Models for Estimating Yield of Italian Ryegrass in South Areas of Korean Peninsula and Jeju Island

서지정보

ㆍ발행기관 : 한국초지조사료학회 ㆍ수록지정보 : 한국초지조사료학회지 / 36권 / 3호
ㆍ저자명 : Jing Lun Peng, Moon Ju Kim, Byong Wan Kim, Kyung Il Sung

목차

Ⅰ. INTRODUCTION
Ⅱ. MATERIALS AND METHODS
1. Data collection and preparation
2. Statistical Analyses
Ⅲ. RESULTS AND DISCUSSION
1. Independent sample t-test results for DMY andclimatic factors between cultivated locations insouth areas of Korean Peninsula and Jeju Island
2. Model construction for IRG in cultivated locationsin south areas of Korean Peninsula
3. Yield estimation model construction for IRG inJeju Island
Ⅳ. CONCLUSION
Ⅴ. ACKNOWLEDGEMENT
Ⅵ. REFERRENCES

영어 초록

The objective of this study was to construct Italian ryegrass (IRG) dry matter yield (DMY) estimation models in South Korea based on climatic data by locations. Obviously, the climatic environment of Jeju Island has great differences with Korean Peninsula. Meanwhile, many data points were from Jeju Island in the prepared data set. Statistically significant differences in both DMY values and climatic variables were observed between south areas of Korean Peninsula and Jeju Island. Therefore, the estimation models were constructed separately for south areas of Korean Peninsula and Jeju Island separately. For south areas of Korean Peninsula, a data set with a sample size of 933 during 26 years was used. Four optimal climatic variables were selected through a stepwise approach of multiple regression analysis with DMY as the response variable. Subsequently, via general linear model, the final model including the selected four climatic variables and cultivated locations as dummy variables was constructed. The model could explain 37.7% of the variations in DMY of IRG in south areas of Korean Peninsula. For Jeju Island, a data set containing 130 data points during 17 years were used in the modeling construction via the stepwise approach of multiple regression analysis. The model constructed in this research could explain 51.0% of the variations in DMY of IRG. For the two models, homoscedasticity and the assumption that the mean of the residuals were equal to zero were satisfied. Meanwhile, the fitness of both models was good based on most scatters of predicted DMY values fell within the 95% confidence interval.

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