An agricultural tele-monitoring method in detecting nutrient deficiencies of oil palm leaf

H. Muhammad Asraf, Nooritawati Md Tahir, K. A. Nur Dalila, Aini Hussain

Research output: Contribution to journalArticle

Abstract

Nutrient management in oil palm plantation is considered as one of the prominent issues especially for smallholder farmer. The nutrient contained in the tress has always been neglected and untreated and these may cause the trees to suffer from nutrient deficiencies. Therefore, in leveraging the oil yield at the maximum, a telemonitoring system is developed to assess and monitor the lack of nutrients for respective trees. This is done using image processing technique and artificial intelligence in detecting the nutritional deficiencies by analyzing the leaf. The categorization focused by classifying into four major types either as magnesium deficiencies, potassium deficiencies, nitrogen deficiencies or healthy that is based on the oil palm's leaf surface. This is achieved by extracting the features namely number of red pixels, entropy and correlations. Further, two classifiers specifically support vector machine and artificial neural network is used for classification purpose along with performance measure using accuracy(ACC), Mean Square Error (MSE), Mean Absolute Error (MAE), Sensitivity (SN), Specificity (SP), Positive Predictive Value (PPV), Negative Predictive Value (NPV) based on ten-fold cross-validation. Results attained showed that the best classifier is SVM using RBF kernel (SVM-RBF) that is capable to accurately recognize the nutrient deficiencies with 100% accuracy.

Original languageEnglish
Pages (from-to)227-230
Number of pages4
JournalInternational Journal of Engineering and Technology(UAE)
Volume7
Issue number4
DOIs
Publication statusPublished - 1 Jan 2018

Fingerprint

Palm oil
Nutrients
Oils
Food
Monitoring
Classifiers
Potassium Deficiency
Magnesium Deficiency
Artificial Intelligence
Entropy
Malnutrition
Mean square error
Magnesium
Artificial intelligence
Support vector machines
Potassium
Image processing
Nitrogen
Pixels
Neural networks

Keywords

  • Deficiencies detection
  • Leaf disease
  • Machine learning classifier
  • Oil palm
  • SVM (Support Vector Machine)

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science (miscellaneous)
  • Environmental Engineering
  • Chemical Engineering(all)
  • Engineering(all)
  • Hardware and Architecture

Cite this

An agricultural tele-monitoring method in detecting nutrient deficiencies of oil palm leaf. / Muhammad Asraf, H.; Tahir, Nooritawati Md; Nur Dalila, K. A.; Hussain, Aini.

In: International Journal of Engineering and Technology(UAE), Vol. 7, No. 4, 01.01.2018, p. 227-230.

Research output: Contribution to journalArticle

Muhammad Asraf, H. ; Tahir, Nooritawati Md ; Nur Dalila, K. A. ; Hussain, Aini. / An agricultural tele-monitoring method in detecting nutrient deficiencies of oil palm leaf. In: International Journal of Engineering and Technology(UAE). 2018 ; Vol. 7, No. 4. pp. 227-230.
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