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http://dx.doi.org/10.5532/KJAFM.2021.23.4.391

Long Range Forecast of Garlic Productivity over S. Korea Based on Genetic Algorithm and Global Climate Reanalysis Data  

Jo, Sera (Climate change Assessment Division, National Institute of Agricultural Sciences)
Lee, Joonlee (School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology)
Shim, Kyo Moon (Climate change Assessment Division, National Institute of Agricultural Sciences)
Kim, Yong Seok (Climate change Assessment Division, National Institute of Agricultural Sciences)
Hur, Jina (Climate change Assessment Division, National Institute of Agricultural Sciences)
Kang, Mingu (Climate change Assessment Division, National Institute of Agricultural Sciences)
Choi, Won Jun (Climate change Assessment Division, National Institute of Agricultural Sciences)
Publication Information
Korean Journal of Agricultural and Forest Meteorology / v.23, no.4, 2021 , pp. 391-404 More about this Journal
Abstract
This study developed a long-term prediction model for the potential yield of garlic based on a genetic algorithm (GA) by utilizing global climate reanalysis data. The GA is used for digging the inherent signals from global climate reanalysis data which are both directly and indirectly connected with the garlic yield potential. Our results indicate that both deterministic and probabilistic forecasts reasonably capture the inter-annual variability of crop yields with temporal correlation coefficients significant at 99% confidence level and superior categorical forecast skill with a hit rate of 93.3% for 2 × 2 and 73.3% for 3 × 3 contingency tables. Furthermore, the GA method, which considers linear and non-linear relationships between predictors and predictands, shows superiority of forecast skill in terms of both stability and skill scores compared with linear method. Since our result can predict the potential yield before the start of farming, it is expected to help establish a long-term plan to stabilize the demand and price of agricultural products and prepare countermeasures for possible problems in advance.
Keywords
Garlic productivity; Artificial Intelligence; Long-range forecast; Climatic potential yield;
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Times Cited By KSCI : 2  (Citation Analysis)
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