Abstract
Yield prediction model for mixed pasture was developed with a shortage that the relationship between dry matter yield (DMY) and days of summer depression (DSD) was not properly reflected in the model in the previous research. Therefore, this study was designed to eliminate the data of the regions with distinctly different climatic conditions and then investigate their relationships DMY and DSD using the data in each region separately of regions with distinct climatic characteristics and classify the data based on regions for further analysis based on the previous mixed pasture prediction model. The data set used in the research kept 582 data points from 11 regions and 41 mixed pasture types. The relationship between DMY and DSD in each region were analyzed through scatter plot, correlation analysis and multiple regression analysis in each region separately. In the statistical analysis, DMY was taken as the response variable and 5 climatic variables including DSD were taken as explanatory variables. The results of scatter plot showed that negative correlations between DMY and DSD were observed in 7 out of 9 regions. Therefore, it was confirmed that analyzing the relationship between DMY and DSD based on each region is necessary and 5 regions were selected (Hwaseong, Suwon, Daejeon, Siheung and Gwangju) since the data size in these regions is large enough to perform the further statistical analysis based on large sample approximation theory. Correlation analysis showed that negative correlations were found between DMY and DSD in 3 (Hwaseong, Suwon and Siheung) out of the 5 regions, meanwhile the negative relationship in Hwaseong was confirmed through multiple regression analysis. Therefore, it was concluded that the interpretability of the yield prediction model for mixed pasture could be improved based on constructing the models using the data from each region separately instead of using the pooled data from different regions.
본 연구는 혼파초지 수량예측모형에서 기후특성이 뚜렷한 지역의 자료 제거 및 지역별 구분을 통해 건물수량과 하고일수 간 상관관계를 검토하였다. 데이터세트는 총 582점으로 11개 지역으로 분류되며 혼파조합은 총 41가지였다. 변수에서 반응변수는 건물수량 이었으며 설명변수는 하고일수를 포함한 5가지의 기상변수를 이용하였다. 통계방법은 산점도, 기술통계량 및 상관분석을 거쳐 다중회귀분석을 통해 건물수량과 하고일수 간 상관관계를 확인하였다. 산점도 분석 결과 데이터세트를 지역별로 구분하였을 때 9개 지역 중 7개에서 건물수량과 하고일수 간 부(-)의 상관관계가 나타나 지역을 구분할 필요가 있었으며 대표본 근사이론을 적용할 수 있었던 5개 지역(화성, 수원, 대전, 시흥 및 광주)을 선정하였다. 5개 지역의 상관분석 결과 3개 지역(화성, 수원 및 시흥)에서, 다중회귀분석결과 화성에서 건물수량에 대한 하고일수의 효과가 부(-)로 나타났다. 따라서 혼파초지의 건물수량에 대한 하고일수의 상관관계는 지역별로 구분하였을 때 풀사료 생산이론과 일치하여 수량예측모형의 정밀도를 높일 수 있을 것으로 판단하였다.
