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  1. AU="Helio Garcia Leite"
  2. AU="Chang, Yi-Yao"
  3. AU="Ren, Xiangzhong"
  4. AU="Ha, Van Thi Cam"
  5. AU="Zheng, Jinhong"
  6. AU="Tomatis-Souverbielle, Cristiana"
  7. AU="Al-Jumaily, Adel A"
  8. AU="Marallo, Carmine"
  9. AU="Alshammari, Afraj"
  10. AU="Min, Dong-Joon"
  11. AU=Fattorini Daniele AU=Fattorini Daniele
  12. AU="Lou, L X"
  13. AU="Yadollah Haji-Heydari"
  14. AU="Placidi, A"
  15. AU="Olivé, Claudia"
  16. AU="Türk, Y"
  17. AU="Brosnan, Hannah"
  18. AU="Hardy, Rowan S"
  19. AU="Demirci, Yılmaz Mehmet"
  20. AU="Dlugosz, Andrzej A"

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  1. Artikel ; Online: Classifying the risk of forest loss in the Peruvian amazon rainforest

    Gianmarco Goycochea Casas / Juan Rodrigo Baselly-Villanueva / Mathaus Messias Coimbra Limeira / Carlos Moreira Miquelino Eleto Torres / Hélio Garcia Leite

    Trees, Forests and People, Vol 14, Iss , Pp 100440- (2023)

    An alternative approach for sustainable forest management using artificial intelligence

    2023  

    Abstract: Peruvian Amazonian rainforests are constantly threatened by forest loss. Understanding changes in forest cover and assessing the level of risk is a permanent concern for numerous scientists and forest authorities. There are many conservation programs for ...

    Abstract Peruvian Amazonian rainforests are constantly threatened by forest loss. Understanding changes in forest cover and assessing the level of risk is a permanent concern for numerous scientists and forest authorities. There are many conservation programs for Peruvian forests that involve collaborative efforts and employ diverse methodologies for forest monitoring. In this study, we propose an alternative approach to decision-making for forest preservation, aiming to classify the risk of forest loss in districts within the Peruvian Amazon rainforest. This classification enables sustainable forest management. To accomplish this, we utilized unsupervised learning artificial intelligence through Kohonen's neural network. The network was trained using a historical database spanning from 2001 to 2021, which includes variables such as forest cover and loss, climate, topography, hydrographic networks, and timber forest concessions. Through this approach, the network successfully established five clusters. Following preliminary analysis, we designated these clusters as: low, medium, high, very high, and extremely high risk of forest loss. Kohonen networks demonstrated their effectiveness in clustering forest loss and forest cover. The results indicate a shifting trend among the classes over time, with an increase in the categories exhibiting high and very high risk of forest cover loss. This study provides valuable information for decision-making in the prevention and conservation of Peruvian forests. We strongly recommend maintaining vigilance, particularly in districts classified as a very high or extremely high risk of losing forest cover.
    Schlagwörter Kohonen neural network ; Forest conservation ; Forest prevention ; Risk classification ; Forestry ; SD1-669.5 ; Plant ecology ; QK900-989
    Thema/Rubrik (Code) 333 ; 910
    Sprache Englisch
    Erscheinungsdatum 2023-12-01T00:00:00Z
    Verlag Elsevier
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  2. Artikel ; Online: Automatic Detection and Counting of Stacked Eucalypt Timber Using the YOLOv8 Model

    Gianmarco Goycochea Casas / Zool Hilmi Ismail / Mathaus Messias Coimbra Limeira / Antonilmar Araújo Lopes da Silva / Helio Garcia Leite

    Forests, Vol 14, Iss 12, p

    2023  Band 2369

    Abstract: The objective of this project was to automate the detection and counting process of stacked eucalypt (hybrid Eucalyptus urophylla x Eucalyptus grandis ) timber in the forestry industry using the YOLOv8 model. The dataset consists of 230 diverse images of ...

    Abstract The objective of this project was to automate the detection and counting process of stacked eucalypt (hybrid Eucalyptus urophylla x Eucalyptus grandis ) timber in the forestry industry using the YOLOv8 model. The dataset consists of 230 diverse images of eucalypt roundwood, including images of roundwood separated on a rail and stacked timber. The annotations were made using LabelImg, ensuring accurate delineation of target objects on the log surfaces. The YOLOv8 model is customized with a CSPDarknet53 backbone, C2f module, and SPPF layer for efficient computation. The model was trained using an AdamW optimizer and implemented using Ultralytics YOLOv8.0.137, Python-3.10.12, and torch-2.0.1 + cu118 with CUDA support on NVIDIA T1000 (4096MiB). For model evaluation, the precision, recall, and mean Average Precision at a 50% confidence threshold (mAP50) were calculated. The best results were achieved at epoch 261, with a precision of 0.814, recall of 0.812, and mAP50 of 0.844 on the training set and a precision of 0.778, recall of 0.798, and mAP50 of 0.839 on the validation set. The model’s generalization was tested on separate images, demonstrating robust detection and accurate counting. The model effectively identified roundwood that was widely spaced, scattered, and overlapping. However, when applied to stacked timber, the automatic counting was not very accurate, especially when using images. In contrast, when using video, the relative percentage error for automatic counting significantly decreased to −12.442%. In conclusion, video proved to be more effective than images for counting stacked timber, while photographs should be reserved for the counting of individual roundwood pieces.
    Schlagwörter computer vision ; deep learning ; object detection ; forestry industry ; automated counting ; Plant ecology ; QK900-989
    Thema/Rubrik (Code) 690
    Sprache Englisch
    Erscheinungsdatum 2023-12-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  3. Artikel ; Online: Configuration of the Deep Neural Network Hyperparameters for the Hypsometric Modeling of the Guazuma crinita Mart. in the Peruvian Amazon

    Gianmarco Goycochea Casas / Duberlí Geomar Elera Gonzáles / Juan Rodrigo Baselly Villanueva / Leonardo Pereira Fardin / Hélio Garcia Leite

    Forests, Vol 13, Iss 697, p

    2022  Band 697

    Abstract: The Guazuma crinita Mart. is a dominant species of great economic importance for the inhabitants of the Peruvian Amazon, standing out for its rapid growth and being harvested at an early age. Understanding its vertical growth is a challenge that ... ...

    Abstract The Guazuma crinita Mart. is a dominant species of great economic importance for the inhabitants of the Peruvian Amazon, standing out for its rapid growth and being harvested at an early age. Understanding its vertical growth is a challenge that researchers have continued to study using different hypsometric modeling techniques. Currently, machine learning techniques, especially artificial neural networks, have revolutionized modeling for forest management, obtaining more accurate predictions; it is because we understand that it is of the utmost importance to adapt, evaluate and apply these methods in this species for large areas. The objective of this study was to build and evaluate the efficiency of the use of a deep neural network for the prediction of the total height of Guazuma crinita Mart. from a large-scale continuous forest inventory. To do this, we explore different configurations of the hidden layer hyperparameters and define the variables according to the function HT = f (x) where HT is the total height as the output variable and x is the input variable(s). Under this criterion, we established three HT relationships: based on the diameter at breast height (DBH), (i) HT = f (DBH); based on DBH and Age, (ii) HT = f (DBH, Age) and based on DBH, Age and Agroclimatic variables, (iii) HT = f (DBH, Age, Agroclimatology), respectively. In total, 24 different configuration models were established for each function, concluding that the deep artificial neural network technique presents a satisfactory performance for the predictions of the total height of Guazuma crinita Mart. for modeling large areas, being the function based on DBH, Age and agroclimatic variables, with a performance validation of RMSE = 0.70, MAE = 0.50, bias% = −0.09 and VAR = 0.49, showed better accuracy than the others.
    Schlagwörter deep learning ; artificial neural network ; total height ; forest management ; Plant ecology ; QK900-989
    Thema/Rubrik (Code) 006
    Sprache Englisch
    Erscheinungsdatum 2022-04-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  4. Artikel ; Online: Growth and Yield of Schizolobium parahyba var. amazonicum According to Soil Management in Agroforestry Systems

    Agust Sales / Sílvio Nolasco de Oliveira Neto / Haroldo Nogueira de Paiva / Helio Garcia Leite / Marco Antonio Siviero / Sabrina Benmuyal Vieira

    Diversity, Vol 13, Iss 511, p

    A Case Study in the Brazilian Amazon

    2021  Band 511

    Abstract: Studies on applying of soil management practices in the management of paricá and the effects on growth and yield are essential to auxiliary its cultivation and would allow us to inform management and conservation decisions to reconciliate biodiversity, ... ...

    Abstract Studies on applying of soil management practices in the management of paricá and the effects on growth and yield are essential to auxiliary its cultivation and would allow us to inform management and conservation decisions to reconciliate biodiversity, wellbeing, and sustainable production. This case study aimed to evaluate the growth and yield of paricá at different soil management practices, including consortium with an agricultural production, in the Brazilian Amazon. Paricá was implanted, consorted with soybean in the first year, and maize in the second, in a 5 × 2 m spacing. The treatments T1 = subsoiling, basal dressing, top-dressing, inoculation of microorganisms and consortium with soybean/maize were applied. In T2, T3, T4, and T5, we applied the same practices of T1, except subsoiling (T2), basal dressing (T3), top-dressing (T4) and inoculation of microorganisms (T5). T6 was the control, which used none of these practices, including the consortium with soybean/maize. The results indicate that the highest rate of plant survival occurred in T2, while T3 and T4 promoted greater intraspecific competition, compromising the growth in dbh and the yield (m 3 ha −1 ) of plants in future ages. Growth in dbh and th and the yield of plants in the soybean/maize consortium period was higher in T2 and T6. In future ages, the dbh and yield of plants demonstrated higher growth trends in T6, T1, and T5. Agroforestry practices of soil management influence the growth and yield of paricá plants. However, there is a tendency for greater growth and yield for paricá plants cultivated in the absence of agroforestry practices for soil management proposed in this case study. When opting for AFS (paricá intercropped with soybean and maize), it is recommended for paricá a subsoiling, fertilization, and inoculation of microorganisms.
    Schlagwörter forest fertilization ; forest modeling ; inoculation of microorganisms ; paricá ; soil preparation ; taungya system ; Biology (General) ; QH301-705.5
    Thema/Rubrik (Code) 630
    Sprache Englisch
    Erscheinungsdatum 2021-10-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  5. Artikel ; Online: Wood density estimation using dendrometric and edaphoclimatic data in artificial neural networks

    Mauro Antônio Pereira Werneburg / Mayra Luiza Marques da Silva / Helio Garcia Leite / Antonilmar Araújo Lopes da Silva / José Marinaldo Gleriani / Jeferson Pereira Martins Silva / Tais Rizzo Moreira / Sofia Maria Gonçalves Rocha / Nívea Maria Mafra Rodrigues

    Revista de Ciências Agroveterinárias, Vol 22, Iss

    2023  Band 4

    Abstract: Forestry measurement is aimed at volumetric production of wood; however, for the pulp processing industry, the main interest is productivity in wood biomass and, to know this variable, it is necessary to determine the basic wood density (BWD) beforehand. ...

    Abstract Forestry measurement is aimed at volumetric production of wood; however, for the pulp processing industry, the main interest is productivity in wood biomass and, to know this variable, it is necessary to determine the basic wood density (BWD) beforehand. Artificial neural networks (ANN) have been used in the forestry sector quite successfully to describe the dynamics of forest characteristics, such as estimating wood volume. In this context, the objective of this study was to assess the accuracy of the basic wood density estimates by means of ANN’s with Continuous Forest Inventory (CFI) and edaphoclimatic input variables. The database consisted of 3,797 data, from permanent plots of the CFI conducted in Eucalyptus sp stands and edaphoclimatic data from the planting sites. The five best ANNs were selected and the analysis of the estimates was carried out through the correlation between the estimated and BWD, the relative root mean square error (RMSE%) and graphical information. It was observed that both the CFI, edaphoclimatic information and the combination of both are potential and present similar results for the basic wood density estimate, and the errors associated with the estimates are between 3.9% to 3.5%. The ANNs based only on the CFI information presented higher RMSE. The use of ANN’s is feasible for estimating BWD and allows for excellent accuracy statistics.
    Schlagwörter Artificial intelligence ; Modeling ; Wood quality ; Agriculture ; S ; Agriculture (General) ; S1-972 ; Veterinary medicine ; SF600-1100
    Thema/Rubrik (Code) 550
    Sprache Englisch
    Erscheinungsdatum 2023-12-01T00:00:00Z
    Verlag Universidade do Estado de Santa Catarina
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  6. Artikel ; Online: Growth and yield of teak stands at different spacing

    Reginaldo Antonio Medeiros / Haroldo Nogueira de Paiva / Flávio Siqueira D’Ávila / Helio Garcia Leite

    Pesquisa Agropecuária Brasileira, Vol 53, Iss 10, Pp 1109-

    2018  Band 1118

    Abstract: Abstract: The objective of this work was to evaluate the growth and yield of teak (Tectona grandis) stands at different spacing and in different soil classes. Twelve spacing were evaluated in an Inceptisol and Oxisol, in plots with an area of 1,505 or 1, ... ...

    Abstract Abstract: The objective of this work was to evaluate the growth and yield of teak (Tectona grandis) stands at different spacing and in different soil classes. Twelve spacing were evaluated in an Inceptisol and Oxisol, in plots with an area of 1,505 or 1,548 m2, arranged in a completely randomized design with nine replicates. The teak trees were measured at 26, 42, 50, and 78 months of age. Total tree height was less affected by spacing. Mean square diameter was greater in wider spacing, whereas basal area and total volume with bark were greater in closer spacing. An increase in volume with bark per tree was observed with the increase of useful area per plant. For teak trees, growth stagnation happens earlier, the growth rate is higher in closer spacing, and the plants grow more in the Inceptisol than in the Oxisol.
    Schlagwörter Tectona grandis ; initial spacing ; modeling ; Agriculture (General) ; S1-972
    Sprache Englisch
    Erscheinungsdatum 2018-10-01T00:00:00Z
    Verlag Embrapa Informação Tecnológica
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  7. Artikel ; Online: Equações para estimar área foliar de folíolos de Acrocomia aculeta

    Clenilso Sehnen Mota / Helio Garcia Leite / Marco Antonio Oliva Cano

    Pesquisa Florestal Brasileira, Vol 34, Iss 79, Pp 217-

    2014  Band 224

    Abstract: O objetivo desse estudo foi desenvolver um modelo estatístico empírico, para estimar a superfície foliar, por um método não destrutivo, de folíolos de plantas jovens e adultas da palmeira macaúba. Foram coletados oito folíolos por folha, quatro em cada ... ...

    Abstract O objetivo desse estudo foi desenvolver um modelo estatístico empírico, para estimar a superfície foliar, por um método não destrutivo, de folíolos de plantas jovens e adultas da palmeira macaúba. Foram coletados oito folíolos por folha, quatro em cada lado e duas folhas por plantas, em lados opostos, totalizando 16 folíolos em cada uma das cinco plantas, por estádio fenológico (jovens e adultas). Foram avaliados um total de 80 folíolos para cada estádio fenológico. Individualmente, cada folíolo teve sua área (AF), comprimento (C) e largura (L) mensurados. Foram testados modelos lineares, com e sem o intercepto, e um modelo potencial, empregando as variáveis independentes C, L e C*L. As equações com coeficiente de determinação inferior a 0,90 foram descartadas e o uso da variável combinada C*L resultou em maior exatidão e melhor distribuição dos resíduos, ao empregar a relação funcional y= β0x β1 . Assim, a área de folíolos de macaúba pode ser estimada pela equação AF=0,4683CL 1,1104 .
    Schlagwörter Método não destrutivo ; Ajuste de equações ; Superfície foliolar ; Forestry ; SD1-669.5 ; Agriculture ; S
    Sprache Portugiesisch
    Erscheinungsdatum 2014-09-01T00:00:00Z
    Verlag Embrapa Florestas
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  8. Artikel ; Online: Curvas de índices de local em povoamentos de eucalipto obtidas por regressão quantílica

    Carlos Alberto Araújo Júnior / Carlos Pedro Boechat Soares / Helio Garcia Leite

    Pesquisa Agropecuária Brasileira, Vol 51, Iss 6, Pp 720-

    2016  Band 727

    Abstract: Resumo: O objetivo deste trabalho foi obter curvas de índice de local, em povoamentos de eucalipto, por meio de regressão quantílica, e compará-las às obtidas com o uso de regressões ajustadas pelo método de mínimos quadrados ordinários. A regressão ... ...

    Abstract Resumo: O objetivo deste trabalho foi obter curvas de índice de local, em povoamentos de eucalipto, por meio de regressão quantílica, e compará-las às obtidas com o uso de regressões ajustadas pelo método de mínimos quadrados ordinários. A regressão quantílica pode ser utilizada para a geração de curvas de índice de local, especialmente em presença de dados discrepantes. O método gera um feixe de curvas mais bem ajustadas aos dados observados, em comparação ao feixe gerado com as estimativas de mínimos quadrados ordinários, seja pelo método da curva-guia (curvas anamórficas), seja pela geração de curvas polimórficas (com o uso de diferentes percentis).
    Schlagwörter Eucalyptus ; dados discrepantes ; método da curva-guia ; mínimos quadrados ordinários ; percentis ; Agriculture (General) ; S1-972
    Sprache Englisch
    Erscheinungsdatum 2016-06-01T00:00:00Z
    Verlag Embrapa Informação Tecnológica
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  9. Artikel ; Online: Hipsometric relationship modeling using data sampled in tree scaling and inventory plots

    Valdir Carlos Lima de Andrade / Helio Garcia Leite

    Revista Árvore, Vol 35, Iss 1, Pp 157-

    2011  Band 164

    Abstract: This work evaluated eight hypsometric models to represent tree height-diameter relationship, using data obtained from the scaling of 118 trees and 25 inventory plots. Residue graphic analysis and percent deviation mean criteria, qui-square test precision, ...

    Abstract This work evaluated eight hypsometric models to represent tree height-diameter relationship, using data obtained from the scaling of 118 trees and 25 inventory plots. Residue graphic analysis and percent deviation mean criteria, qui-square test precision, residual standard error between real and estimated heights and the graybill f test were adopted. The identity of the hypsometric models was also verified by applying the F(Ho) test on the plot data grouped to the scaling data. It was concluded that better accuracy can be obtained by using the model prodan, with h and d1,3 data measured in 10 trees by plots grouped into these scaling data measurements of even-aged forest stands.
    Schlagwörter Bioestatística florestal ; Identidade de modelos ; Análise de regressão ; Forestry ; SD1-669.5 ; Agriculture ; S
    Sprache Portugiesisch
    Erscheinungsdatum 2011-02-01T00:00:00Z
    Verlag Sociedade de Investigações Florestais
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  10. Artikel ; Online: Precipitação efetiva e interceptação da chuva em um fragmento florestal com diferentes estágios de regeneração

    Alexandre Simões Lorenzon / Herly Carlos Teixeira Dias / Hélio Garcia Leite

    Revista Árvore, Vol 37, Iss 4, Pp 619-

    2013  Band 627

    Abstract: Este trabalho teve por objetivo avaliar a precipitação efetiva e a interceptação da chuva em um fragmento de Floresta Estacional Semidecidual em estágio inicial e avançado de regeneração no Município de Viçosa, Minas Gerais, no período de agosto de 2009 ... ...

    Abstract Este trabalho teve por objetivo avaliar a precipitação efetiva e a interceptação da chuva em um fragmento de Floresta Estacional Semidecidual em estágio inicial e avançado de regeneração no Município de Viçosa, Minas Gerais, no período de agosto de 2009 a fevereiro de 2011. Foram demarcadas seis parcelas, três na área de regeneração inicial e três na área de regeneração avançada. Para quantificar a precipitação interna e o escoamento pelo tronco, foram instalados 25 pluviômetros em cada parcela e coletores nas árvores com circunferência 15 cm. Além disso, um pluviômetro foi instalado em local aberto para quantificar a precipitação em aberto, que no período estudado foi igual a 1.509,96 mm. Em média, 85,08 e 74,93% da precipitação em aberto, respectivamente, no estágio inicial e avançado de regeneração, chegam ao solo via precipitação efetiva. A interceptação pelo dossel florestal foi maior na área avançada do que na área inicial de regeneração, correspondendo, respectivamente, a 25,07 e 14,92% da precipitação em aberto, o que sugere que áreas mais densamente povoadas interceptam maior quantidade de chuva e, consequentemente, geram menor precipitação efetiva.
    Schlagwörter Mata Atlântica ; Hidrologia florestal ; Manejo de Bacias Hidrográficas ; Forestry ; SD1-669.5 ; Agriculture ; S
    Sprache Portugiesisch
    Erscheinungsdatum 2013-08-01T00:00:00Z
    Verlag Sociedade de Investigações Florestais
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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