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\begin{document}

\title{Artificial Intelligence-based Machine Learning Model for Identification
of Spices and Herbs: A Systematic Review}



\author[1]{Subh Naman}%
\author[1]{Sanyam Sharma}%
\author[1]{Abhilasha Jain}%
\author[1]{Swati Jindal}%
\author[1]{Ashish Baldi}%
\affil[1]{Maharaja Ranjit Singh Punjab Technical University}%


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  \date{May 24, 2024}


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\begin{abstract}
Spices and herbs play an important role in our day to day life with its
application varying from flavouring the food to various medicinal uses.
But the major limitations linked with these nature oriented spicesare
individualized and restricted information about the identification and
quality mapping. With increasing demands, adulteration of spices and
herbs become a major problem for all the stakeholders \textbf{.}
Artificial intelligence based machine learning and deep learning models
have already been implemented in the various ways for the identification
of herbal images in real time basis. Evidence from past studies related
to identification of plants images strengthens our concept for the
implementation of the artificial intelligence in the spice sector for
the adulteration identification which can become pioneer step in solving
the problem of adulteration. There are various opportunities for
advancement in producing a robust model for the identification of spices
accurately in real time basis. In this review paper, various reliable
and efficient machine learning algorithms for herbs and spice image
classification has been reviewed. Techniques involved forpreparation of
such model have been discussed in details for the better understanding
of readers. With inclusion of various globally available herbal image
datasets and review of recent research related to plants image
identification through machine learning, this article also explains
various machine learning model such as artificial neural network,
convolutional neural network etc along with different parameters
involved in the authentication of the developed model to devise an
artificial intelligence based methodology for quality assessment of
herbs and spices.%
\end{abstract}%



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