因地理壞境及氣候因素,台灣稻米無法於田間自然幹燥,收穫時之稻米含水率高,目前採行的方式是以濕榖交易,由農會或民間糧商收購後,統一進行幹燥,因此交易時,濕榖的成品率須有一客觀公平之換算標準。 本研究針對全省57批濕榖樣本測定,含水率為13%w.b.的幹榖成品率(DYR,%)與濕榖含水率(MC,%)存在線性關係,斜率為-1.0617,節距為109.86,判定係數為0.4881。針對影響較為顯著的雙數與幹榖成品率間迴歸所得線性方程式,濕榖含水率的係數為-0.9471,風選除雜率(PISR,%)的係數為-0.8053,節距為109.22,線性關係的判定係數為0.5523。 濕榖幹燥過程中重量的減少除了水分的散失,尚有夾雜物的除去,濕榖夾雜率(FMR,%)與濕榖含水率、風力篩選或容積密度方法有效地檢測出夾雜物的比例。稻米品種與種植期用對於夾雜率並無顯著差異。 目前各農會所採用“以濕榖含水率推算幹榖成品率”之標準,以此標準換算成品率之平均誤差為-1.647%,預估標準差為3.258%,因此仍有改善的空間。
Due to the climate and geographical surrounding in Taiwan, most farmers traded their harvested paddy with moisture within the range of 23~33%w.b. directly to the Farmer’s Association or local grain merchants, and obtained a return of the dried equivalent on the basis of a rough estimation, followed by a certain exchanging rule. However, a fair standard of conversion is a must to reveal the relationship between the harvested and the dried paddy during the trading process and thus becomes a critical subject in Taiwan. In this study, 57 batches (dryers) of samples were investigated. The results of analysis showed that there existed a linear relationship between the dried yield rate (DYR) of paddy and moisture content (MC) with coefficient of determination 0.4881. Slop is -1.0617 and intercept is 109.86. In addition, coefficients of the linear regression equation with multivariable are -0.9471 on moisture content (M.C.,% w.b.) and -0.8053 on pneumatic impurities selecting ratio (PISR,%) and the intercept is 109.22 with coefficient of determinations 0.5523. The relationships between foreign material contents and the other wet grain physical properties were insignificant, however. There is no significant effect for rice species and crops on foreign material content. Further efforts are required to precisely predict the wet rice quality, as far as the foreign material contents are concerned. For the time being, farmer’s association or regional drying center predicted the dried yield rate with the standard conversion equation between wet and dry rice. The mean error of such conversion found to be -1.647% in this study. The standard deviation of predicted value is 3.258%. The conversion equation needs to be improved.