This study monitored temperature using electronic sensors and developed a prediction model for compost maturity. The experiment used swine manure in a mechanical composting facility equipped with a screw-type agitator, and the composting process was conducted for 60 d during the summer season in South Korea. Four electronic temperature sensors were installed on the inner wall between the compost piles on Days 7, 14, 21, and 28 for daily temperature monitoring. Compost samples were collected daily for 60 d, and compost maturity was analyzed using the Solvita method. Multiple comparisons, correlations, and modeling were performed using the stat package in R software. The average compost pile temperatures was 39.1±3.9, 36.4±4.3, 31.3±4.5, and 35.4±8.1 on days 7, 14, 21, and 28, respectively, after composting. The average compost maturity according to the composting date was 3.61±0.60, 4.13±0.59, 4.26±0.47, and 4.32 ±0.56 on days 7, 14, 21, and 28, respectively. A significant negative correlation was observed between the compost composting periods (seven, 14, 21, and 28 d) and the temperature of all compost piles (p<0.05), where the correlation coefficients were -0.329, -0.382, -0.507, and -0.634, respectively. A significant positive correlation was observed between the compost composting periods (seven, 14, 21, and 28 d) and the maturity of the compost (p<0.05), where the correlation coefficients were 0.410, 0.550, 0.727, and 0.840, respectively. The model for predicting the maturation of the 14 d average compost pile according to the compost composting period and the average temperature for 14 d was y=0.026 x d – 0.021 x mt.x_14 d (mean temperature for 14 d) + 4.336 (R2=0.7612, p<0.001). This study can be considered a basic reference for predicting compost maturity by the proposed model using electronic temperature sensors.

TMR 급여와 분리급여가 반추위 메탄발생량 변화에 미치는 효과를 연구한 사례가 많지 않다. 본 실험은 1일 실험사료를 체중의 1.8%(실험 1) 그리고 2.4%(실험 2) 수준에서 급여 하면서 triplicated 2×2 Latin square design을 이용하여 실험을 수행하였다. 각 실험에는 6마리의 Holstein steer를 이용하였고 2개의 군으로 나누어 각각 TMR 급여 또는 분리급여를 하였다. 공시 사료의 농후사료와 조사료 비율은 73% 그리고 27%이었다. 두 실험 모두 사료급여 방식 간의 1일 메탄발생량 차이가 없었다. 현재까지 보고된 국내 연구와 본 연구에서 얻어진 개체 별 1일 건물섭취량과 1일 메탄발생량과의 관계를 분석한 결과, 메탄발생량 (g/d) = 11.5 (±1.3) × 건물섭취량 (kg/d) + 14.2, R2 = 0.73, p<0.001의 회귀식을 유도하였다.

The objective of this study was to determine the effect of various roughage sources on nutrient digestibility and enteric methane (CH4), and carbon dioxide (CO2) production in goats. Four castrated black goats (48.5 ± 0.6 kg) were individually housed in environmentally controlled respiration-metabolism chambers. The experiment design was a 4 × 4 balanced Latin square design with 4 roughage types and 4 periods. Alfalfa, tall fescue, rice straw, and corn silage was used as representative of legume, grass, straw, and silage, respectively. Dry matter digestibility was higher (p < 0.001) in corn silage than in alfalfa hay. Dry matter digestibility of alfalfa hay was higher than those of tall fescue or rice straw (p < 0.001). Neutral detergent fiber digestibility of tall fescue was lower (p < 0.001) than those of alfalfa, rice straw, or corn silage. Daily enteric CH4 production and the daily enteric CH4 production per kilogram of BW0.75, dry matter intake (DMI), organic matter intake (OMI), digested DMI, and digested OMI of rice straw did not differ from those of tall fescue but were higher (p < 0.001) than those of alfalfa or corn silage. Roughage type had no effect on enteric CO2 emission in goats. Straw appeared to generate more enteric CH4 production than legume or silage, but similar to grass.

This paper focuses on how to retell a story for different target readers/ audiences. When retelling/rewriting a given story, various strategies are involved. Adjusting syntactic complexity is one of the various factors when a story is to be retold. This paper investigates what strategies are involved in order to adjust the syntactic complexity, by analyzing three versions of Alice's Adventures in Wonderland by Lewis Carroll. Simply counting the number of complex sentences such as relative clauses, for example, would not be an appropriate way of measuring syntactic complexity. Based on the investigation results reported on in this paper, we found that a storyteller and/or a reteller of a story considers various factors including linguistic complexity, cognitive development, parsing ability, cultural background, as well as other reading- related experiences.