Analysis of Predictions of Garlic Bulb Weight using LASSO Regression Model

Abstract

As part of a preemptive response to ensure a stable supply and demand policy for garlic (Allium sativum L.), the Korean government strives to determine the final yield of garlic by observing its growth status by season. In particular, estimation of the bulb weight of garlic is one of the main steps in estimating garlic production, conducting observational work on spherical weight prediction is getting more important is getting more important. The observation data on garlic can be viewed as data for predicting the final weight, but since root growth occurs intensively at a specific time, there is a limit to predicting the final bulb weight only by the bulb weight corresponding to each observation time point. In addition, since the factors affecting the final bulb weight of garlic may be different for each growing stage, an estimation is required for each stage to predict the final bulb weight at each time point. In this study, garlic bulb weight estimation analysis, which reflects the characteristics of Korean garlic grown in an outfield, is performed using growth survey data. A stage-by-stage model for predicting the bulb weight of garlic at each time point is established, based on the fact that the factors influencing the bulb weight of garlic may differ according to the growth stage. In the process, LASSO regression is used for variable selection and coefficient estimation of the bulb weight of garlic. As a result of the estimation, significant factors regarding growth, lot and environment were identified stage by stage, providing indicators for forecasting final bulb weight of garlic at each stage.