Recently, an interest has developed in the use of whole green grains as functional food materials. The present study was conducted to provide the baseline data for the stable production of whole green grains in 20 cultivars of wheat by investigating the greenness of grain with maturation (from 20 th to 41 st day after heading, at an interval of 3 days). On the 20 th day after heading, the grains were dark green with a wrinkled long-oval shape. After the 35 th day of heading, the grains turned almost yellow with an oval shape. Their redness (‘a’ value of chromaticity) increased from the 20 th to 41 st days after heading, indicating a negative value up to the 32 nd day after heading. A significant decrease in their chlorophyll content was observed with maturation. The yield of whole green wheat grain (including greenish yellow grain) was the highest from the 32 nd to 35 th after heading. Therefore, we concluded that the optimal harvesting period for whole green wheat grain was from the 32 nd to 35 th day after heading. The heading time of various cultivars ranged from April 28 to May 5, the time of Jopummil cultivar grew the fastest among them, such as Gurumil, Alchanmil, but Dahongmil got the latest in heading time. The greenness of seven cultivars (Jeokjungmil, Keumkangmil, Jogyeongmil, Jopummil, Baekjungmil, Yeonbaekmil, and Milseongmil) was relatively higher than that of the others. The yield of greenish whole grain was relatively high in six cultivars (Alchanmil, Baekjungmil, Eunpamil, Yeonbaekmil, Dahongmil, and Urimil). Based on their greenness and yield, the Baekjungmil and Yeonbaekmil cultivars have been considered to be optimal for the production of whole green wheat grain.

연구용 NIR 장비에서 수집된 벼 생엽의 질소 함량 검량 식 및 데이터베이스를 현장용 NIR 장비에 검량식을 이설,검증함으로서 현장 적용 가능성을 평가하기 위해 수행한 결과는 다음과 같다.1. 2003년부터 2009년까지 스펙트럼을 수집한 시료 중선발 된 A 데이터 세트(개체수 454점)의 총 질소범위는 2.041%～4.933%, 2012년 수집된 B 데이터 세트(258점)는 2.180%～3.690%이며 각각의 전체 평균은3.497%, 2.712%였다.2. A, B 데이터 세트에서 유도된 검량식 결과 결정계수(R2)는 각각 0.845, 0.777,표준오차(SEC)는 0.196, 0.126,SECV는 0.238, 0.150이었다.3. 연구용 NIR 장비 400 nm～2500 nm 파장에서 얻어진데이터베이스를 현장용 NIR 장비 1200 nm～2400 nm파장에 맞게 잘라 이설한 후 2012년 데이터베이스에업데이트 확장한 후 작성된 검량식 결과 결정계수(R2)는 0.880, 표준오차(SEC)는 0.191이었다.4. 연구용 NIR 장비에 구축된 데이터베이스를 현장용NIR 장비에 맞춰 데이터베이스를 확장 업데이트하고검량식을 이설한 결과 연구용 장비와의 표준오차는0.005%로 거의 동일한 수준의 결과를 얻었다.

The aim of the present study was to update the calibration that is used for the measurement of the total nitrogen content in the rice plant samples by using the visible and near infrared spectrum. Before the equation merge, correlation coefficient of calibration equation for nitrogen content on each rice parts was 0.945 (Leaf), 0.928 (Stem), and 0.864 (Whole plant), respectively. In the calibration models created by each part in the rice plant under the various regression method, the calibration model for the leaf was recorded with relatively high accuracy. Among of those, the calibration equation developed by Partial least squares (PLS) method was more accurate than the Multiple linear regression (MLR) method. The calibration equation was sensitive based on variety and location variations. However, we have merged and enlarged various of the samples that made not only to measure the nitrogen content more accurately, but also later sampling populations became more diversified. After merging, R2 value becomes more accurate and significantly to 0.950 (L.), 0.974 (S.), 0.940 (W.). Also, after removal of outlier, R2 values increased into 0.998, 0.995, and 0.997. In view of the results so far achieved, Standard error of prediction (SEP) and SEP (C) were reduced in the stem and whole plant. Biases were reduced in the leaf, stem as well as whole plant. Slopes were high in the stem. Standard deviation reduced in the stem but R2 was high in the stem and whole plant. Result was indicated that calibration equation make update, and updating robust calibration equation from merge function and multi-variate calibration.