Opinion

Can Remote Sensing and Artificial Intelligence Based Technologies Benefit Modern Agriculture and Food Production Systems?

Abhijit Biswas*
USA Prime Biotech LLC, 1330 NW 6th street, Suite A-2, Gainesville, FL 32601, USA

Abstract

The ever changing climate coupled with increasing demand for more land and water resources along with the threats of global pandemic have put a lot of pressure on modern agriculture and food production systems. It is critical to maintain environmental and economic sustainability of current and future food supply systems in order to secure enough food to feed and sustain a fast-growing global population. To this end, new innovations in scientific and technological advances are thought to be essential to gain insights into the interaction of various components of the agricultural system ranging from the cell to the field level. There have been advances in genetic tools that have enabled superior food production. However, the large-scale assessment of crop status in the field still remains a formidable challenge. Recent innovations in remote sensing and Artificial Intelligence (AI) based agriculture and food production have shown a lot promise in quantifying field scale phenotypic information accurately. In addition, studies have suggested the possibility to integrate the big data into predictive and prescriptive management tools. In this opinion, we have assessed the use of remote sensing and AI technologies that could potentially improve the resilience of agricultural systems and help address the agricultural and human nutrition challenges over the next decades.
Keywords: Remote sensing; artificial intelligence; food production; agriculture; big data
Received: November 5, 2021
Revised manuscript: November 15, 2021
Accepted: November 20, 2021

*E-mail: abbtf@yahoo.com
To cite this article: Biswas A, Can Remote Sensing and Artificial Intelligence Based Technologies Benefit Modern
Agriculture and Food Production Systems? Biotechnol. kiosk, Vol 3, Issue 12, PP: 3-9 (2021); DOI: https://doi.org/10.37756/bk.21.3.12.1