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Development of Temporal Modeling for Forecasting and Prediction of the Incidence of Lychee, Tessaratoma papillosa (Hemiptera: Tessaratomidae), Using Time-Series (ARIMA) Analysis

The most destructive enemy of the lychee, Litchi chinensis Sonn. (Sapindales: Sapindaceae), in India is a stink bug, Tessaratoma papillosa (Drury) (Hemiptera: Tessaratomidae). The population of T. papillosa on lychee trees varied from 1.43 ± 0.501 to 9.85 ± 3.924 insects per branch in this study. An...

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Autores principales: Boopathi, T., Singh, S. B., Manju, T., Ramakrishna, Y., Akoijam, R. S., Chowdhury, Samik, Singh, N. Hemanta, Ngachan, S. V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4535482/
http://dx.doi.org/10.1093/jisesa/iev034
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author Boopathi, T.
Singh, S. B.
Manju, T.
Ramakrishna, Y.
Akoijam, R. S.
Chowdhury, Samik
Singh, N. Hemanta
Ngachan, S. V.
author_facet Boopathi, T.
Singh, S. B.
Manju, T.
Ramakrishna, Y.
Akoijam, R. S.
Chowdhury, Samik
Singh, N. Hemanta
Ngachan, S. V.
author_sort Boopathi, T.
collection PubMed
description The most destructive enemy of the lychee, Litchi chinensis Sonn. (Sapindales: Sapindaceae), in India is a stink bug, Tessaratoma papillosa (Drury) (Hemiptera: Tessaratomidae). The population of T. papillosa on lychee trees varied from 1.43 ± 0.501 to 9.85 ± 3.924 insects per branch in this study. An increase in the temperature and a decrease in the relative humidity during summer months (April to July) favor the population buildup of T. papillosa. A forecasting model to predict T. papillosa incidences in lychee orchards was developed using the autoregressive integrated moving average (ARIMA) model of time-series analysis. The best-fit model for the T. papillosa incidence was ARIMA (1,1), where the P-value was significant at 0.01. The highest T. papillosa incidences were predicted for April in 2010, January in 2011, May in 2012, and February in 2013. A model based on time series offers longer-term forecasting. The forecasting model, ARIMA (1,1), developed in this study will predict T. papillosa incidences in advance, thus providing functional guidelines for effective planning of timely prevention and control measures.
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spelling pubmed-45354822015-08-17 Development of Temporal Modeling for Forecasting and Prediction of the Incidence of Lychee, Tessaratoma papillosa (Hemiptera: Tessaratomidae), Using Time-Series (ARIMA) Analysis Boopathi, T. Singh, S. B. Manju, T. Ramakrishna, Y. Akoijam, R. S. Chowdhury, Samik Singh, N. Hemanta Ngachan, S. V. J Insect Sci Research The most destructive enemy of the lychee, Litchi chinensis Sonn. (Sapindales: Sapindaceae), in India is a stink bug, Tessaratoma papillosa (Drury) (Hemiptera: Tessaratomidae). The population of T. papillosa on lychee trees varied from 1.43 ± 0.501 to 9.85 ± 3.924 insects per branch in this study. An increase in the temperature and a decrease in the relative humidity during summer months (April to July) favor the population buildup of T. papillosa. A forecasting model to predict T. papillosa incidences in lychee orchards was developed using the autoregressive integrated moving average (ARIMA) model of time-series analysis. The best-fit model for the T. papillosa incidence was ARIMA (1,1), where the P-value was significant at 0.01. The highest T. papillosa incidences were predicted for April in 2010, January in 2011, May in 2012, and February in 2013. A model based on time series offers longer-term forecasting. The forecasting model, ARIMA (1,1), developed in this study will predict T. papillosa incidences in advance, thus providing functional guidelines for effective planning of timely prevention and control measures. Oxford University Press 2015-05-05 /pmc/articles/PMC4535482/ http://dx.doi.org/10.1093/jisesa/iev034 Text en © The Author 2015. Published by Oxford University Press on behalf of the Entomological Society of America. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Research
Boopathi, T.
Singh, S. B.
Manju, T.
Ramakrishna, Y.
Akoijam, R. S.
Chowdhury, Samik
Singh, N. Hemanta
Ngachan, S. V.
Development of Temporal Modeling for Forecasting and Prediction of the Incidence of Lychee, Tessaratoma papillosa (Hemiptera: Tessaratomidae), Using Time-Series (ARIMA) Analysis
title Development of Temporal Modeling for Forecasting and Prediction of the Incidence of Lychee, Tessaratoma papillosa (Hemiptera: Tessaratomidae), Using Time-Series (ARIMA) Analysis
title_full Development of Temporal Modeling for Forecasting and Prediction of the Incidence of Lychee, Tessaratoma papillosa (Hemiptera: Tessaratomidae), Using Time-Series (ARIMA) Analysis
title_fullStr Development of Temporal Modeling for Forecasting and Prediction of the Incidence of Lychee, Tessaratoma papillosa (Hemiptera: Tessaratomidae), Using Time-Series (ARIMA) Analysis
title_full_unstemmed Development of Temporal Modeling for Forecasting and Prediction of the Incidence of Lychee, Tessaratoma papillosa (Hemiptera: Tessaratomidae), Using Time-Series (ARIMA) Analysis
title_short Development of Temporal Modeling for Forecasting and Prediction of the Incidence of Lychee, Tessaratoma papillosa (Hemiptera: Tessaratomidae), Using Time-Series (ARIMA) Analysis
title_sort development of temporal modeling for forecasting and prediction of the incidence of lychee, tessaratoma papillosa (hemiptera: tessaratomidae), using time-series (arima) analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4535482/
http://dx.doi.org/10.1093/jisesa/iev034
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