Crop Recommendation System
- Authors: Samyak Jain1, Ashutosh Saxena2, Aditya Garg3, Manu Singh4
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View Affiliations Hide Affiliations1 Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, India 2 Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, India 3 Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, India 4 Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, India
- Source: Demystifying Emerging Trends in Green Technology , pp 191-200
- Publication Date: February 2025
- Language: English
Crop Recommendation System, Page 1 of 1
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Agriculture serves as a prominent source of employment for Indian farmers. A prevalent issue among Indian farmers is their inability to make informed decisions regarding crop selection based on soil type. It has a profound impact on productivity. Precision agriculture provides a solution to this issue. This strategy is characterized by the utilization of a soil database that is based on farms, the provision of crops by agricultural experts, and the satisfaction of specific requirements, such as soil quality, through the use of a dataset obtained from a soil testing laboratory. The soil-testing lab offers data derived from the system of recommendations. Subsequently, it will be employed to collect data and construct a band model by employing a technique of determining the outcome according to the preference of the majority. The researchers utilize an Artificial Neural Network (ANN) in conjunction with a Support Vector Machine (SVM) to provide precise recommendations for crop selection based on sitespecific conditions and efficacy.
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