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| Acesso ao texto completo restrito à biblioteca da Embrapa Milho e Sorgo. Para informações adicionais entre em contato com cnpms.biblioteca@embrapa.br. |
Registro Completo |
Biblioteca(s): |
Embrapa Milho e Sorgo. |
Data corrente: |
13/12/2023 |
Data da última atualização: |
29/01/2024 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
HYDE, K. D.; ABDEL-WAHAB, M. A.; ABDOLLAHZADEH, J.; ABEYWICKRAMA, P. D.; ABSALAN, S.; AFSHARI, N.; AINSWORTH, A. M.; AKULOV, O. Y.; ALEOSHIN, V. V.; AL-SADI, A. M.; ALVARADO, P.; ALVES, A.; ALVES-SILVA, G.; AMALFI, M.; AMIRA, Y.; AMUHENAGE, T. B.; ANDERSON, J. L.; ANTONÍN, V.; AOUALI, S.; APTROOT, A.; APURILLO, C. C. S.; ARAÚJO, J. P. M.; ARIYAWANSA, H. A.; ARMAND, A.; ARUMUGAM, E.; ASGHARI, R.; ASSIS, D. M. A.; ATIENZA, V.; AVASTHI, S.; AZEVEDO, E.; BAHKALI, A. H.; BAKHSHI, M.; BANIHASHEMI, Z.; BAO, D. F.; BARAL, H. O.; BARATA, M.; BARBOSA, F. R.; BARBOSA, R. N.; BARRETO, R. W.; BASCHIEN, C.; BELAMESIATSEVA, D. B.; BENNETT REUEL, M.; BERA, I.; BEZERRA, J. D. P.; BEZERRA, J. L.; BHAT, D. J.; BHUNJUN, C. S.; BIANCHINOTTI, M. V.; BŁASZKOWSKI, J.; BLONDELLE, A.; BOEKHOUT, T.; BONITO, G.; BOONMEE, S.; BOONYUEN, N.; BREGANT, C.; BUCHANAN, P.; BUNDHUN, D.; BURGAUD, G.; BURGESS, T.; BUYCK, B.; CABARROI-HERNÁNDEZ, M.; CÁCERES, M. E. S.; CAEIRO, M. F.; CAI, L.; CAI, M. F.; CALABON, M. S.; CALAÇA, F. J. S.; CALLALLI, M.; CAMARA, M. P. S.; CANO-LIRA, J. F.; CANTILLO, T.; CAO, B.; CARLAVILLA, J. R.; CARVALHO, A.; CASTAÑEDA-RUIZ, R. F.; CASTLEBURY, L.; CASTRO-JAUREGUI, O.; CATANIA, M. D. V.; CAVALCANTI, L. H.; CAZABONNE, J.; CEDEÑO-SANCHEZ, M. L.; CHAHARMIRI-DOKHAHARANI, S.; CHAIWAN, N.; CHAKRABORTY, N.; CHAVERRI, P.; CHEEWANGKOON, R.; CHEN, C.; CHEN, C. Y.; CHEN, K. H.; CHEN, J.; CHEN, Q.; CHEN, W. H.; CHEN, Y. P.; CHETHANA, K. W. T.; COLEINE, C.; CONDÉ, T. O.; CORAZON-GUIVIN, M. A.; CORTÉS-PÉREZ, A.; COSTA-REZENDE, D. H.; COURTECUISSE, R.; CROUCH, J. A.; CROUS, P. W.; CUI, B. K.; CUI, Y. Y.; SILVA, D. K. A. da; SILVA, G. A. da; SILVA, I. R. da; SILVA, R. M. F. da; SILVA SANTOS, A. C. da; DAI, D. Q.; DAY, Y. C.; DAMM, U.; DARMOSTUK, V.; DAROODI ZOHA; DAS, K.; DAS, K.; DAVOODIAN, N.; DAVYDOV, E. A.; DAYARATHNE, M. C.; DECOCK, C.; DE GROOT, M. D.; DE KESEL, A.; DELA CRUZ, T. E. E.; DE LANGE, R.; DELGADO, G.; DENCHEV, C. M.; DENCHEV, T. T.; OLIVEIRA, N. T. de; SILVA, N. T. de; SOUZA, F. A. de; DENTINGER, B.; DEVADATHA, B.; DIANESE, J. C.; DIMA, B.; DINIZ, A. G.; DISSANAYAKE, A. J.; DISSANAYAKE, L. S.; DOĞAN, H. H.; DOILOM, M.; DOLATABADI, S.; DONG, W.; DONG, Z. Y.; SANTOS, L. A. dos; DRECHSLER-SANTOS, E. R.; DU, T. Y.; DUBEY, M. K.; DUTTA, A. K.; EGIDI, E.; ELLIOTT, T. F.; ELSHAHED, M. S.; ERDOĞDU, M.; ERTZ, D.; ETAYO, J.; EVANS, H. C.; FAN, X. L.; FAN, Y. G.; FEDOSOVA, A. G.; FELL, J.; FERNANDES, I.; FIRMINO, A. L.; FIUZA, P. O.; FLAKUS, A.; SOUZA, C. A. F. de; FRISVAD, J. C.; FRYAR, A. C.; GABALDÓN, T.; GAJANAYAKE, A. J.; GALINDO, L. J.; GANNIBAL, P. B.; GARCIA, D.; GARCÍA-SANDOVAL, S. R.; GARRIDO-BENAVENT, I.; GARZOLI, L.; GAUTAM, A. K.; GE, Z. W.; GENÉ, D. J.; GENTEKAKI, E.; GHOBAD-NEJHAD, M.; GIACHINI, A. J.; GIBERTONI, T. B.; GÓES-NETO, A.; GOMDOLA, D.; FARIAS, A. R. G. de. |
Afiliação: |
QUJING NORMAL UNIVERSITY; SOHAG UNIVERSITY; UNIVERSITY OF KURDISTAN; BEIJING ACADEMY OF AGRICULTURE AND FORESTRY SCIENCES; CHIANG MAI UNIVERSITY; CHIANG MAI UNIVERSITY; ROYAL BOTANIC GARDENS OF KEW; KHARKIV NATIONAL UNIVERSITY; LOMONOSOV MOSCOW STATE UNIVERSITY; SULTAN QABOOS UNIVERSITY; UNIVERSITY OF AVEIRO; UNIVERSIDADE FEDERAL DE SANTA CATARINA; MEISE BOTANIC GARDEN; UNIVERSIDADE FEDERAL DE SANTA CATARINA; MAE FAH LUANG UNIVERSITY; SWEDISH UNIVERSITY OF AGRICULTURAL SCIENCES; MORAVIAN MUSEUM; ALGERIAN NATIONAL INSTITUTE OF AGRICULTURAL RESEARCH; UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; MAE FAH LUANG UNIVERSITY; THE NEW YORK BOTANICAL GARDEN; NATIONAL TAIWAN UNIVERSITY; MAE FAH LUANG UNIVERSITY; UNIVERSITY OF MADRAS; MAE FAH LUANG UNIVERSITY; UNIVERSIDADE FEDERAL DE PERNAMBUCO; UNIVERSITAT DE VALÈNCIA; JIWAJI UNIVERSITY GWALIOR; UNIVERSIDADE DE LISBOA; KING SAUD UNIVERSITY; IRANIAN RESEARCH INSTITUTE OF PLANT PROTECTION; SHIRAZ UNIVERSITY; DALI UNIVERSITY; UNIVERSIDADE DE LISBOA; UNIVERSIDADE FEDERAL DE MATO GROSSO; UNIVERSIDADE FEDERAL DE PERNAMBUCO; UNIVERSIDADE FEDERAL DE VIÇOSA; LEIBNIZ INSTITUTE DSMZ-GERMAN COLLECTION OF MICROORGANISMS AND CELL CULTURES; KUPREVICH INSTITUTE OF EXPERIMENTAL BOTANY; UNIVERSITY OF SANTO TOMAS; MAE FAH LUANG UNIVERSITY; UNIVERSIDADE FEDERAL DE GOIAS; UNIVERSIDADE ESTADUAL DE SANTA CRUZ; KING SAUD UNIVERSITY; MAE FAH LUANG UNIVERSITY; UNIVERSIDAD NACIONAL DEL SUR; WEST POMERANIAN UNIVERSITY OF TECHNOLOGY IN SZCZECIN; GHENT UNIVERSITY; KING SAUD UNIVERSITY; MICHIGAN STATE UNIVERSITY; MAE FAH LUANG UNIVERSITY; NATIONAL SCIENCE AND TECHNOLOGY DEVELOPMENT AGENCY; UNIVERSITÀ DEGLI STUDI DI PADOVA; MANAAKI WHENUA-LANDCARE RESEARCH; MAE FAH LUANG UNIVERSITY; UNIVERSITÉ DE BRETAGNE OCCIDENTALE; HARRY BUTLER INSTITUTE; INSTITUT DE SYSTÉMATIQUE, EVOLUTION, BIODIVERSITÉ; UNIVERSITY OF GUADALAJARA; UNIVERSIDADE FEDERAL DE SERGIPE; UNIVERSIDADE DE LISBOA; CHINESE ACADEMY OF SCIENCES; CHINESE ACADEMY OF SCIENCES; UNIVERSITY OF THE PHILIPPINES VISAYAS; UNIVERSIDADE ESTADUAL DE GOIÁS; UNIVERSIDAD NACIONAL DE SAN ANTONIO ABAD DEL CUSCO; UNIVERSIDADE FEDERAL RURAL DE PERNAMBUCO; UNIVERSITY ROVIRA I VIRGILI; UNIVERSIDADE ESTADUAL DE FEIRA DE SANTANA; CHINESE ACADEMY OF SCIENCES; UNIVERSIDAD DE ALCALA; UNIVERSITY OF MINHO; INSTITUTO DE INVESTIGACIONES DE SANIDAD VEGETAL; US DEPARTMENT OF AGRICULTURE; UNIVERSITY OF GUADALAJARA; FUNDACIÓN MIGUEL LILLO; UNIVERSIDADE FEDERAL DE PERNAMBUCO; UNIVERSITÉ DU QUÉBEC À MONTRÉAL; TECHNISCHE UNIVERSITÄT BRAUNSCHWEIG; MAE FAH LUANG UNIVERSIT; CHIANG MAI UNIVERSITY; UNIVERSITY OF CALCUTTA; BOWIE STATE UNIVERSITY; CHIANG MAI UNIVERSITY; MAE FAH LUANG UNIVERSITY; NATIONAL CHUNG HSING UNIVERSITY; ACADEMIA SINICA; UNIVERSIDAD POLITÉCNICA DE HUATUSCO; CHINESE ACADEMY OF SCIENCES; GUIZHOU UNIVERSITY OF TRADITIONAL CHINESE MEDICINE; UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA; MAE FAH LUANG UNIVERSITY; UNIVERSITY OF TUSCIA; UNIVERSIDADE FEDERAL DE VIÇOSA; UNIVERSIDADE ESTADUAL DE SANTA CRUZ; UNIVERSITY OF GUADALAJARA; UNIVERSIDADE ESTADUAL DE FEIRA DE SANTANA; UNIVERSITÉ DE LILLE; UNITED STATES DEPARTMENT OF AGRICULTURE; WESTERDIJK FUNGAL BIODIVERSITY INSTITUTE; BEIJING FORESTRY UNIVERSITY; CHINESE ACADEMY OF SCIENCES; UNIVERSIDADE FEDERAL DE PERNAMBUCO; UNIVERSIDADE FEDERAL DE PERNAMBUCO; UNIVERSITY OF CALIFORNIA; UNIVERSIDADE FEDERAL DE PERNAMBUCO; UNIVERSIDADE FEDERAL DE PERNAMBUCO; QUJING NORMAL UNIVERSITY; BEIJING FORESTRY UNIVERSITY; SENCKENBERG MUSEUM OF NATURAL HISTORY GÖRLITZ; W. SZAFER INSTITUTE OF BOTANY; DAROODI ZOHA, FERDOWSI UNIVERSITY OF MASHHAD; BOTANICAL SURVEY OF INDIA; KYUNGPOOK NATIONAL UNIVERSITY; ROYAL BOTANIC GARDENS VICTORIA; ALTAI STATE UNIVERSITY; POSTGRADUATE INSTITUTE OF AGRICULTURE; MYCOTHÈQUE DE L’UNIVERSITÉ CATHOLIQUE DE LOUVAIN; GHENT UNIVERSITY; MEISE BOTANIC GARDEN; UNIVERSITY OF SANTO TOMAS; GHENT UNIVERSITY; BULGARIAN ACADEMY OF SCIENCES; BULGARIAN ACADEMY OF SCIENCES; UNIVERSIDADE FEDERAL DO PERNAMBUCO; CHIANG MAI UNIVERSITY; FRANCISCO ADRIANO DE SOUZA, CNPMS; UNIVERSITY OF UTAH; CSIR-INSTITUTE OF MICROBIAL TECHNOLOGY; UNIVERSIDADE DE BRASÍLIA; EÖTVÖS LORÁND UNIVERSITY; UNIVERSIDADE FEDERAL DO PERNAMBUCO; UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA; GUIZHOU UNIVERSITY; SELCUK UNIVERSITY; ZHONGKAI UNIVERSITY OF AGRICULTURE AND ENGINEERING; HAKIM SABZEVARI UNIVERSITY; ZHONGKAI UNIVERSITY OF AGRICULTURE AND ENGINEERING; ZHONGKAI UNIVERSITY OF AGRICULTURE AND ENGINEERING; UNIVERSIDADE FEDERAL DE SERGIPE; UNIVERSIDADE FEDERAL DE SANTA CATARINA; QUJING NORMAL UNIVERSITY; CHANDIGARH UNIVERSITY; GAUHATI UNIVERSITY; HAWKESBURY INSTITUTE FOR THE ENVIRONMENT; UNIVERSITY OF NEW ENGLAND; OKLAHOMA STATE UNIVERSITY; KIRŞEHIR AHI EVRAN UNIVERSITY; MEISE BOTANIC GARDEN; CABI; BEIJING FORESTRY UNIVERSITY; HAINAN MEDICAL UNIVERSITY; KOMAROV BOTANICAL INSTITUTE; UNIVERSITY OF MIAMI; UNIVERSITY OF MINHO; UNIVERSIDADE FEDERAL DE UBERLÂNDIA; UNIVERSIDADE FEDERAL DO RIO GRANDE DO NORTE; POLISH ACADEMY OF SCIENCES; UNIVERSIDADE FEDERAL DO AGRESTE DE PERNAMBUCO; TECHNICAL UNIVERSITY OF DENMARK; FLINDERS UNIVERSITY; BARCELONA SUPERCOMPUTING CENTRE; MAE FAH LUANG UNIVERSITY; UNIVERSITY OF OXFORD; UNIVERSITY OF TYUMEN; UNIVERSITAT ROVIRA I VIRGILI; UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO; UNIVERSITAT DE VALÈNCIA; NATIONAL RESEARCH COUNCIL; PATANJALI RESEARCH INSTITUTE; KUNMING INSTITUTE OF BOTANY; UNIVERSITAT ROVIRA I VIRGILI; MAE FAH LUANG UNIVERSITY; IRANIAN RESEARCH ORGANIZATION FOR SCIENCE AND TECHNOLOGY; UNIVERSIDADE FEDERAL DE SANTA CATARINA; UNIVERSIDADE FEDERAL DE PERNAMBUCO; UNIVERSIDADE FEDERAL DE MINAS GERAIS; MAE FAH LUANG UNIVERSITY; MAE FAH LUANG UNIVERSITY. |
Título: |
Global consortium for the classification of fungi and fungus-like taxa. |
Ano de publicação: |
2023 |
Fonte/Imprenta: |
Mycosphere, v. 14, n. 1, p. 1960–2012, 2023. |
Idioma: |
Inglês |
Conteúdo: |
The Global Consortium for the Classification of Fungi and fungus-like taxa is an international initiative of more than 550 mycologists to develop an electronic structure for the classification of these organisms. The members of the Consortium originate from 55 countries/regions worldwide, from a wide range of disciplines, and include senior, mid-career and early-career mycologists and plant pathologists. The Consortium will publish a biannual update of the Outline of Fungi and funguslike taxa, to act as an international scheme for other scientists. Notes on all newly published taxa at or above the level of species will be prepared and published online on the Outline of Fungi website (https://www.outlineoffungi.org/), and these will be finally published in the biannual edition of the Outline of Fungi and fungus-like taxa. Comments on recent important taxonomic opinions on controversial topics will be included in the biannual outline. For example, ‘to promote a more stable taxonomy in Fusarium given the divergences over its generic delimitation’, or ‘are there too many genera in the Boletales?’ and even more importantly, ‘what should be done with the tremendously diverse ‘dark fungal taxa?’ There are undeniable differences in mycologists’ perceptions and opinions regarding species classification as well as the establishment of new species. Given the pluralistic nature of fungal taxonomy and its implications for species concepts and the nature of species, this consortium aims to provide a platform to better refine and stabilise fungal classification, taking into consideration views from different parties. In the future, a confidential voting system will be set up to gauge the opinions of all mycologists in the Consortium on important topics. The results of such surveys will be presented to the International Commission on the Taxonomy of Fungi (ICTF) and the Nomenclature Committee for Fungi (NCF) with opinions and percentages of votes for and against. Criticisms based on scientific evidence with regards to nomenclature, classifications, and taxonomic concepts will be welcomed, and any recommendations on specific taxonomic issues will also be encouraged; however, we will encourage professionally and ethically responsible criticisms of others’ work. This biannual ongoing project will provide an outlet for advances in various topics of fungal classification, nomenclature, and taxonomic concepts and lead to a community-agreed classification scheme for the fungi and fungus-like taxa. Interested parties should contact the lead author if they would like to be involved in future outlines. MenosThe Global Consortium for the Classification of Fungi and fungus-like taxa is an international initiative of more than 550 mycologists to develop an electronic structure for the classification of these organisms. The members of the Consortium originate from 55 countries/regions worldwide, from a wide range of disciplines, and include senior, mid-career and early-career mycologists and plant pathologists. The Consortium will publish a biannual update of the Outline of Fungi and funguslike taxa, to act as an international scheme for other scientists. Notes on all newly published taxa at or above the level of species will be prepared and published online on the Outline of Fungi website (https://www.outlineoffungi.org/), and these will be finally published in the biannual edition of the Outline of Fungi and fungus-like taxa. Comments on recent important taxonomic opinions on controversial topics will be included in the biannual outline. For example, ‘to promote a more stable taxonomy in Fusarium given the divergences over its generic delimitation’, or ‘are there too many genera in the Boletales?’ and even more importantly, ‘what should be done with the tremendously diverse ‘dark fungal taxa?’ There are undeniable differences in mycologists’ perceptions and opinions regarding species classification as well as the establishment of new species. Given the pluralistic nature of fungal taxonomy and its implications for species concepts and the nature of species, this consortium aims t... Mostrar Tudo |
Thesagro: |
Fungo; Nomenclatura; Taxonomia. |
Categoria do assunto: |
V Taxonomia de Organismos |
Marc: |
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Notes on all newly published taxa at or above the level of species will be prepared and published online on the Outline of Fungi website (https://www.outlineoffungi.org/), and these will be finally published in the biannual edition of the Outline of Fungi and fungus-like taxa. Comments on recent important taxonomic opinions on controversial topics will be included in the biannual outline. For example, ‘to promote a more stable taxonomy in Fusarium given the divergences over its generic delimitation’, or ‘are there too many genera in the Boletales?’ and even more importantly, ‘what should be done with the tremendously diverse ‘dark fungal taxa?’ There are undeniable differences in mycologists’ perceptions and opinions regarding species classification as well as the establishment of new species. Given the pluralistic nature of fungal taxonomy and its implications for species concepts and the nature of species, this consortium aims to provide a platform to better refine and stabilise fungal classification, taking into consideration views from different parties. In the future, a confidential voting system will be set up to gauge the opinions of all mycologists in the Consortium on important topics. The results of such surveys will be presented to the International Commission on the Taxonomy of Fungi (ICTF) and the Nomenclature Committee for Fungi (NCF) with opinions and percentages of votes for and against. Criticisms based on scientific evidence with regards to nomenclature, classifications, and taxonomic concepts will be welcomed, and any recommendations on specific taxonomic issues will also be encouraged; however, we will encourage professionally and ethically responsible criticisms of others’ work. 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Embrapa Milho e Sorgo (CNPMS) |
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Biblioteca(s): |
Embrapa Solos. |
Data corrente: |
20/08/2020 |
Data da última atualização: |
21/08/2020 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 2 |
Autoria: |
CARVALHO JUNIOR, W. de; PEREIRA, N. R.; FERNANDES FILHO, E. I.; CALDERANO FILHO, B.; PINHEIRO, H. S. K.; CHAGAS, C. da S.; BHERING, S. B.; PEREIRA, V. R.; LAWALL, S. |
Afiliação: |
WALDIR DE CARVALHO JUNIOR, CNPS; NILSON RENDEIRO PEREIRA, CNPS; ELPIDIO INACIO FERNANDES FILHO, UFV; BRAZ CALDERANO FILHO, CNPS; HELENA SARAIVA KOENOW PINHEIRO, UFRRJ; CESAR DA SILVA CHAGAS, CNPS; SILVIO BARGE BHERING, CNPS; VINICIUS RENDEIRO PEREIRA, UFRRJ; SARA LAWALL, UFRRJ. |
Título: |
Sample design effects on soil unit prediction with machine: randomness, uncertainty, and majority map. |
Ano de publicação: |
2020 |
Fonte/Imprenta: |
Revista Brasileira de Ciência do Solo, v. 44, e0190120, 2020. |
DOI: |
https://doi.org/10.36783/18069657rbcs2019 |
Idioma: |
Inglês |
Conteúdo: |
Notwithstanding the importance of soil surveys, advances in digital soil mapping have mainly focused on mapping soil attributes or properties rather than developing digital maps of soil units or soil classes. The purpose of this research was to develop digital soil unit maps based on primary soil data collection in areas without previously collected soil information. The covariate variability, the random effect across the data subset and the map outputs were the focuses of this study. We used five datasets with four models (Random Forest - RF, Gradient Boosted Machine - GBM, C5.0, and multinomial log-linear model - MLR). The covariates were grouped into five datasets, where four were grouped by Region Of Interest per Class (ROIC) and one was not grouped by ROIC. To evaluate the random effect to split the dataset, we ran each model 50 times and observed the overall accuracy (OA) and kappa index, and uncertainty, majority and variety maps. The OA of Dataset01 to 04 was lower than to Dataset05 accuracy. However, map outputs of RF and GBM for Dataset01 and Dataset05 had the same majority prediction. It seems that RF and GBM produce consistent results in map outputs according to this methodology and pedologist expertise. To evaluate the uncertainty and the consistency of soil unit prediction, we used the majority maps process. Random Forest, similar to GBM, presented the best results. The increase in the number of covariates was not a guarantee of improvement in the OA or in the quality of the map output. Geographic position and distance raster did not improve the map output according to expert evaluation. Because the variance between the ROICs, when the training and validation datasets were split based on it, the subsets are quite different in relation to the covariates, and this is the reason for the worse results of this model, comparing with the Dataset05. On the other hand, when considering one complete dataset not based on ROICs, the variance of training and validation subsets is lower and produced more accurate parameters of quality. MenosNotwithstanding the importance of soil surveys, advances in digital soil mapping have mainly focused on mapping soil attributes or properties rather than developing digital maps of soil units or soil classes. The purpose of this research was to develop digital soil unit maps based on primary soil data collection in areas without previously collected soil information. The covariate variability, the random effect across the data subset and the map outputs were the focuses of this study. We used five datasets with four models (Random Forest - RF, Gradient Boosted Machine - GBM, C5.0, and multinomial log-linear model - MLR). The covariates were grouped into five datasets, where four were grouped by Region Of Interest per Class (ROIC) and one was not grouped by ROIC. To evaluate the random effect to split the dataset, we ran each model 50 times and observed the overall accuracy (OA) and kappa index, and uncertainty, majority and variety maps. The OA of Dataset01 to 04 was lower than to Dataset05 accuracy. However, map outputs of RF and GBM for Dataset01 and Dataset05 had the same majority prediction. It seems that RF and GBM produce consistent results in map outputs according to this methodology and pedologist expertise. To evaluate the uncertainty and the consistency of soil unit prediction, we used the majority maps process. Random Forest, similar to GBM, presented the best results. The increase in the number of covariates was not a guarantee of improvement in the OA or in the ... Mostrar Tudo |
Palavras-Chave: |
Hillslope areas; Mapeamento digital de solos; Random forest; Tree learners models. |
Thesagro: |
Mapa; Solo. |
Thesaurus NAL: |
Soil map. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/215441/1/Sample-design-effects-on-soil-unit-prediction-with-machine-2020.pdf
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Marc: |
LEADER 03027naa a2200313 a 4500 001 2124458 005 2020-08-21 008 2020 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.36783/18069657rbcs2019$2DOI 100 1 $aCARVALHO JUNIOR, W. de 245 $aSample design effects on soil unit prediction with machine$brandomness, uncertainty, and majority map.$h[electronic resource] 260 $c2020 520 $aNotwithstanding the importance of soil surveys, advances in digital soil mapping have mainly focused on mapping soil attributes or properties rather than developing digital maps of soil units or soil classes. The purpose of this research was to develop digital soil unit maps based on primary soil data collection in areas without previously collected soil information. The covariate variability, the random effect across the data subset and the map outputs were the focuses of this study. We used five datasets with four models (Random Forest - RF, Gradient Boosted Machine - GBM, C5.0, and multinomial log-linear model - MLR). The covariates were grouped into five datasets, where four were grouped by Region Of Interest per Class (ROIC) and one was not grouped by ROIC. To evaluate the random effect to split the dataset, we ran each model 50 times and observed the overall accuracy (OA) and kappa index, and uncertainty, majority and variety maps. The OA of Dataset01 to 04 was lower than to Dataset05 accuracy. However, map outputs of RF and GBM for Dataset01 and Dataset05 had the same majority prediction. It seems that RF and GBM produce consistent results in map outputs according to this methodology and pedologist expertise. To evaluate the uncertainty and the consistency of soil unit prediction, we used the majority maps process. Random Forest, similar to GBM, presented the best results. The increase in the number of covariates was not a guarantee of improvement in the OA or in the quality of the map output. Geographic position and distance raster did not improve the map output according to expert evaluation. Because the variance between the ROICs, when the training and validation datasets were split based on it, the subsets are quite different in relation to the covariates, and this is the reason for the worse results of this model, comparing with the Dataset05. On the other hand, when considering one complete dataset not based on ROICs, the variance of training and validation subsets is lower and produced more accurate parameters of quality. 650 $aSoil map 650 $aMapa 650 $aSolo 653 $aHillslope areas 653 $aMapeamento digital de solos 653 $aRandom forest 653 $aTree learners models 700 1 $aPEREIRA, N. R. 700 1 $aFERNANDES FILHO, E. I. 700 1 $aCALDERANO FILHO, B. 700 1 $aPINHEIRO, H. S. K. 700 1 $aCHAGAS, C. da S. 700 1 $aBHERING, S. B. 700 1 $aPEREIRA, V. R. 700 1 $aLAWALL, S. 773 $tRevista Brasileira de Ciência do Solo$gv. 44, e0190120, 2020.
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Embrapa Solos (CNPS) |
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