Sirvi Autor "Bambi, G." järgi

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Comparison between different types of bedding materials for horses
(2018) Bambi, G.; Rossi, G.; Barbari, M.
The sports horse lives a large part of the time inside the pen in constant contact with the bedding. Therefore the bedding material can deeply affect the welfare and health of horses kept in pens. The materials have to ensure the realization of a double aim: to create a comforta ble and soft surface on which the animal can stand and relax; to give appropriate hygienic and sanitary conditions. Other important factors influence the choice, such as: the material must not be appetizing for the horse; the litter has to maintain a prope r level of moisture, so that the hoof is kept healthy, elastic and hydrated. Also the costs for material and litter management have to be taken into account. In the present study, different organic materials are compared: wood chips, hemp, rice, flax and c oconut. The trials took place in five box stalls, with square plan of 3 x 3 m. Environmental data were collected during the trials (air temperature and humidity, ammonia concentration, litter moisture). Management data were also collected, regarding the us e of bedding materials, working time, costs. In the paper the main results of the comparison between the different litter materials used in horses pens are presented.
Compost barn system and its influence on the environment, comfort and welfare of dairy cattle
(Estonian University of Life Sciences, 2023) Nepomuceno, G.L.; Cecchin, D.; Damasceno, F.A.; Amaral, P.I.S.; Caproni, V.R.; Rossi, G.; Bambi, G.; Ferraz, P.F.P.
The aim of this study was to evaluate the effect of the thermal environment on behavioral and physiological parameters of crossbred cows of different productivity levels confined in a compost barn system. For this, air temperature (Tdb) and relative humidity (RH) data were measured using sensors/registers and wind speed (Vair) was recorded with the aid of an anemometer. Subsequently, these data were used to calculate the Temperature and Humidity Index (THI). Bedding material variables (pH and humidity) were also evaluated. The animals were evaluated for physiological variables (respiratory rate – RR and surface temperature – ST), scores (body condition, locomotion and dirt) and behavior. The analyses were carried out on two groups of cows (Group 1: high production vs. Group 2: medium and low production). The average pH of the bedding material was 8.5, within the recommended range. In the case of the physiological responses of the cows, the respiratory rate (RR) of Group 1 indicated better conditions of thermal comfort in the morning vs. the afternoon. The system was efficient in both groups based on body condition score, indicating favorable conditions for the health of the animals. Regarding the behavioral evaluation, Group 1 and 2 were statistically similar and had the longest rumination times, in relation to the other evaluated behaviors. Regarding active periods, medium production were the most active. Regarding idle time, low production spent more time idle than the other animals.
Influence of coconut fiber incorporation on the mechanical behavior of adobe blocks
(Estonian University of Life Sciences, 2024) da Silva, N.A.; Cecchin, D.; Rocha, C.A.A.; Toledo Filho, R.D.; Pessin, J.; Rossi, G.; Bambi, G.; Conti, L.; Ferraz, P.F.P.
Adobe is an ancient construction technique, simple and low cost, still used in some parts of the world, mainly in rural areas. Normally, in these regions, a considerable amount of agricultural waste is generated that can be used for different purposes. An agricultural waste that has been increasingly studied in the construction sector is natural fibers. The addition of natural fibers in the soil matrix has been gaining prominence as it is a natural and easily accessible stabilizer. This work aimed to analyze and characterize adobe blocks reinforced with coconut fibers, with the addition of 1% and 2% compared to the reference block (without the addition of coconut fiber) through capillary absorption, fiber-soil adhesion, durability in the presence of water and mechanical, properties through of compression bending tests. The adobe blocks with the addition of fibers showed mechanical results above those required by the standard NBR 16814. The addition of fibers promoted higher capillary absorption results than the samples consisting only of soil and when exposed to drip erosion, no significant damage was observed in the adobe structure.
Life cycle assessment (LCA) in construction materials – Review
(Estonian University of Life Sciences, 2025) Carvalho, J.G.R.O.; Cecchin, D.; de Azevedo, A.R.G.; do Carmo, D.F.; Paes, J.L.; Ferraz, P.F.P.; Hamacher, L.S.; Costa, K.A.; Rossi, G.; Bambi, G.
The construction industry is one of the most impactful sectors in terms of natural resource consumption and greenhouse gas emissions, demanding more sustainable and efficient solutions. This study systematically reviews the applicatication of Life Cycle Assessment (LCA) to evaluate sustainable materials and practices within the construction sector, emphasizing the replacement of tradicional materials with recycled, bioeconomic, and low-carbon alternatives. A systematic review was conducted using the Scopus database, covering studies published between 2020 and September 2024. The methodology included the use of VOS viewer software to generate keyword co-occurrence maps, aiding in the identification of emerging trends and patterns. Key findings indicate substantial environmental benefits from incorporating industrial wastes, agricultural by-products, and bioeconomic materials, demonstrating substantial reductions in CO₂ emissions, energy consumption, and natural resource usage. The analysis also highlights emerging technologies, such as 3D printing and nanotechnology, as innovative tools that further enhance sustainability in construction. However, challenges persist, including limited availability of reliable regional data, methodological complexities, and gaps in integrating socio-economic variables into LCA analyses. This paper contributes to advancing sustainable construction by identifying critical gaps and challenges, proposing strategies for improved data collection, recommending enhanced interdisciplinary collaboration, and suggesting increased governmental support and regulatory frameworks to promote broader adoption of LCA in industry practices.
Measure of thermal transmittance of two different infill wall built with bamboo cultivated in Tuscany
(2019) Bambi, G.; Ferraz, P.F.P.; Ferraz, G.A.S.; Pellegrini, P.; Di Giovannantonio, H.
Bamboo is used in different scenarios of application, its physical and mechanical characteristics guarantee a high flexibility of use especially in the buildings constructions. The experience gained in civil constructions demonstrates that bamboo can be considered a sustainable material able to replace wood in many constructive elements with structural functions. The applications of bamboo aimed at carrying out structural functions are thoroughly studied. For this reason the present research focuses on the thermal insulation performance. To ensure an approach focused on the sustainability of potential exploitation, the research examined only local material coming from three bamboo fields located in the Tuscany region (Italy). The material harvested and suitably treated was utilized for the realization of two different kind of wall, undergone later to experimental tests in compliance with the ISO 9869 standard for the calculation of the transmittance values. The measure of transmittance enabled to know the characteristics of thermal conduction of bamboo walls. The first wall was made of cut throw longitudinal axis bamboo culms; the second one was made of cut throw longitudinal axis bamboo culms coated in internal face with a sustainable mortar. The test was carried out using insulating thermal box with internal temperature under control. The calculation of the transmittance in place was compared with the images captured by thermal camera. Thermal imagine allowed to highlight the behaviour of the material subjected to a thermal stress induced by the experimental test.
Poultry farming solutions for a sustainable development of marshlands areas of South Iraq
(2018) Rossi, G.; Conti, L.; Bambi, G.; Monti, M.; Barbari, M.
The Department of Agricultural, Food and Forestry Systems of University of Florence carried out cooperation projects in the South Iraq, funded by Italian Ministry of Foreign Affairs and International Coop eration, focused on the development of rural areas. All the proposed interventions were designed taking into account some key points, such as the development of sustainable farming systems, the protection of the environment, the empowerment of women role. Among the main activities, a particular importance is given to the simple solutions for poultry breeding that represents an important economic resource for many farmers and a source of food for a large segment of the population. Therefore the main aim of t he project was to define new building solutions to apply in the area of marshlands. A mobile poultry shelter was designed and built to meet the demand for meat and eggs from a typical rural family. This shelter was designed to be used for extensive breedin g, with animals free to graze outside during the day. A suitable self - building methodology was applied to obtain results from farmers without specific skills for wood construction thanks to which they learn the appropriate way to build poultry shelters. As conclusion, poultry breeding can be spread in the area of marshlands using the simple self - building structures presented in the study.
Spatial and temporal variability of productivity of coffee plants grown in an experimental field located in Três Pontas, Brazil
(Estonian University of Life Sciences, 2023) Santos, S.A.; Ferraz, G.A.S.; Figueiredo, V.C.; Volpato, M.M.L.; Matos, C.S.M.; Pereira, A.B.; Conti, L.; Bambi, G.; Marin, D.B.
The coffee grower seeks to increase productivity, as well as reduce the operating costs of his crop. Precision Agriculture (PA) is composed of a cycle of tools and technologies that can bring a good return to coffee growers, seeking to optimize production processes, bringing better yields and minimizing costs. Therefore, the objective of this research is to evaluate the spacetime behavior of productivity in a coffee plantation, aiming to apply AP techniques. The study was carried out in a coffee plantation of the species (Coffea arabica), cultivar Topázio MG1190, located in the municipality of Três Pontas, Brazil, with an area of 1.2 ha. With the aid of a GNSS RTK, 30 plants were georeferenced, from which their yields were later sampled in the years 2020, 2021 and 2022. The collected data were evaluated in two statistical processes in the RStudio software. The first stage consisted of a one-way analysis of variance with repeated measures, from the results it is concluded that there are differences between the production averages when buying the productivity of the years 2020, 2021 and 2022 and, in addition, the coefficient of variation for the three sets of samples was quite high (CV > 30%) indicating a heterogeneity between the data. The second stage consisted of a geostatistical analysis the data were fitted in a model and interpolated by ordinary kriging; the result was maps of spatial variability. Through these maps it was possible to evaluate the behavior of productivity spatially and temporally, as well as to quantify areas that had higher and lower levels of this attribute. It is concluded that productivity, even in the case of such a small productive area, can vary substantially in space and time, and the use of PA can help producers in decision making regarding management.
Spatial modeling of coffee tree height and diameter using LiDAR SLAM, RGB imagery, and field measurements
(Estonian University of Life Sciences, 2026) Rubio, S.V.; Ferraz, G.A.S.; Cardozo, E.J.S.; Zavala, E.H.; de Oliveira, F.M.; Bambi, G.; Sarri, D.; Reis, G.M.; Ferraz, P.F.P.
Remote sensing has become established as a promising tool for crop management. In coffee farming, estimating canopy height and diameter is essential to characterize plant vigor, development, and uniformity. This study compared three approaches to obtain these variables: field measurements, RGB (Red, Green, Blue) imagery acquired by a Remotely Piloted Aircraft (RPA), and a handheld Light Detection and Ranging sensor (LiDAR), using geostatistics to assess spatial accuracy and agreement among methods. From three-dimensional data, surface and terrain models were derived, enabling estimation of canopy height and diameter, while geostatistics was used to characterize the spatial structure, select variogram models via cross-validation, and generate continuous maps through ordinary kriging. In pointwise comparison with field data, LiDAR showed better performance for height (R² = 0.80) than the RGB orthomosaic (R² = 0.63). For canopy diameter, LiDAR was also superior (R² = 0.79) relative to RGB imagery (R² = 0.71). At the spatial level, the comparison between kriged maps indicated greater agreement between LiDAR and field data, especially for plant height (r = 0.99), whereas RGB and field data showed lower spatial correspondence (r = 0.44). For canopy diameter, the maps derived from LiDAR and RGB showed good agreement with field data, with r = 0.88 and r = 0.83, respectively. Thus, the combination of pointwise assessment and geostatistical analysis proved suitable for comparing the studied methods and for interpreting, in an integrated manner, the estimation and spatial distribution of coffee tree height and canopy diameter.
Spatial variability of chlorophyll and NDVI obtained by different sensors in an experimental coffee field
(Estonian University of Life Sciences, 2024) Silva, S.A.S.; Ferraz, G.A.S.; Figueiredo, V.C.; Volpato, M.M.L.; Machado, M.L.; Silva, V.A.; Matos, C.S.M.; Conti, L.; Bambi, G.
The objective of this research was to study the spatial variability of NDVI and chlorophyll sampled by different sensors, as well as to evaluate the correlation between them in a coffee field. The study was carried out on a coffee farm located in the municipality of Três Pontas, Minas Gerais. A sampling grid containing 30 points was created for the study area. Each sampling point was represented by one plant, which was georeferenced by a GNSS RTK. For each sample plant, NDVI and chlorophyll were obtained by the optical and active sensors GreenSeeker and ClorofiLOG, respectively. In addition, it was carried out a flight with an RPA equipped with a passive and multispectral sensor. Using the data obtained by active sensors, a geostatistical analysis was carried out to evaluate the spatial variability of NDVI and chlorophyll. The geostatistical analysis verified the existence of spatial dependence for the two attributes, and thus it was possible to generate spatialization maps through kriging. The images obtained by the passive sensor resulted in five multispectral orthomosaics, making it possible to calculate the NDVI, thus generating a spatialization map of this index. It was possible to observe in the generated maps, points that presented a certain similarity and for this purpose a correlation analysis was carried out for the values of each attribute, sampled directly in the maps, and in different sampling grids (30, 60, 90 and 120 points). By analyzing the Pearson coefficient (R) it was possible to quantify the level of correlation between the data obtained by the different sensors and through the t test it was possible to find significant correlations between them.
Spectral behavior of Macaúba palms (Acrocomia aculeata) under different lighting conditions and phenological stages
(Estonian University of Life Sciences, 2026) Santana, L.S.; Surmani, C.L.S.; Santos, L.G. Maciel dos; Lopes, M.D.S.; da Silva, J.M.; Evaristo, A.B.; Rossi, G.; Bambi, G.
Climate change events highlighted concerns about renewable energy consumption. The Macaúba palm (Acrocomia aculeata) stands out as a palm with high potential for energy production. However, it is still in the domestication phase as an agricultural crop. Thus, integrating technologies such as remote sensing to monitor plant characteristics can contribute to understanding this crop's development. In this context, the study aimed to evaluate the spectral behavior of Macaúba (Acrocomia aculeata) under various lighting conditions and at different phenological stages. Multispectral images were obtained using a Multispectral Remotely Piloted Aircraft (RPA), with flights conducted at 8:00 AM, 12:00 PM, and 4:00 PM, and during two seasonal periods (February and June 2025). The aim was to analyze the effects of solar variation and plant development on reflectance and spectral indices. The results showed a strong influence of illumination on the spectral response, with an 80% reduction in reflectance under shade, with the red band being the most sensitive. Multitemporal analysis revealed marked decreases in the TCARI (-83.7%), OSAVI2 (-80.8%), and TCARI/OSAVI (-15.9%) indices, accompanied by a decrease in photosynthetic pigments and the onset of leaf senescence during the dry season. Conversely, the NDRE (+10.1%) and CIgreen (+24.7%) indices increased, reflecting maintenance of photosynthetic activity and the emergence of new leaves. NDVI remained stable, indicating the conservation of canopy structure. Multispectral RPAs' potential for phenological and physiological monitoring of tropical palms, emphasizing the importance of temporal and geometric standardization of acquisitions to ensure radiometric consistency. Integrating spectral data with solar parameters is an effective strategy to enhance the sustainable management of Macaúba palms.
Temporal analysis of pasture vegetation cover in central-western Brazil using remote sensing
(Estonian University of Life Sciences, 2025) Moreira, A.N.H.; Ciappina, A.H.; Andrade, R.R.; Casaroli, D.; Rossi, G.; Conti, L.; Bambi, G.
Brazil is the world's leading exporter of beef, consolidating beef cattle farming as an important branch of national livestock farming. The expansion of livestock farming and agriculture in recent decades has resulted in a notable increase in pasture areas in Brazil. However, the country faces the growing challenge of pasture degradation, a problem that threatens sustainability and food production. On the other hand, livestock farming in Brazil's Central-West region, the country's largest cattle-producing area, particularly in the state of Goiás, can cause environmental damage when sustainable practices are disregarded. Thus, the objective of this article was to evaluate pasture degradation, at different levels, in the Ribeirão Serra Negra Watershed, in the municipality of Piracanjuba, Goiás, Brazil. Using images from the Sentinel-2A orbital sensor, the NDVI (Normalized Difference Vegetation Index) vegetation index and the vegetation cover classes of pastures were obtained between 2017 and 2021. During this period, the results showed that more than 98% of the areas had some level of degradation, with an average coverage of 6,586.1 ha. There was an upward evolution in the levels of vegetation cover between 2017 and 2019, with the best pasture conditions predominating in 2019. These assessments help identify areas that require greater attention and often necessitate conservation practices and management plans. In this context, monitoring degraded areas is a practice that facilitates the improvement of existing pastures, promotes the rational management of inputs, conserves natural resources, and aligns with development programs focused on sustainability.
Thermal analysis of cement panels with lignocellulosic materials for building
(2020) Ferraz, P.F.P.; Mendes, R.F.; Ferraz, G.A.S.; Carvalho, V.R.; Avelino, M.R.C.; Narciso, C.R.P.; Eugênio, T.M.C.; Cadavid, V.G.; Bambi, G.
The use of lignocellulosic material residue in cement composites can be considered as a good option because they allow good thermal behaviour. This paper aimed to compare three kinds of cement panels reinforced with different lignocellulosic materials (Coffee husk, Coconut shell, and Banana pseudostem) based on their thermal properties. To produce each panel, the methodology suggested by Souza (1994) was used. Six replicates of each lignocellulosic panel with dimensions of 7.0×7.5 were evaluated. The thermal analysis was performed in a chamber composed of MDP (medium density particleboard). The chamber contained the heat source (incandescent lamp) connected to a thermostat that maintained the temperature at 48.0 °C. The porosity and thickness of the panels and the thermal behaviour of each sample panel (thermal conductivity, resistivity, resistance, and transmittance) and the difference in temperature of both sides of the panel were evaluated. The temperature difference to stabilization was obtained after a sampling time of 200 minutes, with 1,000 readings of 12 s each. Although all the panels were submitted under the same temperature, the inner and external superficial temperatures of the coffee husk panels reached smaller values. Besides, coconut and banana pseudostem panels presented the best results of thermal transmittance and thermal resistance. Thus, coconut shell panels present the best thermal performance, which means that this panel might be an attractive alternative building material, in terms of heat insulation for indoor applications.
Three-dimensional reconstruction of the trunk volume of dairy cows using RGB-D images obtained by UAV for body mass prediction
(Estonian University of Life Sciences, 2026) Oliveira, F.M.; Ferraz, G.A.e.S.; Campos, L.L.; Reis, G.M.; Cecchin, D.; Becciolini, V.; Bambi, G.; Ferraz, P.F.P.
Accurate estimation of body mass (BM) in dairy cattle is essential for nutritional management, productivity monitoring, and animal welfare. In this context, three-dimensional (3D) morphometric descriptors derived from remote sensing technologies have emerged as promising alternatives to conventional weighing methods. This study proposes and evaluates a methodological framework for reconstructing the dorsal trunk volume of dairy cows using RGB-D data acquired by an unmanned aerial vehicle (UAV). Data were collected on a commercial dairy farm under a tie-stall system, with animals moving along a defined pathway after milking, enabling standardized overhead image acquisition. Top-view images were obtained using an Intel RealSense D435i depth camera mounted on a UAV platform (3DR Solo). Point clouds were generated and processed in CloudCompare, including dorsal surface segmentation, normal estimation, and volumetric mesh reconstruction using Poisson surface reconstruction. Only closed and geometrically consistent meshes were retained for analysis. The dataset comprised 25 dairy cows, resulting in 25 observations, with BM ranging from 500 to 750 kg, stratified into 50 kg intervals. Correlation analyses showed strong positive associations between reconstructed dorsal volume and BM, both globally (r = 0.979; ρ = 0.989) and across classes. A simple linear regression model, evaluated using a 70/30 train–test split and leave-one-out cross-validation, demonstrated high predictive performance (R² = 0.967 training; R² = 0.931 testing). These results confirm the technical feasibility and zootechnical relevance of UAV-based RGB-D acquisition combined with 3D reconstruction for non-invasive BM estimation in dairy cattle, highlighting its applicability in precision livestock farming systems.
Use of geostatistical analyses for wheat production areas throung the variables NDVI, surface temperature and yield
(Estonian University of Life Sciences, 2024) Abreu, A.L.; Ferraz, G.A.S.; Morais, R.; Bento, N.L.; Conti, L.; Bambi, G.; Ferraz, P.F.P.
Geostatistics is a crucial tool for data analysis in the field of precision agriculture, allowing the characterization of spatial variability magnitude, optimizing profitability and yield in agricultural areas. In this context, the present study aimed to evaluate the spatial dependence of the variables yield, Normalized Difference Vegetation Index (NDVI), and surface temperature in winter wheat plants. This was achieved through fitting semivariograms with different statistical models and interpolating the study variables using Ordinary kriging. The experiment was conducted at Fazenda Santa Helena, located in the municipality of Lavras in the state of Minas Gerais, Brazil, with a 12-hectare winter wheat crop of the TBIO Calibre variety. Data were collected using a grid sampling method at different stages of wheat plant growth (tillering and elongation). The analyzed variables included yield, NDVI, and surface temperature. Statistical analyses were performed using the R software. Initially, the spatial dependence of the study variables was analyzed by fitting semivariograms using the Restricted Maximum Likelihood (REML) method and considering spherical, exponential, and gaussian models. The evaluation of errors was carried out through cross-validation, and subsequently, the data interpolation was performed using ordinary kriging with the best-fitted semivariogram model. The results demonstrated a proper fit of semivariograms for the study models, with the spherical model standing out for surface temperature variables (elongation and tillering), NDVI (tillering), and the exponential model for NDVI (elongation) and yield. Therefore, the use of geostatistics is emphasized as an important tool to assist in precision agriculture management in winter wheat crops.

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