangiiferum therefore, can be recommended for seed treatment of soybean. • Fungicide seed treatments control damping-off caused by Globisporangium in soybean. • Apron RFC, Maxim Advanced and Maxim Quattro provided greater control of damping-off. • Products with higher concentration of metalaxyl-M provide higher damping-ff control. [ABSTRACT FROM AUTHOR]

The decision on crop population density should be a function of biotic and abiotic field parameters and optimize the site-specific yield potential, which can be a real challenge for farmers. The objective of this study was to investigate the yield of maize hybrids subjected to variable rate seeding (VRS) and in differentiated management zones (MZs). The experiment was conducted between 2013 and 2015 in a commercial field in the Central-West region of Brazil. First, MZ were delineated using the K-means algorithm with layers involving soil electrical conductivity, yield maps from previous years, and elevation. Seven maize hybrids at five seeding rates were evaluated in the context of each MZ and the cause-and-effect relationship with soil attributes was investigated. Optimal yields were obtained for crop population densities between 70,000 plants ha−1 and 80,000 plants ha−1. Hybrids which perform well under higher densities are key in achieving positive results using VRS. The plant population densities that resulted in maximum yields were obtained for densities at least 27% higher than the recommended seeding rates. The yield variance between MZs can be explained by the variance in soil attributes, while the yield variance within MZs can be explained by the variance in plant population densities. The study shows that on-farm experimentation can be key for obtaining information concerning yield potential. The management by VRS in different MZs is a low-cost technique that can reduce input application costs and optimize yield according to the site-specific potential of the field. [ABSTRACT FROM AUTHOR]

• 90 videos were recorded during harvest at the harvester conveyor belt. • Different input resolutions were assessed for the YOLOv3-tiny detection system. • The georeferenced video frames were used for object detection. • Coffee maturation stage was mapped during harvest. In this study, an algorithm is implemented with a computer vision model to detect and classify coffee fruits and map the fruits maturation stage during harvest. The main contribution of this study is with respect to the assignment of geographic coordinates to each frame, which enables the mapping of detection summaries across coffee rows. The model used to detect and classify coffee fruits was implemented using the Darknet, an open source framework for neural networks written in C. The coffee fruits detection and classification were performed using the object detection system named YOLOv3-tiny. For this study, 90 videos were recorded at the end of the discharge conveyor of a coffee harvester during the 2020 harvest of arabica coffee (Catuaí 144) at a commercial area in the region of Patos de Minas, in the state of Minas Gerais, Brazil. The model performance peaked around the ~3300th iteration when considering an image input resolution of 800 × 800 pixels. The model presented an mAP of 84%, F1-Score of 82%, precision of 83%, and recall of 82% for the validation set. The average precision for the classes of unripe, ripe, and overripe coffee fruits was 86%, 85%, and 80%, respectively. As the algorithm enabled the detection and classification in videos collected during the harvest, it was possible to map the qualitative attributes regarding the coffee maturation stage along the crop lines. These attribute maps provide managers important spatial information for the application of precision agriculture techniques in crop management. Additionally, this study should incentive future research to customize the deep learning model for certain tasks in agriculture and precision agriculture. [ABSTRACT FROM AUTHOR]

Wind energy is one of the sources which is still in development in Brazil. However, it already represents 17% of the National Interconnected System. Due to the high level of uncertainty and fluctuations in wind speed, predicting wind energy with high accuracy is challenging. In this context, this paper proposes a novel decomposition-ensemble learning approach that combines Complete Ensemble Empirical Mode Decomposition (CEEMD) and Stacking-ensemble learning (STACK) based on Machine Learning algorithms to forecast the wind energy of a turbine in a wind farm at Parazinho city, Brazil, using multi-step-ahead forecasting strategy. The approached forecasting models were k -Nearest Neighbors, Partial Least Squares Regression, Ridge Regression, Support Vector Regression, and Cubist Regression. Additionally, Box-Cox transformation, correlation matrix, and principal component analysis were used to pre-process the data. The performance of the proposed forecasting models was evaluated by using three performance metrics: mean absolute error, mean absolute percentage error, and root mean square error, and the Diebold-Mariano statistical test to evaluate the forecasting error signals. The proposed models outperform the CEEMD, STACK, and single models in all forecasting horizons, with a performance improvement that ranges 0.06%–97.53%. Indeed, the decomposition-ensemble learning model is an efficient and accurate model for wind energy forecasting. Image 1 • A novel decomposition-ensemble learning model is proposed for wind energy forecasting. • CEEMD method deal with the non-linearity and non-stationarity of the time series. • Different preprocessing approaches are employed to deal with the high-correlation of the system's inputs. • STACK approach by divide-and-conquer scheme takes advantages of the models. • Proposed model improves the accuracy of wind energy forecasting multi-step ahead. [ABSTRACT FROM AUTHOR]

The species Amblyomma longirostre Koch, 1844 is poorly known in the state of Rio Grande do Sul. Usually the adult stage could be found on Sphigurus spp. and the immatures on birds (Passeriformes). Although A. longirostre is distributed in the Neotropical region, from Panama to Uruguay, it also occurs in Central America and the United States. The aim of this study was to report that Ramphastos dicolorus Linnaeus 1766 is a new host record for this tick species. [ABSTRACT FROM AUTHOR]

The successful use of energy-dispersive X-ray fluorescence (ED-XRF) sensors for soil analysis requires the selection of an optimal procedure of data acquisition and a simple modelling approach. This work aimed at assessing the performance of a portable XRF (XRF) sensor set up with two different X-ray tube configurations (combinations of voltage and current) to predict nine key soil fertility attributes: (clay, organic matter (OM), cation exchange capacity (CEC), pH, base saturation (V), and extractable nutrients (P, K, Ca, and Mg). An XRF, operated at a voltage of 15 kV (and current of 23 μA) and 35 kV (and current of 7 μA), was used for analyzing 102 soil samples collected from two agricultural fields in Brazil. Two different XRF data analysis scenarios were used to build the predictive models: (i) 10 emission lines of 15 keV spectra (EL-15), and (ii) 12 emission lines of 35 keV spectra (EL-35). Multiple linear regressions (MLR) were used for model calibration, and the models' prediction performance was evaluated using different figures of merit. The results show that although X-ray tube configuration affected the intensity of the emission lines of the different elements detected, it did not influence the prediction accuracy of the studied key fertility attributes, suggesting that both X-ray tube configurations tested can be used for future analyses. Satisfactory predictions with residual prediction deviation (RPD) ≥ 1.54 and coefficient of determination (R2) ≥ 0.61 were obtained for eight out of the ten studied soil fertility attributes (clay, OM, CEC, V, and extractable K, Ca, and Mg). In addition, simple MLR models with a limited number of emission lines was effective for practical soil analysis of the key soil fertility attributes (except pH and extractable P) using XRF. The simple and transparent methodology suggested also enables future researches that seek to optimize the XRF scanning time in order to speed up the XRF analysis in soil samples. [ABSTRACT FROM AUTHOR]

The investigation of the accuracy of methods employed to forecast agricultural commodities prices is an important area of study. In this context, the development of effective models is necessary. Regression ensembles can be used for this purpose. An ensemble is a set of combined models which act together to forecast a response variable with lower error. Faced with this, the general contribution of this work is to explore the predictive capability of regression ensembles by comparing ensembles among themselves, as well as with approaches that consider a single model (reference models) in the agribusiness area to forecast prices one month ahead. In this aspect, monthly time series referring to the price paid to producers in the state of Parana, Brazil for a 60 kg bag of soybean (case study 1) and wheat (case study 2) are used. The ensembles bagging (random forests — RF), boosting (gradient boosting machine — GBM and extreme gradient boosting machine — XGB), and stacking (STACK) are adopted. The support vector machine for regression (SVR), multilayer perceptron neural network (MLP) and K -nearest neighbors (KNN) are adopted as reference models. Performance measures such as mean absolute percentage error (MAPE), root mean squared error (RMSE), mean absolute error (MAE), and mean squared error (MSE) are used for models comparison. Friedman and Wilcoxon signed rank tests are applied to evaluate the models' absolute percentage errors (APE). From the comparison of test set results, MAPE lower than 1% is observed for the best ensemble approaches. In this context, the XGB/STACK (Least Absolute Shrinkage and Selection Operator-KNN-XGB-SVR) and RF models showed better performance for short-term forecasting tasks for case studies 1 and 2, respectively. Better APE (statistically smaller) is observed for XGB/STACK and RF in relation to reference models. Besides that, approaches based on boosting are consistent, providing good results in both case studies. Alongside, a rank according to the performances is: XGB, GBM, RF, STACK, MLP, SVR and KNN. It can be concluded that the ensemble approach presents statistically significant gains, reducing prediction errors for the price series studied. The use of ensembles is recommended to forecast agricultural commodities prices one month ahead, since a more assertive performance is observed, which allows to increase the accuracy of the constructed model and reduce decision-making risk. • Ensembles and single models are compared for short-term forecasting in agribusiness. • Soybean and wheat commodities are adopted as case studies. • Boosting approaches showed lower predictions errors. • XGB or STACK and RF models are adopted in soybean and wheat cases, respectively. • Ensemble performance is better than SVR, KNN and MLP performance. [ABSTRACT FROM AUTHOR]

Crop rotation with leguminous species in sugarcane cultivation is increasing in the southeastern regions of Brazil. Most of researches done on sugarcane is focused on yield regardless its final product. In the specific case of sugarcane ethanol production, studies rely basically on the economic and sustainable points of view overlooking the energy analysis. This study aimed to evaluate the sugarcane ethanol yield under no-tillage and conventional systems with different green manure treatments on energy efficiency. Sugarcane published dataset was used in the study where different management practices and yield were available. Energy indices from different sources were used to transform all the input into the same unit (MJ). Analysis of energy efficiency was carried out using the indicators: energy balance (EB), energy return over investment (EROI) and Energy Intensity (EI). Analysis of variance and Tukey test at 5% of significance was applied. EB ranged from 148 GJ ha-1 to 216 GJ ha-1, with no-tillage over jack beans system presenting the highest values of EB. EI presented that no-tillage systems over spontaneous vegetation presented the highest and statistically different value (1.03 MJ L-1) compared to the other systems (0.69 MJ L-1 for both no-tillage over velvet beans and jack beans and 0.66 MJ L-1 for sunn hemp). In addition to that, sugarcane yield was statically equal for conventional system and no-tillage over sunn hemp and velvet beans. Energy analysis provided an opportunity to target potential management practices to reduce the consumption of energy to produce the same amount of sugarcane, unable to figure out looking at only the yield (Mg ha-1). Applying energy analysis on the available data, it was shown that sugarcane cultivation with no-tillage and no chemical fertilization with green manure crop rotation is energetically feasible increasing sustainability of sugarcane ethanol production, but it is necessary to highlight the importance to verify the absolute values of EB, EROI and EI indicators along years. [ABSTRACT FROM AUTHOR]

Concentrations of As, Cd, Cu, Cr, Pb, Hg, and Ni were analyzed during rainy and dry seasons in water, sediment, soil, and two fish species. The analysis took place at four points in the Xingu River, one point in the Fresco River, and two mining pits in the southeastern area of the Eastern Amazon, Brazil. In the water, the total concentration of As (> 0.14 μg/L) was higher than the local reference values at all sampling points and in both seasons. Ordination analysis (PCA) highlighted As and Cu elements in the water. PERMANOVA showed that the metals behaved differently in the water throughout the monitored season and between sampling points. The sites with mining activity were the regions that were the most contaminated by metals. Samples of sediment (Ni > 18 mg/kg and Cr > 37.30 mg/kg) and soil (Pb > 72 mg/kg, Cr > 75 mg/kg and Ni > 30 mg/Kg) showed concentrations above the recommended by local legislation. Metal values in the muscle of both fish species were relatively low at all sampling points and in both monitored seasons. Concentrations in water, sediment, and soil showed that some points of the Xingu River, Fresco River and mining pits are contaminated by trace elements, mainly As, Hg, Cr, Pb, and Ni. This was the first study about trace elements in the Middle Xingu River, which leads us to conclude that rainfall and cassiterite mining activities strongly influence the mobilization of metals, especially in abiotic compartments. However, the fish analyzed did not exhibit relevant levels of contamination. This indicates low risk for human consumption. Additionally, results highlight the need to establish local criteria to define contamination limits for different metals while taking into account local geochemistry particularities and biome diversity. [ABSTRACT FROM AUTHOR]

Wind energy is an emerging source of renewable energy in Brazil. Nevertheless, it already accounts for 17% of the National Interconnected Network. Due to the great intricacy of wind speed variations, it is difficult to predict wind energy with high accuracy. This research offers, in these circumstances, an ensemble learning model based on variational mode decomposition and singular spectrum analysis in decomposition in multiple stages, using stacking-ensemble learning. The proposed model is tested and applied in short-term wind speed data from a wind farm located in Parazinho in the northeast region of Brazil, using a multi-step-ahead forecasting strategy. The selected models for forecasting were the machine learning models partial least squares regression, k -nearest neighbors, cubist regression, support vector regression, and ridge regression. The results of the study were divided into three comparative experiments: comparisons with (i) dual decomposed models, (ii) single decomposed models, and (iii) decomposed models. Concerning performance improvement, in the first experiment, the model was compared to dual decomposition models with an average performance between 3.71% and 21.38%. In the second experiment, mean performance improved between 37.18 and 52.47 percent compared to single decomposition. Lastly, the proposed model delivered, on average, 54.98% better results than the models without decomposition. In summary, all compared models in all forecasting horizons were surpassed by the proposed model, with an average improvement between 3.69 and 56.61 percent, showing that the dual decomposition ensemble learning model is an effective and accurate approach for forecasting wind speed. [Display omitted] • A novel multi-stage decomposition ensemble learning model for wind speed forecasting. • VMD and SSA composes the decomposition combined with the STACK to forecast wind speed. • The results show the proposed model' superiority over compared approaches. [ABSTRACT FROM AUTHOR]

Soybean is the main product of Brazilian agribusiness, both production and income. Considering the increase in food and energy demand and the search for more sustainable production systems, this study aimed to analyze inputs and energy use of a possible area of expansion of soybean production: a system under sub irrigation management located in a lowland area of Cerrado biome, northern region of Brazil. Its environmental performance was compared to other Brazilian locations among them traditionally soybean producers. The evaluation and comparison was made through material and energy flow tools in order to determine the inputs embodied per area, as well as energy demand, availability and efficiency in the analyzed production system. Energy demand (IE) and energy availability (OE) of the analyzed production system were 7.6 and 57.1 GJ ha-1, respectively. Energy balance (EB) was 49,5 GJ ha-1, energy return over investment (EROI) was 7.5 and embodied energy in grains (EE) was 2,2 MJ kg-1, respectively. Highest energy consumption was due to the use of fertilizers, fuel and herbicide. The system is energy efficient, since it provides more energy than demands, and efficient when compared to usual production systems in other regions, however it is highly dependent on non-renewable energy. [ABSTRACT FROM AUTHOR]

Core objectives of precision agriculture are to improve the economic and environmental performance of agricultural systems. This study used a long-term experiment in citrus to assess whether site-specific nutrient management was successful from these two perspectives. Variable and uniform rate fertilisation treatments were implemented in intercalated strips across two 25 ha citrus groves in São Paulo state, Brazil. To generate variable rate recommendations, information from soil fertility and yield maps were fed into a traditional recommendation formula used by growers. The experiment was carried out for five growing seasons. An economic, energy and nutrient balance analysis was conducted. Variable rate application increased average yield in grove 1 but sometimes reduced yield in grove 2. As a consequence, profit was increased by 34.7% (US$ ∗ 318.5 ha−1 year−1) in grove 1. In grove 2, profit was reduced by 8.5% (US$ −97.4 ha−1 year−1). Embodied fertiliser energy was reduced by 34% in grove 1 and by 29% in grove 2. Nutrient surplus after harvest was reduced by approximately 20–70% depending on the nutrient. Maps of economic and environmental indicators showed that site-specific management did not reduce the spatial variability of the system's performance. The variable rate strategy tested could be improved by using local decision rules rather than generalised recommendation formulas. Site-specific analysis of profit, embodied energy and nutrient balance help to assess system performance and can potentially improve decisions in site-specific nutrient management. • A five-year study was used to evaluate variable rate fertilisation in orange groves. • Economic and environmental performance were spatially variable within orange groves. • Environmental indicators were usually superior with variable rate application. • Mixed economic results were found for variable rate application. • Variable rate application must not rely on global recommendation rules. [ABSTRACT FROM AUTHOR]