Ronnie Concepcion II*

Manufacturing Engineering and Management Department, De La Salle University, Philippines

*Corresponding Author: Ronnie Concepcion II, Manufacturing Engineering and Management Department, De La Salle University, Philippines.

Received: June 22, 2021; Published: July 01, 2021

Keywords: Agricultural Revolution; Biosystem; Computational Intelligence; Computer Vision; Crop Phenotyping; Intelligent System; Precision Agriculture

The broad transitions of agricultural technologies from the prehistoric to modern agricultural production, management, and decision support systems determine the validity of the so-called agricultural revolution. By definition, it is the intensifying increase in agricultural outputs that are dominantly based on the developed techniques and approaches in the levels of germplasm up to energizing systems of plant factories. The latest recorded and widely accepted third agricultural revolution is the Green Revolution that happened five decades ago in the developing world especially in European and Western countries. This have significantly contributed to boost their economy and scientific outputs.

Bibliography

1. Marco Esposito., et al. “Drone and sensor technology for sustainable weed management: a review”. Chemical and Biological Technologies in Agriculture 8 (2021): 1-11.
2. Ronnie Concepcion II., et al. “Lactuca sativa leaf extract concentration optimization using evolutionary strategy as photosensitizer for TiO2-filmed Grӓtzel cell”. Optik 242 (2021).
3. Ronnie Concepcion II and Elmer Dadios. “Lettuce leaf necrotic and chlorotic surface defect assessment using recurrent neural network optimized by electromagnetism-like mechanism”. 9th International Symposium on Computational Intelligence and Industrial Applications (ISCIIA2020) (2020).

Citation

Citation: Ronnie Concepcion II. “Ronnie Concepcion II.". Acta Scientific Computer Sciences 3.8 (2021): 01-02.

Copyright

Copyright: © 2021 Ronnie Concepcion II. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.