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Original Article
Crop Yield and Price Prediction System Using Deep Learning
Dr.Neelam Kumar1
Bhogawade Pallavi2
Jagadale Rutuja3
Jagdale Nisha4
Punde Pranjal5
1 Professor, SRCOE, Department of Computer Engineering, Pune, Maharashtra, India. 2 3 4 5 Student, SRCOE, Department of Computer Engineering, Pune, Maharashtra, India.
Published Online: May-August 2026
Pages: 171-179
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20260502043
References
1. M. Sari, S. Duran and H. Kutlu, “Various optimized machine learning techniques to predict agricultural commodity prices,” Neural Comput.
&Applic., vol. 36, pp. 11439–11459, Apr. 2024.
2. R. L. Manogna, V. Dharmaji and S. Sarang, “A novel hybrid neural network-based volatility forecasting of agricultural commodity prices:
empirical evidence from India,” J. Big Data, vol. 12, Art. no. 85, Apr. 2025.
3. T. Zhang and Z. Tang, “Agricultural commodity futures prices prediction based on a new hybrid forecasting model combining quadratic
decomposition technology and LSTM model,” Front. Sustain. Food Syst., vol. 8, Feb. 2024.
4. .G. Avinash, G. H. Harish Nayak, M. Baishya, B. Samuel Naik and K. V. C., “Enhancing agricultural commodity price forecasting using
generative models: a deep learning approach,” J. Sci. Res. & Reports, vol. 30, no. 10, pp. 1-11, Sept. 2024.
5. A. Thaker, L. H. Chan and D. Sonner, “Forecasting agriculture commodity futures prices with convolutional neural networks with application
to wheat futures,” J. Risk Fin. Manag., vol. 17, no. 4, Art. 143, Apr. 2024.
6. M. Saberironaghi, J. Ren and A. Saberironaghi, “Stock Market Prediction Using Machine Learning and Deep Learning Techniques: A
Review,” AppliedMath, vol. 5, no. 3, Art. 76, June 2025.
7. .M. Barua, T. Kumar, K. Raj and A. M. Roy, “Comparative Analysis of Deep Learning Models for Stock Price Prediction in the Indian
Market,” FinTech, vol. 3, no. 4, pp. 551-568, Nov. 2024.
8. O. Okoyeigbo, “A Comparative Analysis of Machine Learning and Deep Learning Techniques for Accurate Market Price Forecasting,”
Analytics, vol. 4, no. 1, Art. 5, Feb. 2025.
9. H. Gupta, R. Aafrein, R. Kumari, S. Rajput and N. Puri, “Forecasting Commodity Prices using Machine Learning,” Int. J. Scientific Res. in
Sci. & Technol., vol. 11, no. 1, pp. 81-89, Jan-Feb. 2024.
10. H. Saranya, S. Vijayashaarathi, N. Sasirekha, K. Raksha Lohith and S. others, “Stock Market Price Prediction Using Machine Learning,” J.
Popul. Therapeutics Clin. Pharmacol., vol. 30, no. 12, pp. 130-136, 2023.
11. Neelam LabhadeKumar, Mangala S Biradar, Ashvini Narayan Pawale,"Reinforcement Learning-Based Deep FEFM for Blockchain
Consensus Mechanism Optimization with Non-Linear Analysis"Journal of Computational Analysis and Applications, Vol. 33 No. 05 (2024)
12. Neelam Labhade-Kumar “Shot Boundary Detection Using Artificial Neural Network”, Advances in Signal and Data Processing. Lecture
Notes in Electrical Engineering, Springer, Vol 703. PP-44-55 Jan-2021 .
13. Neelam Labhade-Kumar Optimizing Cluster Head Selection in Wireless Sensor Networks Using Mathematical Modeling and Statistical
Analysis of The Hybrid Energy-Efficient Distributed (HEED) Algorithm, Communications on Applied Nonlinear Analysis, ISSN: 1074-
133XVol 31 No. 6s (2024), PP-602-617 August 2024.
14. Neelam Labhade-Kumar “Experimental Design of Electricity Theft Detection and Alert System Using Arduino Assisted Controller and
Smart Sensors"7th International Conference on Inventive Computation Technologies, IEEE Xplore Part Number : CFP24F70-ART ; ISBN
: 979-8-3503-5929-9, 2024,PP-1961-1968 .
15. Dr.NeelamLabhade-Kumar “Novel Management Trends Using IOT in Indian Automotive Spares Manufacturing Industries”, Journal of
Pharmaceutical Negative Results , Vol. 13 ISSUE 09,PP 4887-4899, Nov-2022.
16. Dr.NeelamLabhade-Kumar “Adaptive Hybrid Bird Swarm Optimization Based Efficient Transmission In WSN”, Journal of Pharmaceutical
Negative Results, Vol. 14 ISSUE 02,PP-480-484, Jan-2023.
17. Neelam Labhade-Kumar “Combining Hand-crafted Features and Deep Learning for Automatic Classification of Lung Cancer on CT Scans”,Journal of Artificial Intelligence and Technology, 2023.
18. Neelam Labhade-Kumar “Enhancing Crop Yield Prediction in Precision Agriculture through Sustainable Big Data Analytics and Deep
Learning Techniques”, Carpathian Journal of Food Science and Technology,2023, Special Issue, 1-18.
19. Neelam Labhade-Kumar “Accident prevention and management system in urban VANET for improving slippery roads ride after rain”
Journal of environmental protection and ecology, ISSN:1311-5065 Issue 2 volume 25,PP 586–599,2024.
20. Prof. Dr. Neelam Labhade-Kumar, An image processing method for kidney stone segmentation in CT scan images based on CNN-
regularized extreme learning machine approach, Hybrid and Advanced Technologies, PP- 217-222,202.
&Applic., vol. 36, pp. 11439–11459, Apr. 2024.
2. R. L. Manogna, V. Dharmaji and S. Sarang, “A novel hybrid neural network-based volatility forecasting of agricultural commodity prices:
empirical evidence from India,” J. Big Data, vol. 12, Art. no. 85, Apr. 2025.
3. T. Zhang and Z. Tang, “Agricultural commodity futures prices prediction based on a new hybrid forecasting model combining quadratic
decomposition technology and LSTM model,” Front. Sustain. Food Syst., vol. 8, Feb. 2024.
4. .G. Avinash, G. H. Harish Nayak, M. Baishya, B. Samuel Naik and K. V. C., “Enhancing agricultural commodity price forecasting using
generative models: a deep learning approach,” J. Sci. Res. & Reports, vol. 30, no. 10, pp. 1-11, Sept. 2024.
5. A. Thaker, L. H. Chan and D. Sonner, “Forecasting agriculture commodity futures prices with convolutional neural networks with application
to wheat futures,” J. Risk Fin. Manag., vol. 17, no. 4, Art. 143, Apr. 2024.
6. M. Saberironaghi, J. Ren and A. Saberironaghi, “Stock Market Prediction Using Machine Learning and Deep Learning Techniques: A
Review,” AppliedMath, vol. 5, no. 3, Art. 76, June 2025.
7. .M. Barua, T. Kumar, K. Raj and A. M. Roy, “Comparative Analysis of Deep Learning Models for Stock Price Prediction in the Indian
Market,” FinTech, vol. 3, no. 4, pp. 551-568, Nov. 2024.
8. O. Okoyeigbo, “A Comparative Analysis of Machine Learning and Deep Learning Techniques for Accurate Market Price Forecasting,”
Analytics, vol. 4, no. 1, Art. 5, Feb. 2025.
9. H. Gupta, R. Aafrein, R. Kumari, S. Rajput and N. Puri, “Forecasting Commodity Prices using Machine Learning,” Int. J. Scientific Res. in
Sci. & Technol., vol. 11, no. 1, pp. 81-89, Jan-Feb. 2024.
10. H. Saranya, S. Vijayashaarathi, N. Sasirekha, K. Raksha Lohith and S. others, “Stock Market Price Prediction Using Machine Learning,” J.
Popul. Therapeutics Clin. Pharmacol., vol. 30, no. 12, pp. 130-136, 2023.
11. Neelam LabhadeKumar, Mangala S Biradar, Ashvini Narayan Pawale,"Reinforcement Learning-Based Deep FEFM for Blockchain
Consensus Mechanism Optimization with Non-Linear Analysis"Journal of Computational Analysis and Applications, Vol. 33 No. 05 (2024)
12. Neelam Labhade-Kumar “Shot Boundary Detection Using Artificial Neural Network”, Advances in Signal and Data Processing. Lecture
Notes in Electrical Engineering, Springer, Vol 703. PP-44-55 Jan-2021 .
13. Neelam Labhade-Kumar Optimizing Cluster Head Selection in Wireless Sensor Networks Using Mathematical Modeling and Statistical
Analysis of The Hybrid Energy-Efficient Distributed (HEED) Algorithm, Communications on Applied Nonlinear Analysis, ISSN: 1074-
133XVol 31 No. 6s (2024), PP-602-617 August 2024.
14. Neelam Labhade-Kumar “Experimental Design of Electricity Theft Detection and Alert System Using Arduino Assisted Controller and
Smart Sensors"7th International Conference on Inventive Computation Technologies, IEEE Xplore Part Number : CFP24F70-ART ; ISBN
: 979-8-3503-5929-9, 2024,PP-1961-1968 .
15. Dr.NeelamLabhade-Kumar “Novel Management Trends Using IOT in Indian Automotive Spares Manufacturing Industries”, Journal of
Pharmaceutical Negative Results , Vol. 13 ISSUE 09,PP 4887-4899, Nov-2022.
16. Dr.NeelamLabhade-Kumar “Adaptive Hybrid Bird Swarm Optimization Based Efficient Transmission In WSN”, Journal of Pharmaceutical
Negative Results, Vol. 14 ISSUE 02,PP-480-484, Jan-2023.
17. Neelam Labhade-Kumar “Combining Hand-crafted Features and Deep Learning for Automatic Classification of Lung Cancer on CT Scans”,Journal of Artificial Intelligence and Technology, 2023.
18. Neelam Labhade-Kumar “Enhancing Crop Yield Prediction in Precision Agriculture through Sustainable Big Data Analytics and Deep
Learning Techniques”, Carpathian Journal of Food Science and Technology,2023, Special Issue, 1-18.
19. Neelam Labhade-Kumar “Accident prevention and management system in urban VANET for improving slippery roads ride after rain”
Journal of environmental protection and ecology, ISSN:1311-5065 Issue 2 volume 25,PP 586–599,2024.
20. Prof. Dr. Neelam Labhade-Kumar, An image processing method for kidney stone segmentation in CT scan images based on CNN-
regularized extreme learning machine approach, Hybrid and Advanced Technologies, PP- 217-222,202.
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