Call for Papers - SI on SAUSMLA

Special Issue on Smart Agriculture Unleashed: Statistical Machine Learning in Action

Aims and Scope

The purpose of this special issue is to delve into the utilization of statistical machine learning in smart agriculture, while enhancing data analysis technology. Data science and research on intelligent systems in agriculture have regrettably been overlooked. This special issue endeavors to introduce and advocate for statistical machine learning techniques for processing agricultural data, streamlining agricultural production and decision-making processes, elevating agricultural output, curbing resource consumption, and facilitating sustainable development. Several factors contribute to the current interest in this field: (1) Agriculture generates copious amounts of data, encompassing soil information, meteorological data, and crop growth statistics. The application of statistical machine learning techniques can efficiently extract valuable insights from this data and facilitate more precise, data-driven decision-making. (2) The evolution of statistical machine learning methods and the increased accessibility of computing resources and data have made it feasible to implement these techniques in agriculture. (3) Smart agriculture offers more effective solutions to address the mounting demand for agricultural production, utilizing cutting-edge technologies to optimize production processes. (4) Statistical machine learning plays a pivotal role in optimizing resource utilization, mitigating adverse environmental impacts, and achieving sustainable agricultural practices. In summary, this subject leverages the strengths of data science and intelligent systems to provide comprehensive and accurate guidance for agricultural production.

Lead Guest Editors

Assoc. Prof. Xueqian Fu
China Agricultural University, China
Research Interests:
Statistical Machine Learning, Agricultural Energy Internet, Smart Agriculture

Guest Editors

Prof. Daoliang Li
China Agricultural University, China
Research Interests:
Digital Fisheries, Information Processing in Agriculture

Prof. Youmin Zhang
Concordia University, Canada
Research Interests: 
Avionics and Flight Control for Manned and Unmanned Aerial Vehicles (UAVs) and Spacecrafts/Satellites

Prof. Xihai Zhang
Northeast Agricultural University, China
Research Interests:
Agricultural Internet of Things, Agricultural Artificial Intelligence, Smart Plant Factory

Assoc. Prof. Jie Liu
Huazhong Agricultural University, China
Research Interests:
Fruit Recognition, Localization and Harvesting, Agricultural Product Quality Inspection


Special Issue Information

We invite researchers and practitioners to submit original research articles, reviews, and case studies. Potential topics include but are not limited to the following:

  • Intelligent recognition of crop growth
  • Optimization method for agricultural energy internet based on statistical machine learning
  • Stochastic simulation of agricultural meteorology based on statistical machine learning
  • Agricultural early warning technology based on statistical machine learning
  • Fish disease prediction and diagnosis based on artificial intelligence technology
  • Pest and disease monitoring and prediction based on statistical machine learning
  • New mechanism and algorithm for path planning of mobile beacon nodes in farmland internet of things under complex environments
  • Non-destructive inspection of agricultural product quality based on machine vision
  • Path planning and tracking control of plant protection unmanned aerial vehicles under non-deterministic environmental constraints


Manuscript Submission Information

Submission deadline: 1 August 2024

Submissions that pass pre-check will be reviewed by at least two reviewers of the specific field. Accepted papers will be published on early access first and sent for copy editing and typesetting. Then all papers will be included in the special issue when it is published.

If you have any queries regarding the special issue or other matters, please feel free to contact the editorial office: /