Authors:
Jatin Sohlot, Palak Teotia, K. Govinda, Sandeep Rangineni, P. Paramasivan   

Addresses:
1,2,3School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India. 4Department of Data Test Engineer, Information Technology, Pluto TV, West Hills, California, USA. 5Department of Research and Development, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India. j16sohlot@gmail.com1, palak.teotia2019@vitstudent.ac.in2, kgovinda@vit.ac.in3, sandeep.rangineni@pluto.tv4, paramasivanchem@gmail.com5 

Abstract:

The need for fertilizer increases since the soil has lost its nutrients due to excessive use. When optimum fertilizer is provided to the soil, it will help improve plant growth and even soil fertility. Recognize that increased fertiliser use could harm the soil and land. After applying excessive fertilizer, harmful greenhouse gases are released into the atmosphere, which pollutes the air. Not only that, but also increases the number of nutrients in adjacent lakes and ponds, which is undesirable. However, if we know the optimal amount, we can boost revenues while reducing environmental damage. Chemical fertilisers based on nitrogen, phosphorous, and potassium are used to fertilise crops in agriculture. However, when utilized in an unoptimized manner, it has negative consequences. For example, soil mineral loss, acidification, various pollutions, etc. Fertilizer optimization is critical and must be addressed. The amount of fertiliser sprayed on the crops is optimised in this research by combining hybrid OBHS (Opposition-based Harmony Search) with MRFO (Manta Ray Foraging Optimization). OBL is a machine-learning algorithm that accelerates soft computing algorithm convergence. It computes both the original and the inverse solution. MRFO, also known as a metaheuristic optimizer, is a nature-inspired algorithm that simulates different foraging behaviors of manta rays and is proposed for tackling real-world engineering issues. When dealing with optimization and real-world engineering problems, it has the best strategy for handling computational cost and solution precision. Using these methods, fertiliser is expected to pose no threat to the soil, crop, or ecosystem. The results reveal that OBHS with MRFO outperforms the other strategies, with a fertiliser optimization accuracy of 99%. This is, we believe, the first work to attempt to combine these two strategies for this goal.

Keywords: Agriculture; Fertilizer; Harmony Search; Manta-Ray Foraging Optimization; N2O and NH3; Neurological Disorders; Gastrointestinal Impairment; Damage to Heart; Carcinogenic.

Received on: 17/11/2022, Revised on: 22/01/2023, Accepted on: 25/02/2023, Published on: 16/03/2023

FMDB Transactions on Sustainable Computing Systems, 2023 Vol. 1 No. 1, Pages: 44-53

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