Tag Archives: geostatistics

982-1000 M.A.J.G. Silva, L.M.D. Santos, J.C.D. Ribeiro, M. Barbari, V. Becciolini, L.P. Naves1 and P.F.P. Ferraz
Spatial and temporal variability of enthalpy and its influence on the cloacal temperature of broilers
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Spatial and temporal variability of enthalpy and its influence on the cloacal temperature of broilers

M.A.J.G. Silva¹, L.M.D. Santos², J.C.D. Ribeiro¹, M. Barbari³, V. Becciolini³, L.P. Naves¹1 and P.F.P. Ferraz²*

¹Federal University of Lavras, Animal Science Department, Campus Universitário,
PO Box 3037, Lavras, Minas Gerais, Brazil
²Federal University of Lavras, Agricultural Engineering Departament, Campus Universitário, PO Box 3037, Lavras, Minas Gerais, Brazil
³University of Firenze, Department of Agricultural, Food, Environmental and Forestry Science, Via San Bonaventura, 13, Firenze, Italy
*Correspondence: patrícia.ponciano@ufla.br

Abstract:

Strategies aimed at mitigating heat stress conditions pose a challenge for the poultry industry operating in tropical climate zones. The primary aim of this research was to characterize and analyze the specific enthalpy of air (h, in kJ kg of dry air−1) in a broiler house using geostatistical techniques. In addition, its relationship with the cloacal temperature (tcloacal, °C) of the broilers was evaluated. The study was carried out in Lavras, Minas Gerais, Brazil. A total of 720 Cobb-500 broilers were raised from 1 to 42 days old. When the broilers were 7, 21, 35 and 42 days old, the dry bulb temperature (tdb, °C) and relative air humidity (RH, %) were recorded at 08:00 a.m. and 01:00 p.m. by seven sensors distributed throughout the installation, and tcloacal measured. Subsequently, h computed, and the data were examined through kriging interpolation. The tcloacal data were superimposed on the h maps of the facility. The spatial distribution of h inside the aviary (box) and temporal distribution (time and days) were characterized, and its variability was visualized. Tcloacal was directly related to the spatial as well temporal distribution of h, providing information about the thermal influence on production environment and the physiological responses of broilers.

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554-570 S.A.S. Silva, G.A.S. Ferraz, V.C. Figueiredo, M.M.L. Volpato, M.L. Machado, V.A. Silva, C.S.M. Matos, L. Conti and G. Bambi
Spatial variability of chlorophyll and NDVI obtained by different sensors in an experimental coffee field
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Spatial variability of chlorophyll and NDVI obtained by different sensors in an experimental coffee field

S.A.S. Silva¹, G.A.S. Ferraz¹*, V.C. Figueiredo², M.M.L. Volpato², M.L. Machado², V.A. Silva², C.S.M. Matos², L. Conti³ and G. Bambi³

¹Federal University of Lavras, School of Engineering, Department of Agricultural Engineering, Rotary Clover Professor Edmir Sá Santos, BR37200-900 Lavras, Brazil
²Agricultural Research Company of Minas Gerais, Av. José Cândido da Silveira 1647, Bairro União Belo Horizonte, BR31170-495 Belo Horizonte, Brazil
³University of Florence – UniFI, Department of Agriculture, Food, Environment and Forestry (DAGRI), Via San Bonaventura, 13, IT50145 Florence, Italy
* Correspondence: gabriel.ferraz@ufla.br

Abstract:

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.

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110-126 J.C. Ferreira, P.F.P Ferraz, G.A.S. Ferraz, F.M. Oliveira, V.G. Cadavid, G. Rossi and V. Becciolini
Spatial variability of methane and carbon dioxide gases in a Compost-Bedded Pack Barn system
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Spatial variability of methane and carbon dioxide gases in a Compost-Bedded Pack Barn system

J.C. Ferreira¹, P.F.P Ferraz¹*, G.A.S. Ferraz¹, F.M. Oliveira¹, V.G. Cadavid², G. Rossi³ and V. Becciolini³

¹Federal University of Lavras, Department of Agricultural Engineering, University Campus, PO Box 3037 - CEP 37200-000 Lavras, Minas Gerais, Brazil
²Universidad Nacional de Colombia, sede Medellín, Facultad de Ciencias Agrarias, Grupo de Investigación en Biodiversidad y Genética Molecular (BIOGEM). Carrera 65 #59A-110, postal code 050034 Medellín, Colombia
³University of Firenze, Department of Agriculture, Food, Environment and Forestry, 13 Via San Bonaventura, IT 50145 Firenze, Italy
*Correspondence: patricia.ponciano@ufla.br

Abstract:

The dairy sector significantly contributes to global food production, however, it is closely associated with environmental concerns, specifically the emission of greenhouse gases such as methane (CH4) and carbon dioxide (CO2). The research problem focuses on the environmental impact of livestock farming, particularly in relation to the emission of greenhouse gases (GHG) such as methane (CH4) and carbon dioxide (CO2). Therefore, the objective of this paper was to assess the spatial variability of CH4 and CO2, as well as the thermal environment through the Temperature and Humidity Index (THI) and of air velocity (V, m s-1) in a Compost Bedded Pack (CBP). The experiment was carried out in October 2023, in a commercial dairy cattle facility measuring 54×22×4.5 m (length×width×height) that housed 80 lactating cows. Measurements were collected at 75 points, 0.25 m above the bedding, for one minute in each point. To characterize the distribution of gases and the thermal environment, the data were underwent geostatistical techniques and kriging maps. THI values ranged from 72.4 to 78.4, categorizing the animals into two environments within the facility, comfort and alert to thermal conditions. The maximum recorded for CO2 was 713.60 ppm in the region with a low ventilation incidence. CH4 reached a ranging from 103.38 to 196.73 ppm in areas with low ventilation and higher temperatures. The use of geostatistics enabled the characterization of spatial variability of greenhouse gases CH4 and CO2, as well as THI and V. Analyzing these variables is crucial for implementing mitigation actions and developing an increasingly sustainable production system.

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1423-1435 L. M. dos Santos, G.A.S. Ferraz, H.J.P. Alves, J.D.P. Rodrigues, S. Camiciottoli, L. Conti and G. Rossi
Comparison of spatial-temporal analysis modelling with purely spatial analysis modelling using temperature data obtained by remote sensing
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Comparison of spatial-temporal analysis modelling with purely spatial analysis modelling using temperature data obtained by remote sensing

L. M. dos Santos¹*, G.A.S. Ferraz¹, H.J.P. Alves², J.D.P. Rodrigues³, S. Camiciottoli⁴, L. Conti⁴ and G. Rossi⁴

¹Federal University of Lavras, Department of Agricultural Engineering, University Campus, BR37.200-000 Lavras-MG, Brazil
²Institute of Applied Economic Research- IPEA, Rio de Janeiro, BR 20071-900
Rio de Janeiro, Brazil
³Geoprocessing Analyst, Bracell, Lençois Paulistas, BR17120-000 São Paulo, Brazil
⁴University of Firenze, Department of Agriculture, Food, Environment and Forestry, Via San Bonaventura, 13, Firenze, Italy
*Correspondence: luanna_mendess@yahoo.com.br

Abstract:

Variations in climatic elements directly affect the productivity of agricultural activities. Temperature is one of the climatic elements that varies in space and time. Therefore, understanding spatial variations in temperature is essential for many activities. Given the above, the objective of this work was to compare the performance of the proposed spatiotemporal analysis model with that of purely spatial analysis using temperature data obtained by remote sensing. The experimental data were arranged in a grid with 403 spatial locations, with 22 samples collected in a 24-hour period. The statistical software R Core Team (2020) was used to perform the analysis. The packages used in the analyses were ‘geoR’, ‘CompRandFld’, ‘scatterplot3d’, and ‘fields’. For making the maps, the software ArcGIS was used. The behavioural analysis of spatiotemporal dependence indicated, through the covariogram graph of the data, that there is a strong spatial dependence. For the cases of purely spatial analysis of phenomena, a separate spatial model for each time is justified because this type of model presents a smaller prediction error and requires simpler processing than the space-time model. It was possible to compare the space-time analysis with the purely spatial analysis using temperature data obtained by remote sensing images. The data modelled with the purely spatial analysis had, on average, lower error than those with the space-time model.

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783–796 C.E.A. Oliveira, F.A. Damasceno, P.F.P. Ferraz, J.A.C. Nascimento, G.A.S. Ferraz and M. Barbari
Geostatistics applied to evaluation of thermal conditions and noise in compost dairy barns with different ventilation systems
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Geostatistics applied to evaluation of thermal conditions and noise in compost dairy barns with different ventilation systems

C.E.A. Oliveira¹, F.A. Damasceno¹*, P.F.P. Ferraz¹, J.A.C. Nascimento¹, G.A.S. Ferraz¹ and M. Barbari²

¹Federal University of Lavras, Engineering Department, BR37200-000, Lavras - Minas Gerais, Brazil
²University of Florence, Department of Agriculture, Food, Environment and Forestry, Via San Bonaventura, 13, IT50145 Firenze, Italy
*Correspondence: flavio.damasceno@deg.ufla.br

Abstract:

The objective of this work was to evaluate the spatial distribution of thermal conditions and bed variables in compost dairy barns with different ventilation systems, through the technique of geostatistics. The experiment was conducted in April 2017, in farms located in Madre de Deus, Minas Gerais, Brazil. Three facilities were evaluated with different ventilation systems: natural (NV); mechanical of low volume and high speed (LVHS); and mechanical of high volume and low speed (HVLS). The interior of the premises was divided into 40 meshes equidistant points, in which air temperature, relative humidity and air speed were manually collected. Geostatistics technique was used to assess the spatial dependence of the variables. The results showed the occurrence of dependence and spatial variability of the variables evaluated. Based on thermal comfort indexes, it was concluded that dairy cows were under stress conditions during the hottest hours of the day in the three animal facilities evaluated. The results obtained allow us to understand that the thermal environment is more influenced by the ventilation system adopted.

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385–395 F.A. Damasceno, C.E.A Oliveira, G.A.S Ferraz, J.A.C Nascimento, M Barbari and P.F.P Ferraz
Spatial distribution of thermal variables, acoustics and lighting in compost dairy barn with climate control system
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Spatial distribution of thermal variables, acoustics and lighting in compost dairy barn with climate control system

F.A. Damasceno¹*, C.E.A Oliveira¹, G.A.S Ferraz¹, J.A.C Nascimento¹, M Barbari² and P.F.P Ferraz¹

¹Federal University of Lavras, Engineering Department, BR37200-000 Lavras, Minas Gerais, Brazil
²University of Florence, Department of Agriculture, Food, Environment and Forestry, Via San Bonaventura, 13, IT50145 Firenze, Italy
*Correspondence: flavio.damasceno@deg.ufla.br

Abstract:

The main objective of this research was to evaluate the spatial distribution of the thermal variables, acoustics and lighting in climate controlled compost dairy barn. The experiment was conducted in October 2017, in a farm located in the west of Minas Gerais state, Brazil. For the study, the interior of the animal facility was divided into 120 meshes equidistant points, in which air temperature (tdb), relative humidity (RH), noise, illuminance, and air speed (Vair) were manually collected. The technique of geostatistics was used to evaluate the distribution and spatial dependence of variables. Spatial distribution maps showed the occurrence of high variability of attributes and content within the animal facility. Thermal environment variables showed alert situations throughout practically the entire facility. The noise and luminance levels were within the recommended values.

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1630–1638 G.A.S. Ferraz, R.C. Avelar, N.L. Bento, F.R. Souza, P.F.P. Ferraz, F.A. Damasceno and M. Barbari
Spatial variability of soil fertility attributes and productivity in a coffee crop farm
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Spatial variability of soil fertility attributes and productivity in a coffee crop farm

G.A.S. Ferraz¹*, R.C. Avelar², N.L. Bento¹, F.R. Souza³, P.F.P. Ferraz¹, F.A. Damasceno¹ and M. Barbari⁴

¹Federal University of Lavras – UFLA, Departament of Agricultural Engineering, University Campus, Postal Code 37200-000 Lavras-MG, Brazil
²AVELAR ASSESSORIA LTDA - Consultoria em Cafeicultura – Monte Carmelo – MG, Brazil
³Rural University of Rio de Janeiro – UFRJ, BR-465, Km 7, Postal Code 23.897000 Seropédica-RJ, Brazil
⁴Department of Agriculture, Food, Environment and Forestry (DAGRI), Università degli Studi di Firenze, Via San Bonaventura, 13, IT50145 Firenze, Itália
*Correspondence: gabriel.ferraz@ufla.br

Abstract:

Coffee cultivation is of great importance to Brazilian agribusiness, as coffee occupies extensive production areas and is one of the most exported Brazilian products. To maintain coffee production numbers, productive techniques must be adopted that optimize productive system use. The objective of this work was to apply geostatistical techniques in the evaluation of soil fertility attributes to construct maps of variability in soil fertility parameters and the productivity of a coffee crop in the municipality of Monte Carmelo, Minas Gerais (MG), Brazil. The work was developed with coffee of the cultivar Mundo Novo 379/19, and 19 sample points were georeferenced in Universal Transverse Mercator coordinates. Spatial dependence of the fertility and productivity parameters was analysed via classic semivariogram fitting and interpolation by ordinary kriging using the statistical computer system, R. All parameters evaluated showed high degrees of spatial dependence. The attribute values varied along the sampling points, except for the sodium (Na) contents, which had similar values in all samplings. The studied parameters ranged from 80 to 200 metres. It is conclusion, the use of productivity maps linked to soil chemical attributes can be useful for determining the occurrence of variable productivity rates throughout the area, allowing the adoption of corrective practices for subsequent crops and thus making the maps very useful tools for producers.

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408–417 P.F.P. Ferraz, G.A.S. Ferraz, L. Schiassi, V.H.B. Nogueira, M. Barbari and F.A. Damasceno
Spatial variability of litter temperature, relative air humidity and skin temperature of chicks in a commercial broiler house
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Spatial variability of litter temperature, relative air humidity and skin temperature of chicks in a commercial broiler house

P.F.P. Ferraz¹*, G.A.S. Ferraz¹, L. Schiassi¹, V.H.B. Nogueira¹, M. Barbari² and F.A. Damasceno¹

¹Federal University of Lavras, Agricultural Engineering Departament, Campus Universitário, PO Box 3037, Lavras, Minas Gerais, Brazil
²University of Firenze, Department of Agriculture, Food, Environment and Forestry, Via San Bonaventura, 13, IT50145 Firenze, Italy
*Correspondence: patricia.ponciano@ufla.br

Abstract:

The thermal environment inside a broiler house has a great influence on animal welfare and productivity during the production phase. Among the importance of the chicken litter is the function of absorbing moisture, provide thermal insulation and provide a soft surface for broilers. The skin temperature is an important physiological parameter to quantify the thermal comfort of animals, its variations may occur as a function of thermal variables. So, the aim of this work was to analyse the magnitude and spatial variability of chicken litter temperature and relative humidity of the air and to correlate them with the spatial distribution of chicks’ skin surface temperature throughout the broiler house during the 7th, 14th and 21st days of the chicks’ life, using geostatistical techniques. The experiment was performed in a commercial broiler house located in the western mesoregion of Minas Gerais, Brazil, where 28,000 male Cobb chicks were housed. The heating system consisted of an industrial indirect-fired biomass furnace. The heated air was inflated by an AC motor, 2,206 W of power, 1,725 RPM. Geostatistical techniques were used through semivariogram analysis and isochore maps were generated through data interpolation by kriging. The semivariogram was fitted by the restricted maximum likelihood method. The used mathematical model was the spherical one. After fitting the semivariograms, the data were interpolated by ordinary kriging. The semivariograms along with the isochore maps allowed identifying the non-uniformity of spatial distribution of the broiler litter temperature throughout the broiler house for 3 days of chicks’ life. It was observed that skin surface presented a positive correlation with the litter temperature and a negative correlation with the air humidity. The semivariograms along with the isochore maps allowed identifying the non-uniformity of spatial distribution of the litter temperature, air humidity and skin temperature of chicks throughout the broiler aviary for the three days. In addition, the use of geostatistics and distribution maps made possible to identify different environmental conditions in regions inside the broiler house that may harm the development of chicks.

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