Big Data for Reducing Post-Harvest Losses in Smart Farming

Big Data for Reducing Post-Harvest Losses in Smart Farming

In recent decades, smart farming techniques potentially transformed with many technological trends to meet the future needs of people. Presently, rapid annual population growth demands larger food production with high nutritional values all across the globe. Thus, to satisfy present and future food demands, the public implication of technologies like big data comes into play to increase food production and mitigate post-harvest losses in agricultural sectors.

The essentiality of big data technological trends in agriculture is found to be massive since it holds the ability to provide key data required to acquire greater stability in agriculture. Research envisaged that the preponderance of crops like grains, wheat, and rice is undergoing post-harvest handling and storage management techniques. Thus, higher attempts to mitigate such losses aid in developing greater crop availability among the public. In addition, practicing the mitigation methods of post-harvest losses also helps evolve a safe and healthy ecosystem. BDA (Big Data Analytics) acts as a key tool in digitalized agriculture that features greater possibilities for maintaining sustainability in agriculture. Post-harvest losses are prominently mitigated using big data technologies that minimize pest or insect attacks, which is the major reason for heavy crop losses.

Furthermore, a piece of adequate knowledge of the quality of soil, nutrient level of the earth, and microorganism content in the agricultural lands is deeply monitored using big data technological trends. Data fetched are widely used to reduce post-harvest losses, leading to sustainable farming practices. Additionally, factors such as humidity, suitable storage, and maintenance are also eventually monitored operating trends of big data to develop smart agriculture. A piece of adequate knowledge or deep learning about the technological trends of big data and their applications in agriculture helps in greater sustainability.

The special issue provides many researchers and experts with opportunities to discuss secure methodologies to implement big data for mitigating post-harvest losses. Despite having many beneficial trends, it also holds certain limitations to be addressed. Rules include high system costs, temperature maintenance issues, privacy issues, hacking vulnerabilities, storage problems, etc. The future research scope relies on the factor that aids in overcoming the limitations mentioned above appreciably. Researchers and policymakers are most invited to present theoretical research work against this background. The list of topics in the special section includes, but is not limited to, the following:

  • Emerging trends and applications of big data for smart farming
  • Big data for post-harvest loss: Trends, applications, and perspectives
  • Applications and fundamentals of big data technological trends in smart farming
  • New trends and views of big data for smart farming practices
  • Future perspectives of big data trends in developing smart farming
  • Limitations and drawbacks of big data in smart agriculture
  • Challenges and objectives in the incorporation of big data in précised agriculture
  • Big data for precision farming: Pros and Cons
  • Frontier applications of big data in smart agriculture
  • Insights of smart agriculture and applications for the enhancement of agricultural industries
  • Recent trends and applications of big data for precision agriculture

Guest Editor Detailed Information:

Dr. Shakir Khan

Associate Professor, CCIS, Imam University, Riyadh, Saudi Arabia.

E-Mail: [email protected], [email protected] 

Google Scholar: https://scholar.google.com/citations?user=uw0eUGQAAAAJ&hl=en 

Research Gate: https://www.researchgate.net/profile/Shakir-Khan-6   

Orcid ID: 0000-0002-7925-9191 

Scopus ID: 57218376390 

Web of Science Researcher ID: O-8721-2014

 

Dr. Manju Khari

Professor, School of Computer and Systems Sciences, Jawaharlal Nehru University, Delhi-67, India.

E-Mail: [email protected] 

Google Scholar: https://scholar.google.co.in/citations?user=JB9wY5YAAAAJ&hl=en 

Official Webpage: http://www.jnu.ac.in/content/manjukhari 

ORCID ID: 0000-0001-5395-5335

Scopus ID: 45060953400

Web of Science Researcher ID: AAL-8189-2020/B-6040-2017

 

Dr. Mourade Azrour

Faculty of Sciences and Techniques, Moulay Ismail University of Meknes, Errachidia, Morocco.

E-Mail: [email protected]   

Google Scholar: https://scholar.google.com/citations?user=e_gYfY0AAAAJ&hl=en&oi=sra 

Research Gate: https://www.researchgate.net/profile/Mourade-Azrour 

Personal Website: https://sites.google.com/umi.ac.ma/azrour 

ORCID ID: 0000-0003-1575-8140

Scopus ID: 57193500437

 

Timeline for this Special Issue:

Submission deadline:   April 25, 2024

Author notification:      June 15, 2024

Revised papers due:     August 30, 2024

Final notification:         October 05, 2024

 

The Publication of the special issue will be as per the policy of the journal.

Submission guidelines:

The journal's Guide for Authors on how to prepare a paper is available at: https://qascf.com/index.php/qas/guidelines   

The APC is followed by the Journal

Papers must be submitted electronically via https://qascf.com/index.php/qas/login

To ensure that all manuscripts are correctly identified for inclusion in the special issue, it is important to select the Section “Big data for reducing post-harvest losses”.

Any inquiries regarding the content of papers should be submitted to:

Dr. Shakir Khan: 

[email protected], [email protected]