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URI permanente desta comunidadehttps://thoth.dti.ufv.br/handle/123456789/3352
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Resultados da Pesquisa
Item Monitoring the vegetative state of coffee using vegetation indices(Associação Brasileira de Engenharia Agrícola, 2024) Chedid, Vitor; Cortez, Jorge W.; Arcoverde, Sálvio N. S.Vegetation indices are a quick and practical alternative for monitoring crops due to the availability of satellite images on various platforms for free, allowing a quick analysis of the vegetative state of the crop and interventions in the field in case of signs of diseases and pests. In this context, this study aimed to evaluate the vegetative state of the coffee crop using vegetation indices (NDVI, SAVI, ARVI, EVI, and VDVI) in an agricultural year. The study was carried out on a commercial farm using satellite images from the Planet platform, during an agricultural coffee growing season (2021/2022). The indices selected for the study were the Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Atmospherically Resistant Vegetation Index (ARVI), Enhanced Vegetation Index (EVI), and Visible Difference Vegetation Index (VDVI). The index data were analyzed using descriptive statistics, Pearson correlation, classification/interpretation proposal, and the Kappa index. NDVI and SAVI are efficient in monitoring coffee cultivation in an agricultural year, as the Kappa index was higher than 90%. ARVI and EVI had Kappa index values close to 90% and can be used to monitor the crop. VDVI was inefficient, with a low Kappa index value when compared to the others. The proposed classification for vegetation indices based on NDVI classes and values consisted of an important tool for classifying and interpreting the values of these indices, assisting monitoring and management of coffee cultivation.Item Performance of a variable-rate distribution system for simultaneous fertilizer application(Departamento de Engenharia Agrícola - UFCG, 2016) Barros, Murilo M. de; Volpato, Carlos E. S.; Silva, Fabio M. da; Conceição, Fagner G. da; Corrêa Júnior, Delorme; Ribeiro, Luiz F.The objective of this study was to evaluate the performance of a variable-rate fertilizer distribution system for coffee crop, simultaneously applying two products. Two types of tests were performed: transversal deposition and longitudinal deposition. The transversal deposition test, with tarps, aimed to quantify the variations between programmed and applied doses, using a completely randomized design (CRD), in a factorial scheme, and the Scott-Knott test at p < 0.05. The longitudinal deposition test aimed to determine the distribution characteristics of the equipment along the displacement line, based on relative frequency values. In addition, the application rates on both sides of the distribution system were analysed using a CRD and the Scott-Knott test at p < 0.05. The application variation in the transversal deposition test with tarps was 1.59%. The variable-rate distribution system remained stable regarding the longitudinal deposition, regardless of any interaction.Item Diagnosis about the perspectives of precision applications of coffee growing technologies in municipalities of Bahia, Brazil(Universidade Federal de Lavras, 2022-06-09) Fagundes, Rozymario Bittencourt; Bolfe, Édson LuisBrazil is the largest coffee producer in the world and precision agriculture (PA) is essential for the efficient management of crops. However, one of the challenges is finding the best way to do it. In this sense, we sought to present in this article a diagnosis on the perspectives of Precision Agriculture technologies applicability in the production of coffee (or Precision Coffee Growing) in some municipalities in Bahia, for greater efficiency, economic and environmental sustainability. To achieve this objective, a virtual document was sent to coffee growers in the state of Bahia. The questionnaire was sent by email in 2021 and the WhatsApp application, reaching 457 producers, 34 of whom, from all productive regions of Bahia, responded. The rate of return was 7.4%, within the expected by the use of the application. Considering the return of 34 answered questionnaires, a margin of error of 14% was obtained at a reliability level of 90%. It was found that 59.3% of the respondents have a high prospect of using PA in coffee growing, 26.6% have a medium perspective and 11.1%, a low perspective. The research shows that 67.6% do not use PA in the fields and that 51.7% consider the lack of training as a major obstacle to the use of PA and other digital technologies. Thus, the conclusion is reached that there is a promising scenario in Bahia state for the application of PA in coffee growing, if there is training for the development of techniques in farming.Item Comparing a single-sensor camera with a multisensor camera for monitoring coffee crop using unmanned aerial vehicles(Associação Brasileira de Engenharia Agrícola, 2021) Gomes, Amanda P. A.; Queiroz, Daniel M. de; Valente, Domingos S. M.; Pinto, Francisco de A. de C.; Rosas, Jorge T. F.There exist two options for digital cameras that can capture the near-infrared (NIR) band. Conventional red–green–blue (RGB, visible bands) cameras with a single sensor provide NIR band visibility based on the removal of the internal NIR-blocking filter. Alternatively, multisensor cameras exist that have a specific sensor for each band. The modified RGB cameras are of a lower price. In this context, the objective of this study was to compare the performance of a modified RGB camera with that of a multisensor camera for obtaining the normalized difference vegetation index (NDVI) in an area with coffee cultivations. A multispectral camera with five sensors and another camera with only one sensor were used. The NDVI of the coffee field was also measured using the GreenSeeker handheld NDVI sensor manufactured by Trimble. The images were calibrated radiometrically based on the targets in shades of gray made of napa, and the NDVI was calculated after image calibration. The calibration curves showed a high coefficient of determination. The NDVI value obtained with the calibrated images from the cameras showed a significant correlation with the values obtained by the GreenSeeker NDVI sensor, making it possible to obtain the variability pattern of the vegetation index. However, the NDVI obtained using the multisensor camera was closer to the NDVI obtained by the GreenSeeker NDVI sensor.Item Spatial correlation between the chlorophyll index and foliar npk levels in coffee crop(Editora UFLA, 2020) Zanella, Marco Antonio; Rodrigues Junior, Francelino Augusto; Sousa, Emanoel Di Tarso dos Santos; Martins, Rodrigo Nogueira; Calijuri, Maria LúciaDetection of spatial variability of data that can improve crop management is a key factor for precision agriculture. In agriculture, there is a need for tools to assist farmers in decision-making about proper nutrient management, aiming to achieve their full productive potential. Based on that, this study aimed to (1) determine the spatial correlations between the chlorophyll index (CI) and the foliar levels of nitrogen, phosphorus and potassium (NPK) in the coffee crop using geostatistical tools; and (2) to evaluate the potential use of this index as a tool for site-specific nutrient management in an irrigated coffee field. For that, a study was carried out in a 2.1 ha area under arabica coffee cultivation in Paula Cândido, Minas Gerais State, Brazil. Samplings of the CI were performed in 1141 plants using a portable chlorophyll meter (SPAD-502). Regarding the NPK analysis, leaf samples from one of each 10 plants used to measure the CI were taken for chemical analysis (114 plants). Then, the data were submitted to descriptive and geostatistical analysis. For the spatial correlation analysis, the Moran Bivariate Global (I) and the Local index (Ixy) were used. The results showed a moderate correlation between the CI and N (0.500), showing the potential of the chlorophyll meter as a tool for site-specific nitrogen management in the coffee crop. Differently, the CI is not recommended for P and K management since they were not well correlated. Lastly, as a tool that performs indirect measurements, the results from the chlorophyll meter should be validated by field measurements to local calibrations.Item Technical and economic viability of manual harvesting coffee yield maps(Editora UFLA, 2020) Faria, Rafael de Oliveira; Silva, Fábio Moreira; Ferraz, Gabriel Araújo e Silva; Herrera, Miguel Angel Diaz; Barbosa, Brenon Diennevan Souza; Alonso, Diego José Carvalho; Soares, Daniel VeigaPrecision coffee growing is a concept that implies the use of precision agriculture techniques in coffee plantations. For the coffee growing, the precision electronic resources coupled to the harvesters are very scarce. Thereby, the harvest of coffee plantations that compose the grid sampling for generation of thematic maps can be performed manually. The aim of the present study was to generate a linear regression model to estimate the time required to harvest, estimate the labor costs to harvest manually the georeferenced sample points for generation of coffee yield maps. The study was performed in a coffee area of 56 hectares using two sampling points per hectare, totaling 112 points, being evaluated four coffee plants for each point. The manual harvest of the points was performed by four rural workers with experience in the coffee harvest. Afterwards, the collected volume was measured by a graduated container and the times were obtained by the digital stopwatch. Based on the data obtained in the field, a linear correlation model was established between the harvest time of each sampling point and the yield of the point, whose R² value was 78.27, cost was R$ 8.92 per point. These results are relevant for estimating the amount of labor force required to generate manually harvest yield maps according to the producer’s coffee yield estimate, contributing to the closure of the precision coffee growing cycle.Item Sampling density for characterizing the physical quality of a soil under coffee cultivation in southwestern Minas Gerais(Associação Brasileira de Engenharia Agrícola, 2018-09) Silvero, Nélida E. Q.; Marques Júnior, José; Siqueira, Diego S.; Gomes, Romário P.; Costa, Milene M. R.The elaboration of maps to characterize the spatial variability of soil attributes assists in the strategic planning and decision making of agricultural managers. Precision and accuracy of maps are related to the ideal sampling density to characterize the variability pattern. This study was conducted with the aim of identifying the sampling density to represent the variability of soil physical quality using attributes with different magnitudes of variation in an area cultivated with coffee. Three approaches were used to find the most adequate sampling density (geostatistical analysis, percentage of error associated with the sampling density, and coefficient of variation). A total of 145 soil samples were collected at a depth of 0–0.20 m at the crossing points of a regular grid with a spacing of 50 m. The percentage of clay, silt, and sand, macroporosity, microporosity, total pore volume, and soil density were determined. The data were submitted to descriptive statistical analysis. For elaborating the variability maps with up to 15% error and soil attributes with a coefficient of variation close to 50%, a sampling density of 3 points ha−1 is suggested.Item Multivariate analysis and geostatistics of the fertility of a humic rhodic hapludox under coffee cultivation(Sociedade Brasileira de Ciência do Solo, 2012-03) Silva, Samuel de Assis; Lima, Julião Soares de SouzaThe spatial variability of soil and plant properties exerts great influence on the yeld of agricultural crops. This study analyzed the spatial variability of the fertility of a Humic Rhodic Hapludox with Arabic coffee, using principal component analysis, cluster analysis and geostatistics in combination. The experiment was carried out in an area under Coffea arabica L., variety Catucai 20/15 – 479. The soil was sampled at a depth 0.20 m, at 50 points of a sampling grid. The following chemical properties were determined: P, K + , Ca 2+ , Mg 2+ , Na + , S, Al 3+ , pH, H + Al, SB, t, T, V, m, OM, Na saturation index (SSI), remaining phosphorus (P-rem), and micronutrients (Zn, Fe, Mn, Cu and B). The data were analyzed with descriptive statistics, followed by principal component and cluster analyses. Geostatistics were used to check and quantify the degree of spatial dependence of properties, represented by principal components. The principal component analysis allowed a dimensional reduction of the problem, providing interpretable components, with little information loss. Despite the characte- ristic information loss of principal component analysis, the combination of this technique with geostatistical analysis was efficient for the quantification and determination of the structure of spatial dependence of soil fertility. In general, the availability of soil mineral nutrients was low and the levels of acidity and exchangeable Al were high.