Optical remote sensor for peanut kernel abortion classification

Nisan Ozana; Stav Buchsbaum; Yael Bishitz; Yevgeny Beiderman; Zeev Schmilovitch; Ariel Schwarz; Amir Shemer; Joseph Keshet; Zeev Zalevsky

doi:10.1364/AO.55.004005

Optical remote sensor for peanut kernel abortion classification

Nisan Ozana
, Stav Buchsbaum
, Yael Bishitz
, Yevgeny Beiderman
, Zeev Schmilovitch
, Ariel Schwarz
, Amir Shemer
, Joseph Keshet
, Zeev Zalevsky

Research output: Contribution to journal › Article › peer-review

13 Scopus citations

Abstract

In this paper, we propose a simple, inexpensive optical device for remote measurement of various agricultural parameters. The sensor is based on temporal tracking of backreflected secondary speckle patterns generated when illuminating a plant with a laser and while applying periodic acoustic-based pressure stimulation. By analyzing different parameters using a support-vector-machine-based algorithm, peanut kernel abortion can be detected remotely. This paper presents experimental tests which are the first step toward an implementation of a noncontact device for the detection of agricultural parameters such as kernel abortion.

Original language	English
Pages (from-to)	4005-4010
Number of pages	6
Journal	Applied Optics
Volume	55
Issue number	15
DOIs	https://doi.org/10.1364/AO.55.004005
State	Published - 20 May 2016
Externally published	Yes

ASJC Scopus subject areas

Atomic and Molecular Physics, and Optics
Engineering (miscellaneous)
Electrical and Electronic Engineering

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10.1364/AO.55.004005

Cite this

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title = "Optical remote sensor for peanut kernel abortion classification",

abstract = "In this paper, we propose a simple, inexpensive optical device for remote measurement of various agricultural parameters. The sensor is based on temporal tracking of backreflected secondary speckle patterns generated when illuminating a plant with a laser and while applying periodic acoustic-based pressure stimulation. By analyzing different parameters using a support-vector-machine-based algorithm, peanut kernel abortion can be detected remotely. This paper presents experimental tests which are the first step toward an implementation of a noncontact device for the detection of agricultural parameters such as kernel abortion.",

author = "Nisan Ozana and Stav Buchsbaum and Yael Bishitz and Yevgeny Beiderman and Zeev Schmilovitch and Ariel Schwarz and Amir Shemer and Joseph Keshet and Zeev Zalevsky",

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AU - Ozana, Nisan

AU - Buchsbaum, Stav

AU - Bishitz, Yael

AU - Beiderman, Yevgeny

AU - Schmilovitch, Zeev

AU - Schwarz, Ariel

AU - Shemer, Amir

AU - Keshet, Joseph

AU - Zalevsky, Zeev

PY - 2016/5/20

Y1 - 2016/5/20

N2 - In this paper, we propose a simple, inexpensive optical device for remote measurement of various agricultural parameters. The sensor is based on temporal tracking of backreflected secondary speckle patterns generated when illuminating a plant with a laser and while applying periodic acoustic-based pressure stimulation. By analyzing different parameters using a support-vector-machine-based algorithm, peanut kernel abortion can be detected remotely. This paper presents experimental tests which are the first step toward an implementation of a noncontact device for the detection of agricultural parameters such as kernel abortion.

AB - In this paper, we propose a simple, inexpensive optical device for remote measurement of various agricultural parameters. The sensor is based on temporal tracking of backreflected secondary speckle patterns generated when illuminating a plant with a laser and while applying periodic acoustic-based pressure stimulation. By analyzing different parameters using a support-vector-machine-based algorithm, peanut kernel abortion can be detected remotely. This paper presents experimental tests which are the first step toward an implementation of a noncontact device for the detection of agricultural parameters such as kernel abortion.

UR - https://www.scopus.com/pages/publications/84971298270

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DO - 10.1364/AO.55.004005

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Optical remote sensor for peanut kernel abortion classification

Abstract

ASJC Scopus subject areas

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