Authors :
Shobhit Tembhre; Gopireddy Venkata Rukhmanand Reddy; Chadive Devendra Reddy; Sudalakuntaakhil; Penekalapati Pavan Kalyan
Volume/Issue :
Volume 9 - 2024, Issue 1 - January
Google Scholar :
http://tinyurl.com/2n2dx3tp
Scribd :
http://tinyurl.com/2vybbjd4
DOI :
https://doi.org/10.5281/zenodo.10527308
Abstract :
Agriculture holds a pivotal role in India,
making substantial contributions to the nation's GDP
(23%) and offering significant employment opportunities
(59%), thereby securing the country's food needs.
However, the sector faces challenges due to climate
change, impacting crop predictability and resulting in
lower yields. Recognizing the potential of technology to
address these issues, particularly machine learning, this
research project aims to guide inexperienced farmers in
adopting advanced crop prediction methods. Machine
literacy, a form of machine learning, is proposed as a
solution to enhance agricultural practices by leveraging
data and experience to make informed decisions,
ultimately improving yields and sustainabilityin the face
of climate change.
Agriculture holds a pivotal role in India,
making substantial contributions to the nation's GDP
(23%) and offering significant employment opportunities
(59%), thereby securing the country's food needs.
However, the sector faces challenges due to climate
change, impacting crop predictability and resulting in
lower yields. Recognizing the potential of technology to
address these issues, particularly machine learning, this
research project aims to guide inexperienced farmers in
adopting advanced crop prediction methods. Machine
literacy, a form of machine learning, is proposed as a
solution to enhance agricultural practices by leveraging
data and experience to make informed decisions,
ultimately improving yields and sustainabilityin the face
of climate change.
