Open Access Open Access  Restricted Access Subscription or Fee Access

A Survey on Data Mining Approaches to Handle Agricultural Data

A. Sangeetha, Dr.M. Ravichandran


Agriculture is the backbone of our country, where every activities and events in the agriculture depends on the area or locality. This variation creates huge number of data’s, and that to be maintained effectively. These uncertain and dynamic data’s are very tedious to maintain and to manipulate. To overcome the above issues, several studies introduced numerous techniques in data mining. This paper gives a survey about the data mining techniques and tools used in agriculture. The data mining techniques used in agriculture which includes clustering techniques such as K-Means, Fuzzy, KNN, and classification techniques such as Bayesian, Artificial Neural network, SVM and Decision Tree etc. This also makes discussion about the problems of those techniques in the real time analysis.


Data Mining, Agricultural Data, Decision Tree, Classification, Clustering.

Full Text:



Wang, Ning, Naiqian Zhang, and Maohua Wang. "Wireless sensors in agriculture and food industry—Recent development and future perspective."Computers and electronics in agriculture 50.1 (2006): 1-14.

Chinchuluun, Radnaabazar, et al. "Clustering and classification algorithms in food and agricultural applications: a survey." Advances in Modeling Agricultural Systems. Springer US, 2009. 433-454.

Arockiam, L., S. Baskar, and L. Jeyasimman. "Overview of clustering techniques in agriculture data mining." Agri. J 6 (2011): 222-225.

Arockiam, L., S. S. Baskar, and L. Jeyasimman. "Clustering Methods and Algorithms in Data Mining: Review." Asian Journal of information Technology11.1 (2012): 40-44.

Kaur, Manpreet, Heena Gulati, and Harish Kundra. "Data Mining in Agriculture on Crop Price Prediction: Techniques and Applications."International Journal of Computer Applications 99.12 (2014): 1-3.

Ruß, Georg. "Data mining of agricultural yield data: A comparison of regression models." Industrial Conference on Data Mining. Springer Berlin Heidelberg, 2009.

Khan, Farah, and Divakar Singh. "Association Rule Mining in the field of Agriculture: A Survey." International Journal of Scientific and Research Publications: 329.

Rizzo, Davide, et al. "Use of crop sequences for data-mining of remotely sensed time series across multiple scales: opportunities for scaling up research on agricultural dynamics."

Armstrong, Leisa J., Dean Diepeveen, and Rowan Maddern. "The application of data mining techniques to characterize agricultural soil profiles."Proceedings of the sixth Australasian conference on Data mining and analytics-Volume 70. Australian Computer Society, Inc., 2007.

Ruß, Georg, et al. "Visualization of agriculture data using self-organizing maps." Applications and Innovations in Intelligent Systems XVI. Springer London, 2009. 47-60.

Ganguly, Auroop R., and Karsten Steinhaeuser. "Data mining for climate change and impacts." 2008 IEEE International Conference on Data Mining Workshops. IEEE, 2008.

Hansen, James W. "Realizing the potential benefits of climate prediction to agriculture: issues, approaches, challenges." Agricultural Systems 74.3 (2002): 309-330.

Cunningham, Sally Jo, and Geoffrey Holmes. "Developing innovative applications in agriculture using data mining." The proceedings of the Southeast Asia regional computer confederation conference. 1999.

Moore, Ian D., et al. "Soil attribute prediction using terrain analysis." Soil Science Society of America Journal 57.2 (1993): 443-452.

Rumpf, T., et al. "Early detection and classification of plant diseases with support vector machines based on hyperspectral reflectance." Computers and Electronics in Agriculture 74.1 (2010): 91-99.

Tucker, Compton J. "Red and photographic infrared linear combinations for monitoring vegetation." Remote sensing of Environment 8.2 (1979): 127-150.

Baier, Wolfgang. "Crop-weather analysis model: review and model development." Journal of applied Meteorology 12.6 (1973): 937-947.

Classification and Prediction of Future Weather by using Back Propagation Algorithm-An Approach by Sanjay D. Sawaitul, Prof. K. P. Wagh, Dr.P. N. Chatur Government College of Engineering, Amravati, Maharashtra, India

Narvekar, Meera, and Priyanca Fargose. "Daily Weather Forecasting using Artificial Neural Network." International Journal of Computer Applications121.22 (2015).

Veenadhari, S., Dr Bharat Misra, and Dr CD Singh. "Data mining Techniques for Predicting Crop Productivity–A review article." International Journal of Computer Science and Technology IJCST 2.1 (2011).

Fathima, G. Nasrin, and R. Geetha. "Agriculture crop pattern using data mining techniques." International Journal of Advanced Research in Computer Science and Software Engineering 4.5 (2014): 781-6.

Mucherino, Antonio, Petraq Papajorgji, and Panos M. Pardalos. "A survey of data mining techniques applied to agriculture." Operational Research 9.2 (2009): 121-140.

Bhargavi, P., and S. Jyothi. "Applying naive bayes data mining technique for classification of agricultural land soils." International journal of computer science and network security 9.8 (2009): 117-122.

Leemans, Vincent, and M-F. Destain. "A real-time grading method of apples based on features extracted from defects." Journal of Food Engineering 61.1 (2004): 83-89.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.