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Empirical Survey Analysis For Crop Yield Prediction & Identification Of Factors Affecting Yield Gaps.

Authors :
Saini, Preeti
Nagpal, Bharti
Source :
Journal of Pharmaceutical Negative Results; 2022 Special Issue, Vol. 13, p1318-1329, 12p
Publication Year :
2022

Abstract

About 70% of India's economy is involved in the agriculture sector to live their lives and contributed to the GDP of the country. The Crop yield information along with the environmental change estimate will be useful for the agriculturalist to decide on price policies prior to harvesting the food source. It establishes a requirement for the prediction model, which precisely determines the harvest conditions, crop varieties, and agricultural yield. In literature, numerous crop prediction methods were devised to estimate crop production in the agricultural field & each technique has its potential in terms of yield forecasting. This review article provides a detailed analysis of the utilized approaches in the literature for the prediction of crop production as well as a discussion on the identification of concerns related to the yield gaps of crops. The discussed approaches were classified based on the application of different strategies, such as Machine learning methods, Deep learning methods, Data mining techniques, vegetative indices, fuzzy logic, and hybrid methods. The study was analyzed based on performance metrics, year of publication, datasets employed, software used for experimentation, and performance attained using various methods and highlights the research gaps of the respective method along with the future direction. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09769234
Volume :
13
Database :
Complementary Index
Journal :
Journal of Pharmaceutical Negative Results
Publication Type :
Academic Journal
Accession number :
160276645
Full Text :
https://doi.org/10.47750/pnr.2022.13.S05.207