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Machine Learning in Agriculture

Submissions Open: 1 Aug. 2022

Submissions Deadline: 1 Apr. 2023

Guest Editors:

  • David Clay
  • Kathleen Yeater
  • Scott Fausti
  • Luciano Shiratsuchi
  • Nilovna Chatterjee
  • Xiuliang Jin
  • Zamir Libohova

Agriculture industry plays a key role to feed the world. The only way to meet global food requirements while reducing the agricultural carbon footprint is to improve agricultural efficiency. There are several efforts being made to achieve the UN’s Zero Hunger goal by 2030; however, the factors like increasing population, urbanization, and decreasing arable land have added challenges. Moreover, agriculture industry involves a complex combination of genetic, and environmental factors not limited to weather, soil factors, management practices, and so on, which increase the uncertainty of the industry to the changes in these factors. The question is how do we improve recommendations when we have so much uncertainty?

Machine learning (ML) is a branch of computer science and artificial intelligence that uses data and statistical algorithms to learn and predict the outcome with high accuracy. This approach has been proven as a successful prediction technique in several sectors like image recognition, automated vehicle control, speech recognition, medical diagnosis, and so on. The use of ML approach in the agriculture industry can revolutionize the farming system and the overall management system. This approach helps to manage the farm more precisely; for example- soil characterization, nutrients management, water management, weed and disease detection and management, crop growth stages, yield prediction, etc. and successfully supply the world food demand. Thus, the objective of this special issue is to bring together innovative applications of ML approach in the field of agriculture.

The topics of interest for this issue include review and original research papers but not limited to, the following:

  • Introduction, importance, and challenges of ML in agriculture.
  • What is machine learning?
  • How do we conduct machine learning experiment?
  • Can machine learning algorithms replace fertilizer algorithms?
  • Machine learning in nutrient, weed, irrigation, disease management, yield predictions
  • Machine learning in precision agriculture
  • Machine learning in greenhouse gas emissions estimate.
  • Compare satellite/drone data with ground data using ML approach.
  • Various decision support systems used in agriculture.

How to submit

Manuscripts should be submitted through the AJ submission portal: Inquiries should be sent to Managing Editor Emily Mueller (

August 26th, 2022

Senator Bill Cassidy visit LSU and the Digital Ag Team had a chance to talk to him, showing the research, extension and teaching efforts. The focus in AI, on farm research and undergraduate concentration.

August 20th, 2022

Congratulations Phillip Lanza

Former MS student under Dr. Luciano Shiratsuchi advising, accepted in several universities to pursue his PhD program and now in Cornell University.

August 18th, 2022

NEW LSU program in Digital Agriculture

School of Plant, Environmental and Soil Sciences is about to launch a new program to prepare students for a high demanded job market that require knowledge in Precision Agriculture and Data Analytics. More details coming soon!

August 4-5th, 2022

LSU Digital Ag Team visited the US$65million dollar computer of the University of Florida in Gainesville used for Artificial Intelligence (AI) and Machine Learning applications during multistate AI project annual meeting hosted by Dr. Daniel Lee.

July 15th, 2022

Congratulations for your new position Dr. Francielle Morlin Carneiro

Dr. Franciele Morlin Carneiro is finalizing in July 31st her post doctoral with LSU under Dr. Luciano Shiratsuchi supervision and directly assuming a new position as Assistant Professor with the Federal University of Technology - Parana (UTFPR) in Brazil

July 7th, 2022

Congratulations Murilo Martins for your PhD Defense

Scientific Committee: Brenda Tubana, Syam Dodla, Lisa Fultz, Brian Snyder, Murilo Martins and Luciano Shiratsuchi (Chair).

Jun 7th, 2022 - Congratulations Hector Fajardo for your Thesis Defense

Committee: Brenda Tubana (Chair), Lisa Fultz and Luciano Shiratsuchi (members).

Hector Fajardo Thesis Defensejpg

Research / Extension and Teaching working on farm

This web short publication was published 2 years ago, but it is deserved to be reviewed.


Marshall, Mead, and Jay Hardwick farm on 8,000 acres in Tensas Parish. By collaborating with LSU and the AgCenter and benefiting from recent research and development in precision agriculture, including satelite imaging and data analysis, the family has been able to save money on inputs (seed, fertilizer), get bigger yields, and minimize their impact on the surrounding ecosystem.

“We Just Call It Work”

Farmers across Louisiana rely on LSU AgCenter’s cutting-edge research and technological advances in what’s now called digital agriculture—using remote sensing, machine learning, and big data on farms—to get bigger yields and larger profits while protecting the environment for future generations. But some just call it work.

Mead Hardwick is a fourth-generation farmer in Tensas Parish in the northeastern part of the state, a couple of miles from the Mississippi River, along Highway 65. He farms with his brother Marshall and his dad, Jay Hardwick. When invited to a Zoom meeting, he joins via video link from his tractor. Why not? The tractor practically drives itself and although Hardwick does have to turn it around when he reaches the end of the field, he’s surrounded by technology to help him and his family optimize every bit of energy and money they spend across Hardwick Planting Company’s 8,000 acres on a portion of Somerset Plantation’s 20,000 acres.

Read the whole Publication

Jan 22, 2022 - Launched in Brazil by GTS the biggest combine header in the World

Innovate . Educate . Improve Lives

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