The intensive farming system demands accurate estimating or forecast methods, which are extremely difficult because of the reliance of yield efficiency on climatic, ecological, and agronomic factors and their consequences. Many research has been conducted using the booming technologies like big data, data analysis frameworks, neural networking, deep learning to forecast the yield and quality of Arecanut crop. The study explores the published studies on Arecanut yield forecasting and also examines the frequently used notable approaches and the impact of various environmental factors on the same. The authors have analysed the historical published research data and also performed the quantitative research analysis to examine the crop relationship between various environmental factors.