Climate change has increased rainfall irregularity, making water management critical for soybean productivity. Microalgae-based biostimulants have been proposed to mitigate the effects of water restriction on plant physiology. This study evaluated the effect of foliar application of Scenedesmus obliquus on transpiration and water use efficiency in soybean plants under contrasting water regimes. The experiment was conducted under controlled conditions using the cultivar Embrapa 59 grown in sandy soil (65% sand). A completely randomized design was adopted with four replicates, combining three biostimulant doses (0, 0.3, and 1.2 g L?¹) and two water management regimes (with and without deficit). A 30-day water deficit was imposed from the R1 stage. Transpiration rate (E) and water use efficiency (A/E) were measured using an infrared gas analyzer. Microalgae application significantly increased water use efficiency, particularly under water deficit (up to 250%), and helped maintain transpiration compared to the control. The highest dose produced the most favorable responses, indicating the potential of this biostimulant under water-limited conditions, although further studies are needed to standardize application protocols.
Coffee is one of the most important global commodities, with Brazil leading its production. To ensure its quality and commercial viability, off-season storage is essential. However, inadequate moisture content leads to grain deterioration. The aim of this study was to analyze the hygroscopic behavior of hulled coffee, evaluating mathematical models for predicting moisture adsorption isotherms. The research was conducted using Yellow Bourbon coffee, applying the static method with saturated saline solutions to control relative humidity at temperatures ranging from 10 to 50 °C. Twelve mathematical models were evaluated regarding their fit to the experimental data. The results showed that the adsorption isotherms of hulled coffee follow a sigmoidal pattern, indicating that equilibrium moisture decreases with increasing temperature. The Harkins model presented the best fit, with a coefficient of determination (R²) of 0.998 and a standard error of estimate (SE) of 0.448, outperforming other widely used models. Visual validation of the model confirmed its high accuracy, with predicted values closely aligned with the experimental data. It is concluded that the Harkins model is the most suitable tool for optimizing the storage of hulled coffee, providing a technical basis for sustainable moisture management and the preservation of grain quality.
Coffee production in Brazil requires efficient monitoring tools, especially in regions with heterogeneous terrain and planting patterns. Accurate delineation of coffee canopies from UAV imagery is essential for extracting reliable agronomic information and supporting precision agriculture practices. Multispectral UAV images were acquired over a commercial coffee farm in the Matas de Minas region, Brazil. An orthomosaic was generated and manually annotated to create binary ground-truth masks of coffee canopies. A U-Net convolutional neural network was trained using multispectral bands and the Normalized Difference Vegetation Index (NDVI) as input. Model performance was evaluated using Dice coefficient, Intersection over Union (IoU), precision, recall, and accuracy. The proposed model achieved a Dice coefficient of 0.89, IoU of 0.83, and overall accuracy above 0.92. The predicted coffee canopy area (1.50 ha) was consistent with the reference area obtained from manual annotation (1.45 ha), indicating reliable canopy delineation under heterogeneous field conditions. The results demonstrate that semantic segmentation using multispectral UAV imagery and a U-Net model is an effective and applicable approach for coffee canopy mapping, with potential use in precision agriculture and farm-scale decision-support systems.
The northwestern region of the state of Paraná has undergone deep transformations in its land use, occupation, and management, resulting in environmental degradation and water contamination. The objective of this work was to evaluate soil conservation practices in the Inhacanga River micro-watershed in Altônia, Paraná state, using the AGNPS model and geoprocessing techniques in ArcGIS software. Thus, scenarios were developed to analyze the existing agricultural systems and to compare different terrace spacings, considering the 2019/2020 summer and exposed soil conditions. Sediment production was estimated based on rainfall records from the historical hydrosedimentological monitoring series. In the 2019/2020 summer scenario, with the adoption of terraces, a reduction in potential erosion areas of 13.21% was observed; in sediment production, of 15.38%; in solid runoff, of 35.93%; and in flow, of 31.66%. In the exposed soil condition, potential areas reduced by 5.51%; sediment production, by 9.36%; solid discharge, by 56.63%; and flow, by 15.85%. It should also be noted that the best results were obtained with variations in terrace spacing greater than 49%, 50%, and 53%, compared to the other recommended values.
Wind tunnels are used in application technology for simulating uniform scenarios and quantifying spray drift. This study describes the design, construction, and validation of an open-circuit wind tunnel for aerodynamic simulations at the State University of Goiás. The tunnel consists of a fan, stabilization chamber, nozzle, test section, and diffuser. All components have a square cross-section and were constructed using iron bars and galvanized steel sheets for structural support and outer casing. The test section measures 0.60 m × 0.60 m in cross-section and 1.80 m in length and has acrylic access doors. The contraction nozzle was defined using a fifth-degree polynomial. The honeycomb structure was made from joined PVC pipes. Air propulsion is provided by a 1.1 kW three-phase motor conected to an axial fan and a frequency inverter. Validation involved measuring wind speeds inside the test section at three set points ??(1, 3, and 5 m s-1). Flow uniformity was assessed by calculating the Reynolds number, Mach number, and descriptive measurements. Results showed that the fan maintained desired operating conditions, and the tunnel generated a homogeneous, laminar, and incompressible flow, confirming its suitability for a wide range of simulation studies.
This study aimed to evaluate the effects of different grazing intensities on residual straw mass, soil water content, available water between field capacity and the wilting point, and soybean yield. The experiment was conducted in a randomized block design with three replications, on a Typic Hapludox soil under a non-irrigated integrated crop-livestock (ICL) system. The experiment was established in the 2009/2010 season in Xambrê County, in the Northwestern region of Paraná State, Southern Brazil. The treatments consisted of five palisadegrass grazing height treatments: an ungrazed control and grazing heights of 10, 20, 30, and 40 cm, maintained through variable stocking rates. Palisadegrass dry mass was evaluated three times, and soil water content was measured 19 times during soybean cultivation in the 2013/2014 crop season, and soybean grain yield. In this ICL system, managing palisadegrass at a grazing height of 30 cm resulted in greater water availability in the 0-10 cm soil layer during the soybean growing season. However, soybean grain yield was not influenced by grazing heights management, due to severe dry spells between December and February. During this period, soil water content fell below 50% of the available water, coinciding with the critical grain-filling stage of soybean development. Monitoring water availability in sandy soils under ICL systems highlighted the need for supplemental irrigation to improve soybean grain yield under drought conditions.
The consumption of fruits, both fresh and processed, is closely linked to their quality and the attributes valued by the consumer market. Chemical characteristics of the ‘Pêra-Rio’ orange such as vitamin C content, acidity, and soluble solids—are increasingly important in fruit analysis. These factors play a key role in guiding genetic improvement and determining the optimal harvest period for cultivars that produce fruits with traits specifically sought by end consumers. This study aims to present a detailed perspective on the chemical characterization of fruits, with a particular focus on the correlation analysis of the ‘Pêra-Rio’ orange. The fruits were obtained from a local market in Jataí, Goiás, and transported to the Fruit Growing Laboratory at the Federal University of Jataí. Upon arrival, the samples were selected and sanitized for subsequent analysis of soluble solids content, titratable acidity, and vitamin C concentration. The ‘Pêra-Rio’ orange samples exhibited an average citric acid concentration of 1.22 mg/100 mL of juice. Soluble solids content ranged from 8.6 to 11.5 °Brix. A positive correlation was observed between titratable acidity and vitamin C levels, whereas an inverse correlation was found between titratable acidity and the soluble solids to titratable acidity (SS/TA) ratio. These findings suggest that the fruits analyzed may have exhibited enhanced chemical characteristics had they remained on the plant for a longer maturation period.
The objective of the study was to evaluate the agronomic performance of wheat genotypes and their relationships with the attributes that enhance grain production. A randomized block experimental design was used with nine wheat genotypes and three replications, totaling 27 experimental units. Sowing was carried out in the first half of May 2023, with a sowing density of 350 viable seeds m-2. The following variables were evaluated: number of ears per meter, plant height, ear insertion height, ear length, number of grains per ear, ear grain weight, thousand grain weight, and grain yield. Climatic data, including mean, maximum, and minimum air temperature and precipitation, were obtained from NASA Power. The data were analyzed using analysis of variance (ANOVA), Scott-Knott mean grouping, correlation analysis and K-means clustering. It was possible to estimate a positive linear relationship of ears per linear meter with grain yield. The genotypes TBIO Trunfo, TBIO Audaz and TBIO Motriz achieved the best agronomic performance for the attributes thousand grain weight and grain yield.
Vinasse is a liquid effluent generated as by-product of the fractional distillation of fermented sugarcane juice during ethanol production. When properly managed, vinasse can be used in fertigation, offering significant benefits to agricultural production. This review aims to evaluate the effects of vinasse application on fertigated crops and soil quality. This exploratory study involved a literature review of scientific articles and books using the keywords “fertigation” and “vinasse”. When applied as a fertilizer, vinasse can positively influence the physical, chemical and biological properties of soil. The results indicated that vinasse contains essential nutrients that contribute to plant growth. To support its appropriate application, a general equation for calculating the fertigation rate is also presented. The Vinasse Application Plan should include a descriptive report outlining the fertility characteristics of both the soil and the vinasse, along with the calculated application rate. Literature indicates that the use of irrigation equipment for vinasse fertigation in sugarcane cultivation is a technically and economically viable practice. When applied judiciously, this strategy supports the sustainable management of vinasse while minimizing potential environmental impacts.
Several factors interfere in the efficiency of the seeding process in planting system, with the quality of longitudinal seed distribution being particularly critical. This study aimed to identify the most productive maize hybrid under the prevailing soil conditions and to evaluate the quality of seed longitudinal distribution during cultivation. The experimental design consisted of strip plots with seven treatments and five repetitions. The treatments comprised the following hybrid maize cultivars: EXP T14M774265, Balu 761, EXP T14M6520, EXP T14M713265, Balu 383 VIP 3, EXP T14M7641 and EXP 7132MT14. The variable evaluated included maize productivity, soil pH, soil mechanical resistance to penetration (RP) and the percentage of normal, double and missing crop spacing. Data were subjected to analysis of variance (ANOVA), and means were compared using Tukey’s test when the F-test was significant at the 5% probability level. No significant differences were observed in soil pH (measured in both H2O and KCl), and soil compaction levels remained within acceptable limits, indicating favorable conditions for plants development. However, the seed longitudinal distribution exhibited high variability, attributed to inadequate planter calibration. Among the hybrids tested, EXP T14M6520 (C3) exhibited the highest average productivity, reaching 8.43 t ha-1.
Red rice is considered the predominant weed species in rice fields, causing significant economic losses to producers. The objective of this study was to evaluate the behavior of red rice seeds during the soaking of seeds in water, as well as the development of plants under two fertilization sources (NPK and complete nutrient solution). Seeds were subjected to different soaking durations in water: 0, 10, 20, 30, 40, 50, and 60 minutes. After four days of germination, the seedlings were divided into two treatment groups: (i) plants fertilized with NPK and (ii) plants fertilized with complete nutrient solution. The experiment was conducted in a completely randomized design, evaluating the variables: germination, number of leaves, plant height and dry matter accumulation. A significant increase in germination percentage, number of leaves, plant height and dry matter accumulation in both the aerial part and roots was observed with longer seed soaking durations. This effect was more expressive in red rice plants fertilized with the complete nutritive solution. Thus, we conclude that this fertilizer source enhances the competitive ability of this weed species against cultivated rice.
This study aims to analyze the dynamic relationship between the physicochemical attributes of a Yellow Dystrophic Latosol, which a particular focus on their direct and indirect influences on soil electrical conductivity. Soil samples were collected from 50 georeferenced points within the municipality of Brejo – MA, Brazil, to evaluate these interactions using multivariate stastistical approaches. The path analysis process was conducted using the GENES software, a statistical tool essential for estimate linear correlation values and decomposing the data. The evaluated soil attributes included electrical conductivity, altitude, humidity, soil density, porosity, organic matter, pH, clay, silt, total sand, very coarse sand, coarse sand, medium sand, fine sand, very fine sand, aggregates larger than 2.00 mm³, aggregates larger than 1.00 mm³, aggregates larger than 1.00 mm³, aggregates larger than 0.10 mm³, weighted mean diameter, and mean internal diameter. The approach was adopted due to the high occurrence of multicollinearity, which can lead to interpretative misunderstanding. For this purpose, data decomposition was performed, using electrical conductivity as primary variable - to mitigate the mutual influence among soil attributes. The analysis revealed that pH is the most influential attribute in determining the electrical conductivity of the studied Latosol.
The intrinsic soil air permeability (Kair), defined as the capacity of soil pores to conduct air, is an important soil attribute, as it identifies changes in pore spaces. This study aimed to evaluate the influence of initial gauge pressure, permeameter air cylinder volume, and sample volume on the Kair measurement. Samples of an Oxisol were collected at a depth of 0–0.2 layer and stored in a pot. The experimental design was completely randomized in a 4x3x2 factorial scheme, characterized by four different initial gauge pressures (500, 1000, 1500, and 2000 Pa), three different permeameter cylinder volumes (0.008, 0.0124, and 0.031 m3), and two sample volumes (100 and 270 cm3). The assessment was performed under two soil density conditions in pots (1.334 and 1.421 Mg m?3). Kair showed no changes due to the different sample volumes, but a different behavior was observed for the two soil density conditions. Increasing the permeameter air cylinder volume promoted an increase in the Kair estimate. Kair was lower for the initial pressure evaluated with 2000 Pa.
Agricultural pests are organisms capable of significantly impacting the yield and quality of cultivated crops. Traditionally, population control of insect pests has relied on methods such as trapping and subsequent analysis of captured individuals to implement specific control actions, such as the use of insecticides. However, advancements in Computer Vision and Deep Learning techniques offer promising ways for more efficient pest detection and management. This study aims to apply Convolutional Neural Networks (CNNs) to detect the insect pest Diatraea saccharalis, a major pest of sugarcane crops. A dataset comprising 945 training images and 470 test images of deceased insects collected from traps was compiled in order to train and test the model. The Yolov8 Computer Vision framework was employed for software implementation. Results indicate promising outcomes, with the trained CNN achieving 96.2% precision and 95.8% recall. The application of Computer Vision in pest management could lead to more timely and accurate detection of pests, reducing the need for widespread insecticide use, enabling specific interventions, and minimizing labor-intensive monitoring tasks. This research highlights the potential of Deep Learning methodologies to enhance agricultural pest management strategies by improving early pest detection, reducing crop damage, and optimizing the use of pest control resources.
The present study aims to expose information about the dynamics between the chemical attributes of corn and the direct and indirect influence of these attributes on the proteins of the grain. The attributes analyzed were grain mass, total soluble solids, pH, total titratable acidity, ashes, moisture content, lipids, proteins, and carbohydrates. A network of correlations was obtained and descriptive statistical results of the attributes were generated. Through a path analysis, in which protein content was the main variable, the direct and indirect correlation between the attributes was determined. The moisture level and ash content obtained for the corn were similar to those found in literature. The levels of protein, lipids, and carbohydrates were lower than those established in the Brazilian Table of Food Composition. It was concluded that lipids were the attributes that best determine corn proteins.
The Sustainable Development Goals (SDGs), transcending their prescribed targets and actions, propose a critical reflection on global food production and consumption patterns. These inquiries foster the promotion of resilient agri-food systems, with Agroecology identified as a pragmatically viable alternative for achieving the advocated goals. The scope of this article is to discuss these intersections, demonstrating that simple actions such as valuing local products, as advocated by Slow Food, can strengthen relationships and networks around food, promoting food security, preservation of knowledge, practices, traditions, and biodiversity, as well as the sense of belonging, improvement of quality of life, sustainable development, and local governance. Methodologically, this research is qualitative, adopting a bibliographical approach and employing a literature review to contextualize and reflect the problem, anchored in the Agroecology domains, SDGs, and the paradigm proposed by the Slow Food movement. This study substantially contributes to understanding the intricate relationships between the SDGs, agri-food systems, and Agroecology. By emphasizing the importance of seemingly simple practices, such as valuing local products, the article highlights the imperative of holistic and sustainable approaches to achieve broader sustainable development goals guided by the principles of “well-being.”
The maize crop is highlighted in the worldwide and Brazilian agribusiness, presenting itself as a raw material for both human and animal nutrition. Nitric oxide (NO) stands out as a signalling molecule playing a crucial role in plant responses to abiotic stresses as caused by heavy metals. Therefore, the objective of this work was to evaluate the effect of nitric oxide on the levels of macro and micronutrients, such as cationic magnesium, calcium, iron, copper, zinc and manganese. The copper bioaccumulation and translocation factor, in the initial growth of maize seedlings were subjected to copper toxicity. The seeds were soaked for 48 hours in Germitest paper using a solution containing sodium nitroprusside Na2[Fe(CN)5NO]2H2O as a donor of nitric oxide, sodium ferrocyanide Na4Fe (CN)6 as compensator and deionized water (control). The experiment was carried out in a 4 x 3 completely randomized factorial design with 12 treatments and 8 repetitions, totaling 96 trays containing 25 seeds per repetition. The results showed that the doses of nitric oxide were not sufficient to attenuate the copper toxicity, highlighting the metal accumulation in the roots. The doses of sodium nitroprusside and sodium ferrocyanide provided toxicity, changing the mineral balance in the mobilization of macro and cationic micronutrients and their translocation to the aerial part of K9606VIP3 maize seedlings in the initial growth.
At a global level, it is estimated that between 30% and 50% of agricultural production is influenced by the use of commercial fertilizers. The objective of this study was to evaluate the performance of soybean and corn subjected to doses of fertilizers containing multiple micronutrients. The experiment was conducted on the Água Limpa Araras property, in the 2022/2023 season. The experimental design adopted was randomized blocks, consisting of six treatments and four replicates, totaling 24 experimental units. Treatments were Fert Micro BR 12 fertilizer doses of: 0; 25; 50; 75; 100 and 125 kg ha-1. Leaf B, Mn and Zn contents were within the range considered ideal for soybean and corn crops, except in the corn crop, where the leaf Mn content in the control treatment and at a dose of 25 kg ha-1. Soybean and corn responded to the application of fertilizer containing multiple micronutrients. Soybean responded linearly with the increase in the dose of fertilizer containing multiple micronutrients, reaching a grain yield of 5,535 kg ha-1 with a dose of 125.0 kg ha-1. For corn, the maximum estimated dose of fertilizer containing multiple micronutrients was 115.8 kg ha-1, with grain yield of 12,454.48 kg ha-1.
This study aimed to evaluate the yield performance, physiological and nutritional quality of wheat seeds and grains subjected to times of application of a physiological ripening agent in pre-harvest. The experiment was arranged in a randomized block design and the treatments were six times of application of the physiological process of ripening in three replications. The applications were carried out at the ealy milk stage, milk stage, early dough stage, soft dough stage, hard dough stage and a control with no application. Yield, nutritional characteristics and the physiological quality of the seeds were evaluated. Analysis of variance and the Skott Knott test were performed at 5% probability. Linear correlation coefficients between pairs of traits were calculated. The application of the physiological process of ripening from the soft dough stage did not affect wheat grain yield. Wheat seed germination was not impacted when the physiological process of ripening was applied from the hard dough stage. The use of the ripening agent reduced the vigor of wheat seeds, regardless of the time of application. The presence of protein in grains was not influenced by the application of the physiological ripening agent. Starch had the greatest expression when the physiological process of ripening was applied between the milk stage and the early dough stage.
Brazil is the largest producer and consumer of beans in the world; however, the prospect of climate change could affect this production. Among these changes, the incidence of rising temperatures can directly affect the crop cycle, influencing biochemical processes that occur during seed germination and seedling emergence. The objective of this work was to determine the optimum temperature level for the emergence and initial growth of three varieties of cowpea. The experiment was conducted in a laboratory linked to the Federal University of the São Francisco Valley, Juazeiro Campus, state of Bahia, with a completely randomized design (DIC), in a 6x3 factorial scheme, with six treatments at different temperature levels: 20, 25, 30, 35, 40 and 45 °C; and three varieties of cowpea: BRS Pajeú, BRS Nova Era and BRS Pujante. The following variables were assessed: speed index, average time, relative frequency and percentage of emergence; stem length and diameter; accumulation of fresh and dry biomass in the stem, leaf and root. The ideal temperature range found for the emergence and initial growth of the cowpea varieties BRS Pajeú ranged from 27 to 32 ºC, for BRS Nova Era between 30 and 41 ºC and for BRS Pujante between 29 and 35 ºC. As the BRS Nova Era variety performs better in high temperature conditions, it could be an alternative for growing beans in the face of climate change.
