MODELING OF ARIMA FOR MAIZE PRODUCTION IN INDIA FROM 1980-2022

Abstract

This result paper aims to develop an a ARIMA model to protect predict maize output in India from 1980 to 2022. Agriculture's critical importance in India's economy precise forecasting of crop fields is essential for guaranteeing food security and optimizing agricultural planning this research used the ARIMA (Auto Regressive Integrated Moving Average) Model which is extensively utilized in time series forecasting to analyse historical maize production data for predicting future trends. The research utilizes historical  data analysis to provide important insights into future mace production plans, aiding policy makers and farmers in making informed decisions. The research indicates that ARIMA is effective for predicting, although acknowledges limits related to external variables such as weather patterns and agricultural practices. Maize is not only a staple food for the people but also an industrial raw material for products like poultry feeds, biofuels, and processed foods, among others. The position of maize as a food as well as an industry crop compels the effective prediction of maize production, more so, because India is working hard to feed its ever-bulging population.

This report aims to elucidate the construction as well as the validation of an ARIMA model applied for maize production and scope out the time series forecasting for agriculture within India as a whole. The results are anticipated to offer useful information for decision-makers, agricultural planners, and farmers, thus enabling them to effectively manage the crop and make timely decisions. This research has understood the implications of both the advantages and the weaknesses of the ARIMA model, thus this research will seek to aid the advancement of better forecasting tools which in the future will adapt code techniques of machine learning and artificial intelligence to improve the long-term scope of predicting agriculture.