Prediction of Hexaconazole Concentration in the Top Most Layer of Oil Palm Plantation Soil Using Exploratory Data Analysis (EDA).

Ganoderma boninense is a fungus that can affect oil palm trees and cause a serious disease called the basal stem root (BSR). This disease causes the death of more than 80% of oil palm trees midway through their economic life and hexaconazole is one of the particular fungicides that can control this...

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Main Authors: Zainol Maznah, Muhamad Halimah, Mahendran Shitan, Provash Kumar Karmokar, Sulaiman Najwa
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5217833?pdf=render
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spelling doaj-fd96ed97caf94cceabfe7867c6feeb2d2020-11-24T21:52:12ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01121e016620310.1371/journal.pone.0166203Prediction of Hexaconazole Concentration in the Top Most Layer of Oil Palm Plantation Soil Using Exploratory Data Analysis (EDA).Zainol MaznahMuhamad HalimahMahendran ShitanProvash Kumar KarmokarSulaiman NajwaGanoderma boninense is a fungus that can affect oil palm trees and cause a serious disease called the basal stem root (BSR). This disease causes the death of more than 80% of oil palm trees midway through their economic life and hexaconazole is one of the particular fungicides that can control this fungus. Hexaconazole can be applied by the soil drenching method and it will be of interest to know the concentration of the residue in the soil after treatment with respect to time. Hence, a field study was conducted in order to determine the actual concentration of hexaconazole in soil. In the present paper, a new approach that can be used to predict the concentration of pesticides in the soil is proposed. The statistical analysis revealed that the Exploratory Data Analysis (EDA) techniques would be appropriate in this study. The EDA techniques were used to fit a robust resistant model and predict the concentration of the residue in the topmost layer of the soil.http://europepmc.org/articles/PMC5217833?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Zainol Maznah
Muhamad Halimah
Mahendran Shitan
Provash Kumar Karmokar
Sulaiman Najwa
spellingShingle Zainol Maznah
Muhamad Halimah
Mahendran Shitan
Provash Kumar Karmokar
Sulaiman Najwa
Prediction of Hexaconazole Concentration in the Top Most Layer of Oil Palm Plantation Soil Using Exploratory Data Analysis (EDA).
PLoS ONE
author_facet Zainol Maznah
Muhamad Halimah
Mahendran Shitan
Provash Kumar Karmokar
Sulaiman Najwa
author_sort Zainol Maznah
title Prediction of Hexaconazole Concentration in the Top Most Layer of Oil Palm Plantation Soil Using Exploratory Data Analysis (EDA).
title_short Prediction of Hexaconazole Concentration in the Top Most Layer of Oil Palm Plantation Soil Using Exploratory Data Analysis (EDA).
title_full Prediction of Hexaconazole Concentration in the Top Most Layer of Oil Palm Plantation Soil Using Exploratory Data Analysis (EDA).
title_fullStr Prediction of Hexaconazole Concentration in the Top Most Layer of Oil Palm Plantation Soil Using Exploratory Data Analysis (EDA).
title_full_unstemmed Prediction of Hexaconazole Concentration in the Top Most Layer of Oil Palm Plantation Soil Using Exploratory Data Analysis (EDA).
title_sort prediction of hexaconazole concentration in the top most layer of oil palm plantation soil using exploratory data analysis (eda).
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2017-01-01
description Ganoderma boninense is a fungus that can affect oil palm trees and cause a serious disease called the basal stem root (BSR). This disease causes the death of more than 80% of oil palm trees midway through their economic life and hexaconazole is one of the particular fungicides that can control this fungus. Hexaconazole can be applied by the soil drenching method and it will be of interest to know the concentration of the residue in the soil after treatment with respect to time. Hence, a field study was conducted in order to determine the actual concentration of hexaconazole in soil. In the present paper, a new approach that can be used to predict the concentration of pesticides in the soil is proposed. The statistical analysis revealed that the Exploratory Data Analysis (EDA) techniques would be appropriate in this study. The EDA techniques were used to fit a robust resistant model and predict the concentration of the residue in the topmost layer of the soil.
url http://europepmc.org/articles/PMC5217833?pdf=render
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