RECENT DEVELOPMENTS IN AGRICULTURE USING DATA MINING TECHNIQUES

V.Manimekalai , R.Suresh

Abstract


This survey covers some very recent applications of data miningtechniques in the field of agriculture. This is an emerging researchfield that is experiencing a constant development. In this paper, we firstpresent two applications in this field in details; in particular, we considerthe problem of discovering problematic wine augmentations at the earlystages of the process, and the problem of predicting yield production byusing sensor data information. Secondly, we briefly describe other problemsin the field for which we found very recent contributions in the Scientificliterature.


Keywords


Clustering, Fermentations, Cross-validation,k-means algorithm, Bi-cluster.

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References


S. Arivazhagan, R.N. Shebiah, S.S. Nidhyanandhan, L. Ganesan, Fruit Recognitionusing Color and Texture Features, Journal of Emerging Trends in Computing andInformation Sciences 1(2), 90–94, 2010.

P. Baranowski, W. Mazurek, Detection of Physiological Disorders and MechanicalDefects in Apples using Thermography, International Agrophysics 23, 9–17, 2009.

S. Busygin, O.A. Prokopyev, P.M. Pardalos, Feature Selection for Consistent Bi-clustering via Fractional 0-1 Programming, Journal of Combinatorial Optimization10, 7-21, 2005.

P. Cortez, A. Cerdeira, F. Almeida, T. Matos, J. Reis, Modeling Wine Preferencesby Data Mining from Physicochemical Properties, Decision Support Systems 47(4),547–553, 2009.

S. Cubero, N. Aleixos, E. Molt´o, J. G´omez-Sanchis, J. Blasco, Advances in MachineVision Applications for Automatic Inspection and Quality Evaluation of Fruits andVegetables, Food and Bioprocess Technology 4(4), 487–504, 2011.

L. Ding, J. Meng, Z. Yang, An Early Warning System of Pork Price in ChinaBased on Decision Tree, IEEE Conference Proceedings, International Conferenceon E-Product E-Service and E-Entertainment (ICEEE), Henan, China, 1–6, 2010.

D.A. Griffith, Spatial Autocorrelation and Spatial Filtering, Advances in SpatialScience Series, Springer, New York, 2003.

M. Guarino, P. Jans, A. Costa, J-M. Aerts, D. Berckmans, Field Test of Algorithm for Automatic Cough Detection in Pig Houses, Computers and Electronicsin Agriculture 62(1), 22–28, 2008.

D.S. Guru, Y.H. Sharath, S. Manjunath, Texture Features and KNN in Classification of Flower Images, International Journal of Computer Applications 1, SpecialIssue “Recent Trends in Image Processing and Pattern Recognition”, 21–29, 2010.

R.P. Haff, Real-Time Correction of Distortion in X-ray Images of Cylindrical orSpherical Objects and its Application to Agricultural Commodities, Transactionsof the American Society of Agricultural and Biological Engineers 51(1), 341–349,2007.

R.P. Haff, N. Toyofuku, X-ray Detection of Defects and Contaminants in the FoodIndustry, Sensing and Instrumentation for Food Quality and Safety 2(4), 262–273,2008.

J. Hartigan, Clustering Algorithms, John Wiles & Sons, New York, 1975.13. M. Kovacevic, B. Bajat, B. Gajic, Soil Type Classification and Estimation of SoilProperties using Support Vector Machines, Geoderma 154(3–4), 340–347, 2010.

O.E. Kundakcioglu, P.M. Pardalos, The Complexity of Feature Selection for Consistent Biclustering, In: Clustering Challenges in Biological Networks, S. Butenko,P.M. Pardalos, W.A. Chaovalitwongse (Eds.), World Scientific Publishing, 2009.

A. Mucherino, A. Urtubia, Consistent Biclustering and Applications to Agriculture,IbaI Conference Proceedings, Proceedings of the Industrial Conference on DataMining (ICDM10), Workshop “Data Mining in Agriculture” (DMA10), Berlin,Germany, 105-113, 2010.


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