Early Price Prediction of Crops Using Machine Learning Model

Abstract

The agriculture sector is a cornerstone of India’s economy, contributing as the third-largest GDP sector and supporting the livelihoods of millions. While farmers in India have extensive knowledge of climate conditions and crop suitability, they often face significant investment losses due to over production of specific crops, leading to low market prices. This overproduction is frequently driven by a lack of accurate price forecasting and guidance on crop selection. To address this challenge, machine learning (ML) techniques can be leveraged to predict optimal crops for cultivation and their base market prices. By analysing historical data, market trends, and environmental factors, these advanced models can provide actionable insights to farmers, help farmers increase profits, thereby reducing losses. This approach ensures informed decision-making, minimizes risks, and promotes sustainable economic growth in the agriculture sector.

Country : India

1 Fathima Begum M2 Venkat Sai Krishna Reddy3 Lokesh Reddy.K

  1. Computer Science and Engineering (Cyber Security), Madanapalle Institute of Technology & Science, Annamayya District, Andhra Pradesh, India
  2. Computer Science and Engineering (Cyber Security), Madanapalle Institute of Technology & Science, Annamayya District, Andhra Pradesh, India
  3. Computer Science and Engineering (Cyber Security), Madanapalle Institute of Technology & Science, Annamayya District, Andhra Pradesh, India

IRJIET, Volume 9, Special Issue of INSPIRE’25 April 2025 pp. 359-363

doi.org/10.47001/IRJIET/2025.INSPIRE58

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