Artigos - Engenharia Rural - FCAV

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    Scenarios of environmental deterioration in the Paraopeba River, in the three years after the breach of B1 tailings dam in Brumadinho (Minas Gerais, Brazil)
    (2023-09-15) Mendes, Rafaella Gouveia; do Valle Junior, Renato Farias; de Melo Silva, Maytê Maria Abreu Pires; de Morais Fernandes, Gabriel Henrique; Fernandes, Luís Filipe Sanches; Pissarra, Teresa Cristina Tarlé [UNESP]; de Melo, Marília Carvalho; Valera, Carlos Alberto; Pacheco, Fernando António Leal [UNESP]; Federal Institute of Triângulo Mineiro (IFTM); University of Trás-os-Montes e Alto Douro; Universidade Estadual Paulista (UNESP); Cidade Administrativa do Estado de Minas Gerais; Coordenadoria Regional das Promotorias de Justiça do Meio Ambiente das Bacias dos Rios Paranaíba e Baixo Rio Grande
    The collapse of B1 dam at the Córrego do Feijão mine of Vale, S.A., located in the Ferro-Carvão stream watershed (Brazil), released 11.7 Mm3 of tailings rich in iron and manganese, and 2.8 Mm3 entered the Paraopeba River 10 km downstream. Seeking to predict the evolution of environmental deterioration in the river since the dam break on January 25, 2019, the present study generated exploratory and normative scenarios based on predictive statistical models, and proposed mitigating measures and subsides to ongoing monitoring plans. The scenarios segmented the Paraopeba into three sectors: “anomalous” for distances ≤63.3 km from the B1 dam site, “transition” (63.3–155.3 km), and “natural” (meaning unimpacted by the mine tailings in 2019; >155.3 km). The exploratory scenarios predicted a spread of the tailings until reaching the “natural” sector in the rainy season of 2021, and their containment behind the weir of Igarapé thermoelectric plant located in the “anomalous” sector, in the dry season. Besides, they predicted the deterioration of water quality and changes to the vigor of riparian forests (NDVI index) along the Paraopeba River, in the rainy season, and a restriction of these impacts to the “anomalous” sector in the dry season. The normative scenarios indicated exceedances of chlorophyll-a in the period January 2019–January 2022, but not exclusively caused by the rupture of B1 dam as they also occurred in areas not affected by the accident. Conversely, the manganese exceedances clearly flagged the dam failure, and persist. The most effective mitigating measure is likely the dredging of the tailings in the “anomalous” sector, but currently it represents solely 4.6 % of what has entered the river. Monitoring is paramount to update the scenarios until the system enters a route towards rewilding, and must include water and sediments, the vigor of riparian vegetation, and the dredging.
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    Adsorption of tebuthiuron on hydrochar: structural, kinetic, isothermal, and mechanistic modeling, and ecotoxicological validation of remediative treatment of aqueous system
    (2023-01-01) Moreira, Bruno Rafael de Almeida [UNESP]; Cruz, Victor Hugo [UNESP]; Barbosa Júnior, Marcelo Rodrigues [UNESP]; de Vasconcelos, Leonardo Gomes; da Silva, Rouverson Pereira [UNESP]; Lopes, Paulo Renato Matos [UNESP]; Universidade Estadual Paulista (UNESP); Federal University of Mato Grosso
    Tebuthiuron (C9H16N4OS) offers farmers a cost-effective chemical solution to control weeds. Nevertheless, it can manifest as a hazardous organic compound to society and the environment as it escapes from agroecosystems into the surroundings via leaching and running off, polluting surface and underground water bodies. Hence, research was designed to analyze whether hydrochar can develop an adsorbent to remove it from an aqueous solution. Food waste was reacted with subcritical water at a stoichiometric 1:4 ratio (m v−1) and 1.5 M potassium hydroxide (KOH) at 10 g L−1 at 250 °C and 1.5 MPa for 2 h to produce porous hydrochar via simultaneous hydrothermal carbonization and chemical activation. The product at 25, 50, and 100 mg L−1 was tested for its ability to adsorb tebuthiuron (TBT) at 0.5, 1, and 1.5 mg L−1 by spectrophotometry. In addition, kinetic and isothermal models were applied to experimental data to describe the separation of the pollutant from the liquid-phase analytical environment. Equally significant, an ecotoxicological assay was developed to investigate its remediative potential; Lactuca sativa was employed as a testing organism, as it is responsive to TBT at phytotoxic residual quantity. Hydrochar significantly separated TBT from aqueous media. Such honeycomb-structured mesoporous carbonaceous matrix developed approximately 1420.1 m2 g−1 specific surface area and 0.05 cm3 g−1 total pore volume; hence, at the highest concentration, it adsorbed 98.65% of TBT at 1.5 mg L−1 through physical (e.g., pore filling and interparticle diffusion) or chemical (e.g., H-bonding, π-stacking, and metal-adsorbate complex) forces. In addition, it allowed seven adsorption-desorption cycles with 80% efficiency, supporting excellent regenerability. Equally significant, L. sativa germinated 76.6% on plates containing residual solution from sorption testing, validating the hydrochar for environmental bioremediation. Hence, it can advance the field’s prominence in treating TBT by bioadsorption. It can offer stakeholders across agroindustries possibilities to remediate such a compound in aquatic environments, such as water and wastewater. Graphical Abstract: [Figure not available: see fulltext.]
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    Hydrologic Response to Land Use and Land Cover Change Scenarios: An Example from the Paraopeba River Basin Based on the SWAT Model
    (2023-04-01) Costa, Renata Cristina Araújo [UNESP]; Santos, Regina Maria Bessa; Fernandes, Luís Filipe Sanches [UNESP]; Carvalho de Melo, Marília [UNESP]; Valera, Carlos Alberto [UNESP]; Valle Junior, Renato Farias do [UNESP]; Silva, Maytê Maria Abreu Pires de Melo [UNESP]; Pacheco, Fernando António Leal [UNESP]; Pissarra, Teresa Cristina Tarlé [UNESP]; University of Trás-os-Montes and Alto Douro (UTAD); Universidade Estadual Paulista (UNESP); Cidade Administrativa do Estado de Minas Gerais; Coordenadoria Regional das Promotorias de Justiça do Meio Ambiente das Bacias dos Rios Paranaíba e Baixo Rio Grande; Federal Institute of Triângulo Mineiro (IFTM)
    Human land use land cover changes (LULCCs) can cause impacts on watershed lands and on water resources. The regions with land use conflict suffer more intense erosion processes due to their high slope and drainage density. The study intends to evaluate scenarios with an absence of land use conflict and verify if it can contribute to reductions in surface runoff, avoiding the carriage of tailings to river channels. In the study, the SWAT model was used in the hydrological modeling of the Paraopeba River watershed affected by the rupture. The results show that the SWAT model was able to reproduce the flow data with good and very good performances. The quality indicators in the calibration step were NSE = 0.66, R2 = 0.69, PBIAS = 5.2%, and RSR = 0.59, and in the validation, step were NSE = 0.74, R2 = 0.77, PBIAS = 13.5%, and RSR = 0.51. The LULCC from 2000 to 2019 led to a 70% increase in lateral runoff (LATQ) and a 74% decrease in aquifer groundwater. The scenario of land use capability and no conflict can reduce lateral runoff by 37% and increase water infiltration by 265%, minimizing the point and diffuse contamination of the tailings in the Paraopeba river channel.
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    The Accuracy of Land Use and Cover Mapping across Time in Environmental Disaster Zones: The Case of the B1 Tailings Dam Rupture in Brumadinho, Brazil
    (2023-04-01) Filho, Carlos Roberto Mangussi; do Valle Junior, Renato Farias; de Melo Silva, Maytê Maria Abreu Pires; Mendes, Rafaella Gouveia; de Souza Rolim, Glauco [UNESP]; Pissarra, Teresa Cristina Tarlé [UNESP]; de Melo, Marília Carvalho; Valera, Carlos Alberto; Pacheco, Fernando António Leal [UNESP]; Fernandes, Luís Filipe Sanches; Federal Institute of Triângulo Mineiro (IFTM); Universidade Estadual Paulista (UNESP); Cidade Administrativa do Estado de Minas Gerais; Coordenadoria Regional das Promotorias de Justiça do Meio Ambiente das Bacias dos Rios Paranaíba e Baixo Rio Grande; University of Trás-os-Montes e Alto Douro
    The rupture of a tailings dam causes several social, economic, and environmental impacts because people can die, the devastation caused by the debris and mud waves is expressive and the released substances may be toxic to the ecosystem and humans. There were two major dam failures in the Minas Gerais state, Brazil, in the last decade. The first was in 2015 in the city of Mariana and the second was in 2019 in the municipality of Brumadinho. The extent of land use and cover changes derived from those collapses were an expression of their impacts. Thus, knowing the changes to land use and cover after these disasters is essential to help repair or mitigate environmental degradation. This study aimed to diagnose the changes to land cover that occurred after the failure of dam B1 in Brumadinho that affected the Ferro-Carvão stream watershed. In addition to the environmental objective, there was the intention of investigating the impact of image preparation, as well as the spatial and spectral resolution on the classification’s accuracy. To accomplish the goals, visible and near-infrared bands from Landsat (30 m), Sentinel-2 (10 m), and PlanetScope Dove (4.77 m) images collected between 2018 and 2021 were processed on the Google Earth Engine platform. The Pixel Reduction to Median tool was used to prepare the record of images, and then the random forest algorithm was used to detect the changes in land cover caused by the tailings dam failure under the different spatial and spectral resolutions and to provide the corresponding measures of accuracy. The results showed that the spatial resolution of the images affects the accuracy, but also that the selected algorithm and images were all capable of accurately classifying land use and cover in the Ferro-Carvão watershed and their changes over time. After the failure, mining/tailings areas increased in the impacted zone of the Ferro-Carvão stream, while native forest, pasture, and agricultural lands declined, exposing the environmental deterioration. The environment recovered in subsequent years (2020–2021) due to tailings removal and mobilization.
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    Does the Soil Tillage Affect the Quality of the Peanut Picker?
    (2023-04-01) Lopes de Brito Filho, Armando [UNESP]; Morlin Carneiro, Franciele; Costa Souza, Jarlyson Brunno [UNESP]; Luns Hatun de Almeida, Samira [UNESP]; Patias Lena, Bruno; Pereira da Silva, Rouverson [UNESP]; Universidade Estadual Paulista (UNESP); Federal Technological University of Paraná (UTFPR); University of Nebraska–Lincoln
    Machine harvesting is an essential step of crop production, considering a dynamic operation, and is subject to losses due to several factors that affect its quality. The objective of this study was to evaluate the quality of mechanized peanut pickers in the three soil tillage operations using Statistical Quality Control (SQC) tools. We conducted the experiments in a peanut field located at 21°20′23″ S and 47°54′06″ W of Brazilian peanut farmers. We used Statistic Control Quality (SQC) experimental design to monitor peanut losses during machine harvesting. The treatments evaluated were three soil tillage operations: conventional (CT), rotary tillers (RT), and hoe (RH). The quality indicators were collected inside the picker’s bulk tank. Statistical analyses used were descriptive statistics and SQC tools (run charts, control charts, and the Ishikawa diagram). The process was considered stable for indicators: whole pods (CT, RT, and RH), broken pods (CT, RT, and RH), and hatched pods (CT, RT, and RH), while the other indicators showed points that were out of control. With the application of SQC tools, it was possible to identify the factors that caused the increase of variability in peanut harvesting, listing the points to be improved to support decision-making, always aiming to increase this operation’s quality.
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    Performance of the SAFER model in estimating peanut maturation
    (2023-07-01) de Almeida, Samira Luns Hatum [UNESP]; Souza, Jarlyson Brunno Costa [UNESP]; Pilon, Cristiane; Teixeira, Antônio Heriberto de Castro; dos Santos, Adão Felipe; Sysskind, Morgan Nicole; Vellidis, George; da Silva, Rouverson Pereira [UNESP]; Universidade Estadual Paulista (UNESP); Tifton Campus; Universidade Federal de Sergipe (UFS); Universidade Federal de Lavras (UFLA)
    The most widespread method for obtaining Peanut Maturity Index (PMI), the Hull-Scrape, is time-consuming and highly subjective, which makes its application on a large scale difficult and does not represent the variability of the production area. Seeking more accurate PMI estimates, this research uses a combination of weather and spectral data. Therefore, this study aimed to evaluate the performance of the Simple Algorithm for Evapotranspiration Retrieving (SAFER) model to calculate evapotranspiration and estimate PMI, indicating the optimal timing for crop digging. The experiment was conducted in three commercial peanut fields (A, B, and C) in Georgia, USA, in the 2020 and 2021 growing seasons. Pods were collected on different dates and classified according to maturity using the Hull-Scrape method. Weather data and PlanetScope images were used to calculate actual evapotranspiration from the SAFER model, which was correlated with the PMI collected in situ and used to generate linear regression models. Maturity in Fields A and B showed a stronger correlation with evapotranspiration estimated by SAFER (0.757 and 0.796, respectively), which led to the development of a model using data from these two fields. This model presented a relative error of 13.16% and proved to be the most suitable for estimating peanut maturity by integrating different field conditions. The SAFER model proved to be promising for estimating PMI, as it reduces the subjectivity of the traditional method by eliminating the need for a person to identify the color of pod mesocarp. Additionally, the model does not require images from the given day PMI is estimated, allowing for the estimation even in regions highly affected by the presence of clouds and shadows.
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    Selection of a Navigation Strategy According to Agricultural Scenarios and Sensor Data Integrity
    (2023-03-01) Bonacini, Leonardo; Tronco, Mário Luiz; Higuti, Vitor Akihiro Hisano; Velasquez, Andres Eduardo Baquero; Gasparino, Mateus Valverde; Peres, Handel Emanuel Natividade; Oliveira, Rodrigo Praxedes de; Medeiros, Vivian Suzano; Silva, Rouverson Pereira da [UNESP]; Becker, Marcelo; Universidade de São Paulo (USP); Universidade Estadual Paulista (UNESP)
    In digital farming, the use of technology to increase agricultural production through automated tasks has recently integrated the development of AgBots for more reliable data collection using autonomous navigation. These AgBots are equipped with various sensors such as GNSS, cameras, and LiDAR, but these sensors can be prone to limitations such as low accuracy for under-canopy navigation with GNSS, sensitivity to outdoor lighting and platform vibration with cameras, and LiDAR occlusion issues. In order to address these limitations and ensure robust autonomous navigation, this paper presents a sensor selection methodology based on the identification of environmental conditions using sensor data. Through the extraction of features from GNSS, images, and point clouds, we are able to determine the feasibility of using each sensor and create a selection vector indicating its viability. Our results demonstrate that the proposed methodology effectively selects between the use of cameras or LiDAR within crops and GNSS outside of crops, at least 87% of the time. The main problem found is that, in the transition from inside to outside and from outside to inside the crop, GNSS features take 20 s to adapt. We compare a variety of classification algorithms in terms of performance and computational cost and the results show that our method has higher performance and lower computational cost. Overall, this methodology allows for the low-cost selection of the most suitable sensor for a given agricultural environment.
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    Unmanned aerial system and satellite: Which one is a better platform for monitoring of the peanut crops?
    (2023-05-01) Costa Souza, Jarlyson Brunno [UNESP]; Luns Hatum de Almeida, Samira [UNESP]; Lopes de Brito Filho, Armando [UNESP]; Morlin Carneiro, Franciele; Santos, Adão Felipe dos; da Silva, Rouverson Pereira [UNESP]; Universidade Estadual Paulista (UNESP); Universidade Federal de Lavras (UFLA)
    Remote sensing tools are helpful in monitoring and managing crop production. However, each remote sensing technology responds to crop variability differently. In this way, the objective of this work was to compare sensors on airborne and orbital platforms and to observe which one has the best quality to determine the behavior of the peanut (Arachis hypogaea L.) crop variability. The experimental design followed the premises of the statistical quality control (SQC), with samples collected over time. The experimental area was composed of 30 sampling points spaced every 50 m. The multispectral images were acquired with an unmanned aerial system (UAS) consisting of a DJI Matrice quad-copter and a Micasense RedEdge multispectral camera and with the PlanetScope multispectral imaging satellites. It was verified that in all periods evaluated for spectral bands and vegetation indices (VI), satellite images presented better process quality. The enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI) generated from satellite images were able to detect the peanut maturation variation better. The behavior of the bands and the VIs generated from the Planet images show quality for peanut crop monitoring. While UAS showed sensitivity to detect the saturation of the bands, making it difficult to visualize the temporal variability.
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    How to decide between buying or renovating agricultural tractors?
    (2022-01-01) Vidal, Diego Onofre [UNESP]; da Silva, Rouverson Pereira [UNESP]; de Oliveira, Bruno Rocca [UNESP]; Conceição, Elimar Veloso; Santos, David Ferreira Lopes [UNESP]; Universidade Estadual Paulista (UNESP); Universidade de São Paulo (USP)
    Deciding whether to buy or rebuild a tractor and when to do so is an empirical problem for farmers and/or rural administrators, whose analytical methods explored in the literature do not provide a clear approach to the operational and economic effects in the short and long term, despite its importance to the competitiveness of the activity. If the cost of replacing the agricultural tractors used in spraying the citrus crop could be more helpful than the reform of these, this study aimed to build and validate an economic evaluation method to support the decision to buy new or replace existing wheel tractors. To achieve such goals, a database with quarterly operational and financial information on 47 tractors between 2009 and 2017 was constructed. The method combined the use of an empirical, with the use of model panel-data regression, combining cross-sectional data with time series, to establish the actual cost information to be used in the model, and finally, implement the discounted cash flow, in which all uncertainties were controlled using a Monte Carlo simulation. The results indicated that the best decision is to purchase new equipment only after the fourth year of use. It stands out in the study findings, the impact of tax benefits and the resale of tractors were relevant to the cash flow, as well as the increase in maintenance costs over time. The economic evaluation method applied in this study can help rural producers and administrators in the decision-making process for investments in fixed assets and innovative technologies, thereby enabling them to be more accurate in their investment decisions. Technological progress increases the obsolescence rate of agricultural machinery and equipment whose paradigm referring to replacement was restricted to costs and operating conditions. In this study, it was found that the aggregate impact of expenditures and tax benefits had significant relevance on cash flow, therefore, should guide the analysis to create economic value.
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    Multicriteria spatial model to prioritize degraded areas for landscape restoration through agroforestry
    (2023-01-01) de Mendonça, Gislaine Costa [UNESP]; da Costa, Luis Miguel [UNESP]; Abdo, Maria Teresa Vilela Nogueira [UNESP]; Costa, Renata Cristina Araújo [UNESP]; Parras, Rafael [UNESP]; de Oliveira, Laís Caroline Marianno [UNESP]; Pissarra, Teresa Cristina Tarlé [UNESP]; Pacheco, Fernando António Leal [UNESP]; Universidade Estadual Paulista (UNESP); Guarulhos University (UNG); APTA - São Paulo Agency of Agribusiness Technology; University of Trás-os-Montes and Alto Douro
    Reconciling the restoration of ecosystem services within agricultural landscapes is an effort that has been advancing within degraded areas restoration through agroforestry systems. However, to contribute to the effectiveness of these initiatives, it is essential to integrate landscape vulnerability and local demands to better highlight in which areas the implementation of agroforestry systems should be prioritized. Thus, we developed a spatial hierarchization methodology as a decision support tool as an active strategy for agroecosystem restoration. The proposed method constitutes a spatial indicator of priority areas to guide agroforestry interventions, including resource allocation and public policies for payment for environmental services. The methodology consists of Multicriteria Decision Analysis implemented in GIS software by combining input datasets based on biophysical conditions, environmental and socioeconomic aspects, that integrated promotes an assessment of the environment fragility, the pressures and responses to land use dynamic; a strategy for landscape restoration and conservation of the natural habitats, and multiple specific scenarios for decision making regarding the agricultural and the local actors demands. The output of the model provides the spatial distribution of areas suitable for the implementation of agroforestry systems, sorted into four priority levels (Low, Medium, High, and Extreme priority). The method is a promising tool proposal for territorial management and governance and subsidizes future research on the flows of ecosystem services. • Assessment of the environment fragility and the pressures and responses to land use dynamic. • Strategy for landscape restoration and conservation of remaining natural habitats. • Multiple specific scenarios for decision making regarding the agricultural and the local actors demands.
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    The COP27 screened through the lens of global water security
    (2023-05-15) de Melo, Marília Carvalho; Fernandes, Luís Filipe Sanches; Pissarra, Teresa Cristina Tarlé [UNESP]; Valera, Carlos Alberto; da Costa, Adriana Monteiro; Pacheco, Fernando António Leal [UNESP]; Cidade Administrativa do Estado de Minas Gerais; Universidade Vale do Rio Verde (UNINCOR); Universidade de Trás-os-Montes e Alto Douro (UTAD); Universidade Estadual Paulista (UNESP); Coordenadoria Regional das Promotorias de Justiça do Meio Ambiente das Bacias dos Rios Paranaíba e Baixo Rio Grande; Universidade Federal de Minas Gerais (UFMG)
    Water security is an expression of resilience. In the recent past, scientists and public organizations have built considerable work around this concept launched in 2013 by the United Nations as “the capacity of a population to safeguard sustainable access to adequate quantities of acceptable quality water for sustaining livelihoods, human well-being, and socio-economic development, for ensuring protection against water-borne pollution and water-related disasters, and for preserving ecosystems in a climate of peace and political stability”. In the 27th Conference of the Parties (COP27), held in Sharm El-Sheikh (Egypt) in last November, water security was considered a priority in the climate agenda, especially in the adaption and loss and damage axes. This discussion paper represents the authors' opinion about how the conference coped with water security and what challenges remain to attend. As discussion paper, it had the purpose to stimulate further discussion in a broader scientific forum.
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    Forage Mass Estimation in Silvopastoral and Full Sun Systems: Evaluation through Proximal Remote Sensing Applied to the SAFER Model
    (2023-02-01) Luns Hatum de Almeida, Samira [UNESP]; Brunno Costa Souza, Jarlyson [UNESP]; Furlan Nogueira, Sandra; Ricardo Macedo Pezzopane, José; Heriberto de Castro Teixeira, Antônio; Bosi, Cristiam; Adami, Marcos; Zerbato, Cristiano [UNESP]; Carlos de Campos Bernardi, Alberto; Bayma, Gustavo; Pereira da Silva, Rouverson [UNESP]; Universidade Estadual Paulista (UNESP); Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA); Universidade Federal de Sergipe (UFS); National Institute for Space Research (INPE)
    The operational slowness in the execution of direct methods for estimating forage mass, an important variable for defining the animal stocking rate, gave rise to the need for methods with faster responses and greater territorial coverage. In this context, the aim of this study was to evaluate a method to estimate the mass of Urochloa brizantha cv. BRS Piatã in shaded and full sun systems, through proximal sensing applied to the Simple Algorithm for Evapotranspiration Retrieving (SAFER) model, applied with the Monteith Radiation Use Efficiency (RUE) model. The study was carried out in the experimental area of Fazenda Canchim, a research center of Embrapa Pecuária Sudeste, São Carlos, SP, Brazil (21°57′S, 47°50′W, 860 m), with collections of forage mass and reflectance in the silvopastoral systems animal production and full sun. Reflectance data, as well as meteorological data obtained by a weather station installed in the study area, were used as input for the SAFER model and, later, for the radiation use efficiency model to calculate the fresh mass of forage. The forage collected in the field was sent to the laboratory, separated, weighed and dried, generating the variables of pasture total dry mass), total leaf dry mass, leaf and stalk dry mass and leaf area index. With the variables of pasture, in situ, and fresh mass, obtained from SAFER, the training regression model, in which 80% were used for training and 20% for testing the models. The SAFER was able to promisingly express the behavior of forage variables, with a significant correlation with all of them. The variables that obtained the best estimation performance model were the dry mass of leaves and stems and the dry mass of leaves in silvopastoral and full sun systems, respectively. It was concluded that the association of the SAFER model with the proximal sensor allowed us to obtain a fast, precise and accurate forage estimation method.
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    Application of the CSM-CROPGRO-Dry bean model to optimize irrigation as a function of sowing date in common bean cultivars
    (2023-03-15) Coelho, Anderson Prates [UNESP]; Faria, Rogério Teixeira de [UNESP]; Lemos, Leandro Borges [UNESP]; Cazuza Neto, Ancelmo [UNESP]; Universidade Estadual Paulista (UNESP)
    Common bean is grown in tropical and subtropical regions under a wide range of pedoclimatic conditions and there is a large variation between the management practices, types of cultivars being used and the farmers' technological level. In this context, simulation models are feasible and promising alternatives for site specific management practices. This study aimed to use the CSM-CROPGRO-Dry bean model as a tool to optimize irrigation management as a function of sowing date and common bean cultivar. Two common bean cultivars IAC Imperador (determinate growth habit) and IPR Campos Gerais (indeterminate growth) were grown during two winter growing seasons in a field experiment conducted in south-eastern Brazil. The experiment included five irrigation treatments (54%, 70%, 77%, 100%, and 132% of crop evapotranspiration). After model parameterization, a long-term analysis was performed to simulate the effect of the five irrigation levels on the grain yield of common bean cultivars as a function of eight sowing dates. The results showed that irrigation may be managed under a regulated water deficit without significantly reducing common bean yields if sowing is brought forward (Mar/Apr) within the winter season. For no deficit irrigation, sowing dates in which common bean reproductive stages coincide with the period of lowest global solar radiation (GSR) should be avoided. This is because, for each unit increase in GSR after flowering, grain yields of the cultivars IAC and IPR increase by 55 and 50 kg ha−1, respectively. Therefore, the CSM-CROPGRO-Dry bean model is a powerful tool for defining more specific and sustainable irrigation management for common bean cultivars.
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    Effect of subsurface irrigation on the productivity and technological quality of sugarcane
    (2022-01-01) Filho, Joao Alberto Fischer [UNESP]; Cavichioli, Thiago Henrique [UNESP]; Dalri, Alexandre Barcellos [UNESP]; Coelho, Anderson Prates [UNESP]; Martins, Izabela Paiva [UNESP]; Zanini, Jose Renato [UNESP]; Universidade Estadual Paulista (UNESP)
    The aim of the study was to evaluate the effect of irrigation depths, via subsurface drip, on the technological quality, productivity, and water use efficiency (WUE) of sugarcane cultivars. The experimental design was of balanced blocks with 12 blocks and two factors: cultivars (CTC 4, IACSP93-3046, RB86-7515, IACSP95-5000 and IAC91-1099) and irrigation depths (dry, deficit and supplementary). From the estimated evapotranspiration (ETc), irrigation depths equivalent to 100% of crop ETc were defined for the supplemental treatment and 50% for deficit. The amounts of sucrose in the juice (POL) and the cane (PC) did not differ among the cultivars; however, additional irrigation provided higher values of the evaluated parameters. The purity levels of all treatments were superior to those recommended (85%) and differed between the cultivars. In the supplementary irrigation regime, the IAC91-1099 cultivar had the highest total recoverable sugar value (TRS), equal to 165.62 kg Mg-1, and the highest yields of stalks and sugars, 157.02 and 26.01 Mg ha-1, respectively. The WUE was superior in the dry regime for the CTC4 and RB86-7515 cultivars, and these were considered tolerant to the water deficit. The deficit irrigation provided average gains in the yield of sugarcane and sugar similar to supplementary irrigation; consequently, there were substantial reductions in water use and irrigation requirements in addition to energy savings.
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    Quantification and Evaluation of Water Requirements of Oil Palm Cultivation for Different Climate Change Scenarios in the Central Pacific of Costa Rica Using APSIM
    (2023-01-01) Watson-Hernández, Fernando; Serrano-Núñez, Valeria; Gómez-Calderón, Natalia; Pereira da Silva, Rouverson [UNESP]; Instituto Tecnológico de Costa Rica; Universidade Estadual Paulista (UNESP)
    Climate change is a variation in the normal behavior of the climate. These variations and their effects will be seen in the coming years, the most imminent being anomalous fluctuations in atmospheric temperature and precipitation. This scenario is counterproductive for agricultural production. This study evaluated the effect of climate change on oil palm production for conditions in the Central Pacific of Costa Rica, in three simulation scenarios: the baseline between the years 2000 and 2019, a first climate change scenario from 2040 to 2059 (CCS1), and a second one from 2080 to 2099 (CCS2), using the modeling framework APSIM, and the necessary water requirements were established as an adaptive measure for the crop with the irrigation module. A decrease in annual precipitation of 5.55% and 7.86% and an increase in the average temperature of 1.73 °C and 3.31 °C were identified, generating a decrease in production yields of 7.86% and 37.86%, concerning the Baseline, in CCS1 and CCS2, respectively. Irrigation made it possible to adapt the available water conditions in the soil to maintain the baseline yields of the oil palm crop for the proposed climate change scenarios.
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    A structural equation model of land capability and related drivers: Implications for land degradation forecasting in a tropical river basin
    (2023-04-15) de Morais Fernandes, Gabriel Henrique; do Valle Junior, Renato Farias; de Melo Silva, Maytê Maria Abreu Pires; Mendes, Rafaella Gouveia; Fernandes, Luís Filipe Sanches; Fernandes, António Carlos Pinheiro; Pacheco, Fernando António Leal; Pissarra, Teresa Cristina Tarlé [UNESP]; de Melo, Marília Carvalho; Valera, Carlos Alberto; Geoprocessing Laboratory; University of Trás-os-Montes e Alto Douro; University of Porto; Universidade Estadual Paulista (UNESP); Administrative City of the State of Minas Gerais; Regional Coordination of Environmental Prosecutors' Offices of the Paranaíba and Baixo Rio Grande River Basins
    Land degradation is a worldwide problem with natural and anthropogenic causes. An important anthropogenic cause of land degradation is land uses that deviate from land capability, which is the “natural” use. Despite the conscience of scientists about this issue, studies are lacking that set up a quantitative nexus between land capability and related drivers. This nexus is essential because it allows anticipating changes in the drivers that promote or recede degradation. In this study, a partial least squares–path model (PLS–PM) was used to help closing this gap. The pilot study occurred in seven Paraopeba River sub-basins located in the State of Minas Gerais (Brazil), where capability is dominated by mosaics of forests and pastures. Land capability was assessed by the ruggedness number, being inversely proportional to it. Among multiple potential drivers of land capability initially included in the model, collinearity and other consistency and performance analyses indicated the percentage of latosols and (re)forested areas, annual rainfall, and water-related processes (e.g., weathering, nutrient leaching) as prominent in the studied region. The results linked increases of latosol and forest occupation to runoff reduction [runoff = latosol × (−0.640) + forest × (−0.156) + reforestation × (−0.379)], suggesting an attenuation of erosion by these parameters, namely gully erosion that impacts on the ruggedness number and land capability in the sequel. The weathering of carbonate rocks was also related to land capability changes because the PLS–PM model exposed a relationship between the ruggedness number and products of carbonate rock dissolution: ruggedness number = alkalinity × (−0.578) + total magnesium × (0.462) + dissolved oxygen × (−0.418). In addition to highlighting processes capable of changing land capability overtime, the model equations brought attention to measures that could improve it in the region thus preventing degradation. The measures included management practices capable to raise the soil's dissolved oxygen (e.g., through aeration) or preventing soil's magnesium deficiency (e.g., through foliar sprays). The network of cause-and-effect relationships set up by the PLS–PM model was finally used to elucidate about potential land use changes that would bring capability in the Paraopeba River basin towards a better status, such as conversions to pasture land. Future work is expected to further elucidate about the benefits for land capability of specific land use changes, through the testing of expected socioeconomic development scenarios.
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    Anaerobic digestion of vinasse and water treatment plant sludge increases methane production and stability of UASB reactors
    (2023-02-01) Lima, Vivian de Oliveira [UNESP]; Barros, Valciney Gomes de [UNESP]; Duda, Rose Maria [UNESP]; Oliveira, Roberto Alves de [UNESP]; Universidade Estadual Paulista (UNESP); Science and Technology of São Paulo; Faculty of Technology “Nilo de Stéfani”
    Studies are still needed to increase the stability and efficiency of methane production from vinasse. Therefore, operations strategies, such as the anaerobic digestion with one or more wastes and adding micronutrients, especially iron, become attractive. The performance of two treatment systems, each one composed of two UASB reactors in series, operated under mesophilic (R1M and R2M) and thermophilic (R1T and R2T) temperature conditions, was evaluated in the anaerobic digestion of vinasse (ADV). First, the reactors were operated with the effluent recirculation and increasing organic loading rate (OLR) up to 20 g CODtotal L−1d−1 in the R1M and R1T. Then, the anaerobic digestion of vinasse and water treatment plant (WTP) sludge (ADVS) was performed in the proportions of 25:75 to 50:50 (% v/v) in both systems. In the ADV, applying the highest OLR, the mesophilic and thermophilic reactors instabilities happened. The ADVS of over 35% of WTP sludge promoted the recovery of the mesophilic and thermophilic UASB reactors with significantly reduced total volatile acids and increased alkalinity and biogas production. The higher average values of the volumetric methane production (VMP) occurred in the ADVS at 50% of WTP; in the R1M and R1T, they were 3.23 and 3.00 L CH4 L−1d−1, respectively. In the ADV, the thermophilic system presented higher VMP concerning the mesophilic for OLR up to 15 g CODtotal L−1d−1. For higher OLR, the mesophilic system showed better carrying capacity and stability. The ADVS with above 35% of WTP sludge promoted similar benefits in the two systems, with no significant differences in CODtotal removal and VMP. Therefore, adding iron by WTP sludge in ADVS improves methane production and increases the stability of UASB reactors under mesophilic and thermophilic conditions.
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    Training Machine Learning Algorithms Using Remote Sensing and Topographic Indices for Corn Yield Prediction
    (2022-12-01) Oliveira, Mailson Freire de [UNESP]; Ortiz, Brenda Valeska; Morata, Guilherme Trimer; Jiménez, Andrés-F; Rolim, Glauco de Souza [UNESP]; Silva, Rouverson Pereira da [UNESP]; Universidade Estadual Paulista (UNESP); Auburn University; Macrypt R.G. Universidad de los Llanos
    Methods using remote sensing associated with artificial intelligence to forecast corn yield at the management zone level can help farmers understand the spatial variability of yield before harvesting. Here, spectral bands, topographic wetness index, and topographic position index were integrated to predict corn yield at the management zone using machine learning approaches (e.g., extremely randomized trees, gradient boosting machine, XGBoost algorithms, and stacked ensemble models). We tested four approaches: only spectral bands, spectral bands + topographic position index, spectral bands + topographic wetness index, and spectral bands + topographic position index + topographic wetness index. We also explored two approaches for model calibration: the whole-field approach and the site-specific model at the management zone level. The model’s performance was evaluated in terms of accuracy (mean absolute error) and tendency (estimated mean error). The results showed that it is possible to predict corn yield with reasonable accuracy using spectral crop information associated with the topographic wetness index and topographic position index during the flowering growth stage. Site-specific models increase the accuracy and reduce the tendency of corn yield forecasting on management zones with high, low, and intermediate yields.
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    Impacts of urban sprawl in the Administrative Region of Ribeirão Preto (Brazil) and measures to restore improved landscapes
    (2023-01-01) Marianno de Olivera, Laís Caroline [UNESP]; de Mendonça, Gislaine Costa [UNESP]; Araújo Costa, Renata Cristina [UNESP]; Leite de Camargo, Regina Aparecida [UNESP]; Fernandes, Luís Filipe Sanches [UNESP]; Pacheco, Fernando António Leal [UNESP]; Pissarra, Teresa Cristina Tarlé [UNESP]; Universidade Estadual Paulista (UNESP); Programa de Mestrado em Análise Geoambiental (MAG); University of Trás-os-Montes and Alto Douro
    The present study addressed the problem of urban expansion in a large metropolis of Brazil (ARRP – Administrative Region of Ribeirão Preto), relating the evolution of urbanization in the past 35 years with losses of agricultural area and respective equivalent production and economic effects. Besides these food security and agribusiness issues, the study tracked important environmental consequences of the observed growing urbanization. This included water insecurity related with the occupation of watercourse networks, destruction of riparian vegetation that is legally protected as Permanent Preservation Areas (PPAs), and the occupation of Guarani Aquifer recharge areas with impermeable surfaces. The database consisted of Landsat images interpreted and processed in a Geographic Information System (GIS). The results indicate losses of rural area exceeding 350 km2 in the studied timeframe, with equivalent production and economic losses around 1.1 Mton/year and 230 MR$/year, on average. It is worth to mention the 40–75% overlap between the impermeable surfaces of some ARRP municipalities (e.g., Cajuru, Altinópolis) and recharge areas of Guarani Aquifer. The impermeable surfaces within the ARRP also affected approximately 7000 headwaters that were potential hotspots of shallow aquifer recharge. The urban sprawl destroyed more than 9100 km of natural watercourses and nearly 630 km2 of PPAs. The pathways recognized to improve the ARRP landscape included implementation of urban agriculture and landscape planning measures capable to protect the recharge to and the quality of Guarani Aquifer water, mostly anchored in the Municipal Director Plans, the prominent land use policy tools in the ARRP. This integrated, long-term, spatially explicit and quantitative assessment of urban sprawl impacts assembled with indications of landscape restoration policies and measures is novel in Brazil. On the other hand, studying the ARRP is worthwhile because of its historical relationship with the Brazilian ethanol program that brought an accelerated development to the region following the World oil crisis of 1970 s until now.
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    (2022-01-01) Tavares, Marcos S. [UNESP]; da Camara, Felipe T.; Lopes, Afonso [UNESP]; Pinto, Antonio A. [UNESP]; Universidade Estadual Paulista (UNESP); Centro de Ciências Agrárias e da Biodiversidade - CCAB/UFCA - Universidade Federal do Cariri
    The growing demand for clean energy aimed at reducing greenhouse gas emissions associated with the oil crises has encouraged the search for biofuels, among which biodiesel has stood out in the gradual replacement of diesel. This study aimed to evaluate the performance of an agricultural tractor fueled with four types of biodiesels (peanut, sunflower, soybean, and waste frying oil) added to diesel at five proportions (0, 25, 50, 75, and 100% biodiesel, that is, B0, B25, B50, B75, and B100, respectively). The experiment was carried out at the Laboratory of Biofuel and Machinery Testing at FCAV– UNESP. A Valtra BM100 4×2 FWD tractor with a power of 74 kW (100 hp) was used. The drawbar pull force (DF), displacement velocity (V), drawbar power (DP), volumetric fuel consumption (VC), weight fuel consumption (WC), and specific fuel consumption (SC) were studied. The factors did not influence DF, V, and DP. The proportion factor influenced (p<0.01) the volumetric fuel consumption, in which diesel S50 was 14% more efficient than B100. Weight fuel consumption was influenced by the type of biodiesel in the blend. Diesel had the lowest specific fuel consumption (328 g kW h−1). The biodiesel fraction showed a direct relationship with the consumption parameters, with sunflower showing the lowest WC value in the B75 and B100 blends