Enhancing agriculture production through smart assessment of soil nutrients

ABSTRACT

The growth of the world population is leading to an increased demand for food production. Consequently, there is a need to update agricultural processes to enhance production. Smart farming has evolved as a farm management concept that leverages real-time, dependable, and site-specific agricultural information to ensure consistent and sustainable yields. This study focuses on soil nutrient analysis, specifically nitrogen (N), phosphorus (P), and potassium (K) for enhancing crop production. Maintaining an appropriate balance of NPK is crucial for the well-rounded nutrition of crops. Various environmental factors such as temperature, rainfall, humidity, and soil pH affect the NPK composition of agricultural land. The optimal usage of NPK levels can help to improve plant growth, increase crop yields, and enhance overall farm productivity. Hence, we have proposed a stack regressor learning algorithm comprising of two layers for accurate, reliable, and context-sensitive predictions of NPK levels. The proposed approach considers the combined impact of these environmental factors and predicts the optimal NPK requirements tailored to specific crops and agricultural land. The analysis of graphs demonstrates that the predictive accuracy of the proposed stacked regressor model far surpasses that of preexisting built-in machine learning models. This study helps farmers make informed decisions, leading to productivity and sustainability.

KEYWORDS:

• Environmental factors
• machine learning algorithms
• smart farming
• soil nutrient-NPK
• stacked regressor model

Acknowledgement

We would like to express our sincere gratitude to Heritage Institute of Technology, Kolkata for providing research environment and resources that enabled us to undertake this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors stated that no funding was associated with the work presented in this article.