A review of recent sensing technologies to detect invertebrates on crops

Abstract

Precision agriculture needs integrated pest management (IPM), for which detection and identification of target invertebrate species is a prerequisite. Researchers have been developing various technologies to detect pests more efficiently and accurately. However, these existing sensing technologies still have limitations for effective infield applications. This review paper aims to explore the relative technologies and find a sensing method that has potential to detect and identify common invertebrates on crops, such as butterflies, locusts, snails and slugs. It was found that there are two main research branches for invertebrate detection and identification: acoustic sensing and machine vision system (MVS). Acoustic sensing is suitable for detecting and identifying pests in soil, stored grains and wood, while usually acoustic sensors need to be attached to samples for inspection, which causes difficulties for efficient infield applications. MVS has the potential to provide a more effective and flexible way to detect and identify invertebrates on crops. In recent work with MVS, the technologies of invertebrate identification have been intensively studied, however, infield detection is relatively weak. This review points out the current research gaps and then discusses the potential research directions.

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Abbreviations

ANN:

Artificial neural network

BOR:

Bag-of-region

CT:

Computerized tomographic

DAISY:

Digital automated identification system

FOV:

Field of view

GLCM:

Gray-level co-occurrence matrix

IA:

Impact acoustic

IPM:

Integrated pest management system

LDA:

Linear discriminant analysis

LDV:

Laser Doppler vibrometer

LED:

Light emitting diode

LMT:

Logistic model tree

MOE:

Modulus of elasticity

MVS:

Machine vision system

QDA:

Quadratic discriminant analysis

SFM:

Structure from motion

SIFT:

Scale-invariant feature transform

SVM:

Support vector machine

TOF:

Time of flight

UV:

Ultraviolet

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Liu, H., Lee, SH. & Chahl, J.S. A review of recent sensing technologies to detect invertebrates on crops. Precision Agric 18, 635–666 (2017). https://doi.org/10.1007/s11119-016-9473-6

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Keywords

  • Invertebrate detection
  • Insect identification
  • IPM
  • Machine vision
  • Acoustic sensing