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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
28/01/2011 |
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Data da última atualização: |
15/01/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
LUACES, O.; RODRIGUES, L. H. A.; MEIRA, C. A. A.; QUEVEDO, J. R.; BAHAMONDE, A. |
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Afiliação: |
OSCAR LUACES, Universidad de Oviedo; LUIZ HENRIQUE A. RODRIGUES, FEAGRI/UNICAMP; CARLOS ALBERTO ALVES MEIRA, CNPTIA; JOSÉ R. QUEVEDO, Universidad de Oviedo; ANTONIO BAHAMONDE, Universidad de Oviedo. |
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Título: |
Viability of an alarm predictor for Coffee Rust disease using interval regression. |
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Ano de publicação: |
2010 |
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Fonte/Imprenta: |
In: INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND OTHER APPLICATIONS OF APPLIED INTELLIGENT SYSTEMS, 23., 2010, Cordoba. Trends in applied intelligent systems: proceedings. Berlin: Springer, 2010. pt. II, p. 337-346. |
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Série: |
(Lecture notes in artificial intelligence, 6097). |
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ISBN: |
978-3-642-13024-3 |
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Idioma: |
Inglês |
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Notas: |
IEA/AIE 2010. |
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Conteúdo: |
We present a method to formulate predictions regarding continuous variables using regressors able to predict intervals rather than single points. They can be learned explicitly using the so-called insensitive zone of regression Support Vector Machines (SVM). The motivation for this research is the study of a real case; we discuss the feasibility of an alarm system for co?ee rust, the main coffee crop disease in the world. The objective is to predict whether the percentage of infected coffee leaves (the incidence of the disease) will be above a given threshold. The requirements of such a system include avoiding false negatives, seeing as these would lead to not preventing the disease. The aim of reliable predictions, on the other hand, is to use chemical prevention of the disease only when necessary in order to obtain healthier products and reductions in costs and environmental impact. Although the breadth of the predicted intervals improves the reliability of predictions, it also increases the number of uncertain situations, i.e. those whose predictions include incidences both below and above the threshold. These cases would require deeper analysis. Our conclusion is that it is possible to reach a trade-of that makes the implementation of an alarm system for co?ee rust disease feasible. |
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Palavras-Chave: |
Ferrugem do café; Previsão de doença; Sistemas de alarme. |
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Thesagro: |
Hemileia Vastatrix. |
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Thesaurus Nal: |
Alarm systems; Plant diseases and disorders. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02318nam a2200265 a 4500
001 1874993
005 2020-01-15
008 2010 bl uuuu u00u1 u #d
020 $a978-3-642-13024-3
100 1 $aLUACES, O.
245 $aViability of an alarm predictor for Coffee Rust disease using interval regression.$h[electronic resource]
260 $aIn: INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND OTHER APPLICATIONS OF APPLIED INTELLIGENT SYSTEMS, 23., 2010, Cordoba. Trends in applied intelligent systems: proceedings. Berlin: Springer, 2010. pt. II, p. 337-346.$c2010
490 $a(Lecture notes in artificial intelligence, 6097).
500 $aIEA/AIE 2010.
520 $aWe present a method to formulate predictions regarding continuous variables using regressors able to predict intervals rather than single points. They can be learned explicitly using the so-called insensitive zone of regression Support Vector Machines (SVM). The motivation for this research is the study of a real case; we discuss the feasibility of an alarm system for co?ee rust, the main coffee crop disease in the world. The objective is to predict whether the percentage of infected coffee leaves (the incidence of the disease) will be above a given threshold. The requirements of such a system include avoiding false negatives, seeing as these would lead to not preventing the disease. The aim of reliable predictions, on the other hand, is to use chemical prevention of the disease only when necessary in order to obtain healthier products and reductions in costs and environmental impact. Although the breadth of the predicted intervals improves the reliability of predictions, it also increases the number of uncertain situations, i.e. those whose predictions include incidences both below and above the threshold. These cases would require deeper analysis. Our conclusion is that it is possible to reach a trade-of that makes the implementation of an alarm system for co?ee rust disease feasible.
650 $aAlarm systems
650 $aPlant diseases and disorders
650 $aHemileia Vastatrix
653 $aFerrugem do café
653 $aPrevisão de doença
653 $aSistemas de alarme
700 1 $aRODRIGUES, L. H. A.
700 1 $aMEIRA, C. A. A.
700 1 $aQUEVEDO, J. R.
700 1 $aBAHAMONDE, A.
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| 1. |  | KOTHARI, K.; BATTISTI, R.; BOOTE, K. J.; ARCHONTOULIS, S. V.; CONFALONE, A.; CONSTANTIN, J.; CUADRA, S. V.; DEBAEKE, P.; FAYE, B.; GRANT, B.; HOOGENBOOM, G.; JING, Q.; VAN DER LAAN, M.; SILVA, F. A. M. da; MARIN, F. R.; NEHBANDANI, A.; NENDEL, C.; PURCELL, L. C.; QIAN, B.; RUANE, A. C.; SCHOVING, C.; SILVA, E. H. F. M.; SMITH, W.; SOLTANI, A.; SRIVASTAVA, A.; VIEIRA JÚNIOR, N. A.; SALMERÓN, M. Evaluating differences among crop models in simulating soybean in-season growth Field Crops Research, v. 309, 109306, April 2024.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Cerrados. |
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| 2. | | KOTHARI, K.; BATTISTI, R.; BOOTE, K. J.; ARCHONTOULIS, S. V.; CONFALONE, A.; CONSTANTIN, J.; CUADRA, S. V.; DEBAEKE, P.; FAYE, B.; GRANT, B.; HOOGENBOOM, G.; JING, Q.; VAN DER LAAN, M.; SILVA, F. A. M. da; MARIN, F. R.; NEHBANDANI, A.; NENDEL, C.; PURCELL, L. C.; QIAN, B.; RUANE, A. C.; SCHOVING, C.; SILVA, E. H. F. M.; SMITH, W.; SOLTANI, A.; SRIVASTAVA, A.; VIEIRA JÚNIOR, N. A.; SLONE, S.; SALMERÓN, M. Are soybean models ready for climate change food impact assessments? European Journal of Agronomy, v. 135, 126482, Apr. 2022.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Cerrados. |
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| Registros recuperados : 2 | |
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