1.Areef, M., Rajeswari, S., Vani, N. and Naidu, G.M. 2020. Forecasting of onion prices in Bangalore market: An application of time series models. Indian Journal of Agricultural Economics, 75(2): 218–221.

2.Atesogun, A. and Gulsen, M.A. 2024. Hybrid forecasting structure based on ARIMA and artificial neural network models. Applied Sciences, 14(16): 7122.

3.Dave, E., Leonardo, A., Jeanice, M. and Hanafiah, N. 2021. Forecasting Indonesia exports using a hybrid model ARIMA-LSTM. Procedia Computer Science, 179: 480–487.

4.Gadge, S.B. and Lawande, K.E. 2012. Crop damage due to climatic change: A major constraint in onion farming. Journal of Community Mobilization and Sustainable Development, 7(2): 211–215.

5.Jha, G.K. and Sinha, K. 2014. Time-delay neural networks for time series prediction: An application to the monthly wholesale price of oilseeds in India. Neural Computing and Applications, 24(3–4): 563–571.

6.Kamble, A. and Tiwari, U. 2019. Instability in onion production and marketing in Maharashtra. International Journal of Science and Research, 8(2): 975–979.

7.Kulkarni, B.S., Patil, S.M. and Ramchandra, V.A. 2012. Growth trends in area, production, and export of onion from India: An economic analysis. International Journal of Commerce and Business Management, 5(2): 159–163.

8.Kumar, P., Badal, P.S., Paul, R.K., Jha, G.K., Venkatesh, P., Kamalvanshi, K., Anbukani, P., Balasubramanian, M. and Patel, P. 2021. Forecasting onion price for Varanasi market of Uttar Pradesh, India. Indian Journal of Agricultural Sciences, 91(2): 249–253.

9.Kusuma, D.K. and Rudrapur, S. 2016. Production and export performance of Indian onion – Markov chain analysis. Agriculture Update, 11(1): 70–74.

10.Ma, C., Wu, J., Hu, H., Chen, Y. and Li, J. 2024. Predicting stock prices using hybrid LSTM and ARIMA model. International J Applied Mathematics, 54(3): 424–432.

11.Mila, F.A. and Parvin, M.T. 2019. Forecasting area, production and yield of onion in Bangladesh by using ARIMA model. Asian J. Agricultural Extension, Economics and Sociology, 37(4): 1–12.

12.Özen, F. 2024. Random forest regression for prediction of Covid-19 daily cases and deaths in Turkey. Heliyon, 10(2): e25746.

13.Sanjeev and Bhardwaj, N. 2022. Time series prediction using hybrid ARIMA-ANN models for sugarcane. International Journal of Plant and Soil Science, 34(23): 772–782.

14.Shankar, S.V., Chandel, A., Gupta, R.K., Sharma, S., Chand, H., Kumar, R., Mishra, N., Ananthakrishnan, S., Aravinthkumar, A., Kumaraperumal, R. and Gowsar, S. R.N. 2023. Exploring the dynamics of arrivals and prices volatility in onion (Allium cepa) using advanced time series techniques. Frontiers in Sustainable Food Systems, 7: Article 1208898.

15.Sharma, D. and Chauhan, A. 2022. Kharif onion production in India: Present status and future potential—A review. Agricultural Reviews, 45(4): 653-660.