Relação Entre Atributos Físicos E Químicos Dos Solos E a Produtividade De Capim Dourado Na Região Do Jalapão, To

Santana, Hugo; Sano, Edson Eyji; Júnior, Manuel Pereira de Oliveira; Lacerda, Marilusa Pinto Coelho; Malaquias, Juaci Vitória

doi:10.1590/01000683rbcs20140364

Cited by 4 publications

(4 citation statements)

References 20 publications

(5 reference statements)

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“…Araújo et al (2014) Tanto a área de Mata Nativa quanto a área de Pousio apresentaram valores baixos de RMSE e MAE, indicando melhor desempenho de estimativa do modelo de semivariograma escolhido (Uniyal, et al, 2021). Em relação ao índice de concordância de Willmott, foram observados altos valores tanto nos atributos estudados na área de Mata Nativa quanto na área de Pousio, indicando boa concordância dos valores obtidos (Santana, et al, 2015). A dependência espacial das famílias está descrita na Tabela 3.…”

Section: Resultsunclassified

Relação entre a entomofauna edáfica e atributos físicos do solo através de análise multivariada e geoestatística

Santos

Sacramento

Pires

et al. 2022

RSD

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Este estudo objetivou avaliar a influência que os atributos físicos do solo podem exercer sobre a entomofauna edáfica, considerando uma área de Pousio e outra de Mata Nativa, coletando-se amostras de solo nas profundidades 0 – 20 cm e 20 – 40 cm, totalizando 49 amostras por profundidade, totalizando 98 amostras por área, avaliando-se: densidade do solo (DS), macroporosidade (MAC), microporosidade (MIC), porosidade total (PT), umidade gravimétrica (UG) e volumétrica (UV) e resistência à penetração do solo (RPS), com coleta da entomofauna em cada ponto amostral. Coletou-se 3.098 insetos, apresentando maior número de indivíduos a família Formicidae e, maior número de famílias a ordem Coleóptera. Na Análise de Componentes Principais encontrou-se relação das famílias Staphylinidae, Cleridae, Scarabaeidae, Bostrichidae, Culicidae, Blattidae, Scolytidae e Termitidae à PT e UG na área de Mata Nativa. Na área de Pousio, Staphylinidae, Curculionidae, Tenebrionidae, Scarabaeidae e Blattidae apresentaram maior proximidade com UV, UG, MAC e PT. Na análise geoestatística os modelos de semivariogramas matern, esférico, gaussiano, exponencial e cúbico foram ajustados aos atributos de solo. Na fauna edáfica, ajustaram-se os modelos de covariogramas circular, exponencial, cúbico, esférico e gaussiano. Os resultados indicam a importância das características físicas do solo, que interferem no estabelecimento da entomofauna edáfica.

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Section: Resultsunclassified

Relação entre a entomofauna edáfica e atributos físicos do solo através de análise multivariada e geoestatística

Santos

Sacramento

Pires

et al. 2022

RSD

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“…Therefore, multicollinearity was assessed by Pearson's linear correlation coefficient and variance inflation factor (VIF). With these procedures, the four regression assumptions (linearity, error independence, error normality, and equality of variance) were evaluated (Santana et al, 2015).…”

Section: Methodsmentioning

confidence: 99%

Macauba production estimated by regression models

Malaquias¹,

Conceição²,

Braga³

et al. 2019

Científica

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Macauba has been shown to be the most promising native species for oil and biomass production. The first commercial crops have arisen mainly in Minas Gerais State, and estimates indicate a vegetable oil yield potential above 8 t ha-1. In this context, research has acted strongly on technological advance for improvements in the production system and selection of superior genotypes, which requires the use of precise and less expensive methodologies. Thus, we built prediction models to estimate the weight of macauba bunches using easy-to-measure physical variables. Bunches of plants from five regions of Brazil were evaluated. The bunches were weighed, and length and diameter were measured along with four other variables. Based on the set of variables obtained, stepwise multiple regression analysis was used to build regression models for each region. The correlation between observed versus estimated data reached determination coefficients (R 2) above 0.90 in three of the models built. The main variables selected by the best models were bunch volume, bunch length/diameter ratio, and bunch square diameter.

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“…The study area is located in a tropical climate zone, with temperatures ranging from 22 °C to 27 °C, in two seasons, one wet, from October to March, with an average precipitation of more than 1500 mm, and one dry season, from April to September [18]. The region is marked by sandy and nutrientpoor soils, which have limited the development of agriculture [42]; in its place, cattle ranching and The study area is located in a tropical climate zone, with temperatures ranging from 22 • C to 27 • C, in two seasons, one wet, from October to March, with an average precipitation of more than 1500 mm, and one dry season, from April to September [18]. The region is marked by sandy and nutrient-poor soils, which have limited the development of agriculture [42]; in its place, cattle ranching and sale of handcraft made from Syngonanthus nitens (Bong.)…”

Section: Study Areamentioning

confidence: 99%

“…The region is marked by sandy and nutrientpoor soils, which have limited the development of agriculture [42]; in its place, cattle ranching and The study area is located in a tropical climate zone, with temperatures ranging from 22 • C to 27 • C, in two seasons, one wet, from October to March, with an average precipitation of more than 1500 mm, and one dry season, from April to September [18]. The region is marked by sandy and nutrient-poor soils, which have limited the development of agriculture [42]; in its place, cattle ranching and sale of handcraft made from Syngonanthus nitens (Bong.) Ruhland (Eriocaulaceae), locally known as "golden grass", are the main economic activities [43].…”

Section: Study Areamentioning

confidence: 99%

Fire Recurrence and Normalized Difference Vegetation Index (NDVI) Dynamics in Brazilian Savanna

Santana

2018

Fire

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Fire is one of the main modeling agents of savanna ecosystems, affecting their distribution, physiognomy and species diversity. Changes in the natural fire regime on savannas cause disturbances in the structural characteristics of vegetation. Theses disturbances can be effectively monitored by time series of remote sensing data in different terrestrial ecosystems such as savannas. This study used trend analysis in NDVI (Normalized Difference Vegetation Index)-MODIS (Moderate Resolution Imaging Spectroradiometer) time series to evaluate the influence of different fire recurrences on vegetation phenology of the Brazilian savanna in the period from 2001 to 2016. The trend analysis indicated several factors responsible for changes in vegetation: (a) The absence of fire in savanna phytophysiognomies causes a constant increase in MODIS-NDVI, ranging from 0.001 to 0.002 per year, the moderate presence of fire in these areas does not cause significant changes, while the high recurrence results in decreases of MODIS-NDVI, ranging from −0.002 to −0.008 per year; (b) Forest areas showed a high decrease in NDVI, reaching up to −0.009 MODIS-NDVI per year, but not related to fire recurrence, indicating the high degradation of these phytophysiognomies; (c) Changes in vegetation are highly connected to the protection status of the area, such as areas of integral protection or sustainable use, and consequently their conservation status. Areas with greater vegetation conservation had more than 70% of positive changes in pixels with significant tendencies. Absence or presence of fire are the main agents of vegetation change in areas with lower anthropic influence. These results reinforce the need for a suitable fire management policy for the different types of Cerrado phytophysiognomies, in addition to highlighting the efficiency of remote sensing time series for evaluation of vegetation phenology.

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Relação Entre Atributos Físicos E Químicos Dos Solos E a Produtividade De Capim Dourado Na Região Do Jalapão, To

Cited by 4 publications

References 20 publications

Relação entre a entomofauna edáfica e atributos físicos do solo através de análise multivariada e geoestatística

Relação entre a entomofauna edáfica e atributos físicos do solo através de análise multivariada e geoestatística

Macauba production estimated by regression models

Fire Recurrence and Normalized Difference Vegetation Index (NDVI) Dynamics in Brazilian Savanna

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