Question3: What are the benefits of earlier prediction of crop yield?Observed Benefits are – 1.  It helps in taking decisions.2.

  It also assists in identifying the relevance of attributes which significantly affect the crop yield.3. It helps in defining a decision support system (DSS) for whole farm management with the goal of optimizing returns on inputs while preserving resources. 4. It helps in Agronomic Management which is the most important input for getting potential yield and high net returns in any crop or crop sequence.

5.  It helps in maximize the crop yield by selection process of the appropriate crop that will be sown plays a vital role. Question4: What are the applications of Data Mining Techniques in field of agriculture?There are several applications of Data Mining techniques in the field of agriculture. Some of the data mining techniques are related to weather conditions and forecasts. For example, the K-Means algorithm is used to perform forecast of the pollution in the atmosphere, the K Nearest Neighbor (KNN) is applied for simulating daily precipitations and other weather variables, and different possible changes of the weather scenarios are analyzed using SVMs.        3. Conclusion & Future WorkThis paper reviews different systems specialized accomplishments in the field of crop yield prediction. Discuses methodology, comprehensive survey of various proposed methods to predict crop yield and applications.

It also discusses various data mining techniques used for prediction of crop yield. Growing better strategies to foresee crop productivity in various climatic conditions can help farmer and different partners in essential basic leadership as far as agronomy and product decision. It additionally talks about different data mining methods utilized for prediction of crop yield. Developing better strategies to predict crop profitability in different climatic conditions can help rancher and distinctive partners in basic fundamental leadership to the extent agronomy and item choice. It also helps the farmers to merchandise the products without middlemen which help them to obtain maximum price for their products.

Promote the  investigation results can be specifically accessible to farmers through web which can expand generation and can improve price. Performance of these classification algorithms can be evaluated on some bigger test datasets in order to get better results 4. References1    Kalyani, M.R.

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Kanjana Dev(2016) ” Enhanced Crop Yield Prediction and Soil Data  Analysis Using Data Mining “International Journal of Modern Computer Science (IJMCS) 4( 6); 2320-7868 16    Dakshayini Patil , Dr.P.G.Halakatti (2017) “Rice Crop Yield Prediction using Data Mining Techniques”, International Journal of Advanced Research in Computer Science and Software Engineering 7(5); 427-431.17    Rupinder Singh , Gurpreet Singh (2017)”Wheat Crop Yield Assessment Using Decision Tree Algorithms”, International Journal of Advanced Research in Computer Science, 8 (5);1809-1817. 18    E.

Manjula , S. Djodiltachoumy(2017)  “A Model for Prediction of Crop Yield” International Journal of Computational Intelligence and Informatics, 6( 4);2349-6363.19     Marzieh Mokarram, Mohammad Jaafar Mokarram and Behrouz Safarianejadian(2017) “Using Adaptive Neuro Fuzzy Inference System (ANFIS) for Prediction of Soil Fertility for Wheat Cultivation “Biological Forum – An International Journal  9(1): 37-44.

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