A METHOD OF CAPABILITY EVALUATION FOR KOREAN PADDY SOILS -Part 2. The rice yield prediction by soil fertility constituents and other characters

한국(韓國) 답토양(畓土壤)의 생산력(生産力) 평가방법에 관한 연구 -2 보(報)·비옥도(肥沃度) 구성인자(構成因子) 및 기타(其他) 특성(特性)에 의(依)한 쌀수확량(收穫量)의 추정(推定)

In the first paper of the series the five soil fertility factors were evaluated by means of principal component analysis and varimax method. They are interpreted as representing, 1) skeletal available phosporus status, 2) organnic matter status, 3) salt status 4) base status, and 5) free oxide status. In order to resynthesize such fragmented information for the overall soil fertility evaluation, the method of multiple regression analysis was adopted, using the five factor scores and yield data for Korean paddy soils as independent and dependent variables respectively. As test of linear models with different combinations of independent variables the results of t-test of regression coefficient were revealed that the organic matter status (FII) has no relevance to the yield of paddy and that the free oxides and salt supply has by it self only an insignificant contribution to the yield. The multiple correlation coefficient (R) revealed its multiple regression analysis was as low as 0.43. Introduction of quadratic terms to the linear model bettered the result. Thus multiple correlation coefficient (R) was increased as 0.59. Therefore, a coefficient of determination 0.35 was obtained by a quadratic model with interaction terms among the five fertility constituents. Generally we think that the fertility factor has more contribution to raise the rice yield in paddy and that the failure of yield prediction by fertility factor scores was caused by one of follows; 1) the roughness of the yield inspection, and 2) missextraction of fertility constituents. The second step in this study, assuming that the residuals by multiple regression analysis were due to factors other than soil fertility, we can now proceed to predicting the yield from the field characters with the classified fertility groups by means of Hayashi's theory of quantification No. 1. Such variables as fertility groups (FTYG), water availability (WATER), soil drainage (DRNG), climatic zone (CLIZ), surface soil's stickiness (STCKT), surface soil's dry consistence (DCNST), and surface soil's texture (FTEXT) are taken up as the explanatory variables. The quantification appears reasonable; the well to extremely well in soil drainage, very sticky of surface soil, inefficiency in water availability, coarse texture, and very hard to extremely hard dry consistence in soil are detrimental to the rice yield. The R was as high as 0.90 for the set of variables. But the given explanatory variables in this study were not quite effective in explaining rice yield. The method developed seems to be promising only if properly collected data are available. Conditions that should be satisfied in the yield inspection obtained from common cultivator for the purpose of deriving a prediction equation were put forward.

본(本) 연구의 제(第)1보(報)에서 추출(抽出)된 비옥도(肥沃度) 구성인자(構成因子)의 인자평점(因子評点) 및 현지조사(現地調査)에서 얻은 기타(其他) 환경인자(環境因子)를, 설명변수(說明變數)로 취(取)하고, 현지(現地)에서 청취조사(聽取調査)로부터 얻어진 쌀 수확량(收穫量)을 목적변수(目的變數)로 하여 다중회귀(多重回歸) 분석(分析)과 하야시의 수량화(數量化) 이론(理論) I (Hayashi's theory of quantification No.1)를 적용(適用)하여 생산력을 추정(推定)한 결과(結果)는 다음과 같다. (1) 시료(試料) 개체(個體)에 대하여 얻어진 다섯개의 인자평점(因子評点)을 설명변수(說明變數)로 하여 다중회귀분석(多重回歸分析)을 행(行)한 결과(結果) 중상관계수(重相關係數)가 0.43으로 추정(推定) 정도(程度)가 낮았다. (2) 비옥도(肥沃度) 인자간(因子間)의 상호작용(相互作用)을 고려(考慮)하여 직선회귀(直線回歸) 모델을 이차방정식(二次方程式)으로 변형(變形)시켜 생산력(生産力)을 추정(推定)한 결과(結果) 중상관계수(重相關係數)가 0.59로써 추정정도(推定精度)는 약간 높아졌으나 만족할 수 있는 추정식(推定式)은 얻지 못하였다. (3) 답(畓) 토양(土壤)에서 쌀의 생산력(生産力)을 지배(支配)하는 인자(因子)로서 비옥도(肥沃度)는 물론(勿論) 중요(重要)하지만 다른 환경인자(環境因子)의 영향(影響)도 받을 것으로 사료(思料)되어 비옥도군(肥沃度群), 수분공급(水分供給)의 양부(良否), 토양배수(土壤排水)의 양부(良否), 기후대(氣候帶), 표토(表土)의 점착성(粘着性), 표토(表士)의 결시성(結持性), 토성(土性) 및 하층토(下層土)의 구조발달정도(構造發達程度) 등(等)을 설명변수(說明變數)도 취(取)하여 하야시의 수량화(數量化) 이론(理論) 1을 적용(適用)하여 생산력(生産力)을 추정(推定)한 결과(結果) 중상관계수(重相關係數)가 0.9였고, 이들 인자(因子)들 중(中) 비옥도군(肥沃度群), 수분공급(水分供給) 및 기후대(氣候帶) 인자(因子)가 생산력(生産力)에 크게 기여(寄與)하고 있는 것으로 나타났다.