Stochastic Modeling and Prediction of Sugarcane Crop Production Structure in Pakistan

Sugarcane is one of the major crops grown in four provinces of Pakistan, Punjab, Sindh, Khyber Pakhtunkhwa and Baluchistan with respect to their crop share. In this study the Spatial sugarcane crop yield in Pakistan is modeled and predicted using Markov chain analysis from 2000-2022, with the aim of forecasting for the years 2023-2030 in business-as-usual (BAU) scenario. Yearly transition matrices and average one step transition matrix was determined. Sugarcane crop production increased from 43.61 – 86.45 million metric ton(MMT) during 2000-2022, with a robust Compounded annual growth rate (CAGR) of 3.16 %.The average contributions from the four provinces were 66.78%, 24.76%, 8.40% and 0.06% respectively. Sugarcane production is projected to rise from 90.06 – 120.85 between 2023 – 2030 at an enhanced CAGR of 4.29 %. Additionally, the average contributions from the four provinces during this period will be 78.44%, 16.41%, 5.11% and 0.03% respectively. Furthermore, the Punjab province will anticipate maintaining its status as the top sugarcane producer in Pakistan. To enhance industrial growth and promote socio-economic progress in the country, it is crucial to focus on adding value to the primary sugarcane crop at the state level.