This study was conducted to find a way to improve quality by observing changes in quality and microbial communities according to whether corn silage was treated with additives and the storage period, and to utilize them as basic research results. The experimental design was performed by 2˟4 factor desigh, and the untreated (CON), and the additive inoculated (ADD) silage were stored and fermented for 30 (TH), 60 (ST), 90 (NT), and 120 (OHT) days, with each condition repeated 3 times. There was no change in the nutrient content of corn silage according to additive treatment and storage period (p>0.05). However, the change in DM and the increase in the relative proportions of lactic acid content and Lactobacillales according to the storage period (p<0.05) indicate that continuous fermentation progressed until OHT days of fermentation. Enterobacterales (33.0%), Flavobacteriales (14.4%), Sphingobacteriales (12.7%), Burkholderiales (9.28%) and Pseudomonadales (6.18%) dominated before fermentation of corn silage, but after fermentation, the diversity of microorganisms decreased sharply due to the dominance of Lactobacillales (69.4%) and Bacillales (11.5%), Eubacteriales (7.59%). Therefore, silage maintained good fermentation quality with or without microbial additives throughout all fermentation periods, but considering the persistence of fermentation even in long-term storage and the aerobic stability, it would be advantageous to use microbial additives.

This study was conducted with the aim of confirming the impact and relative contribution of extreme weather to dry matter yield (DMY) of silage corn in the central inland region of Korea. The corn data (n=1,812) were obtained from various reports on the new variety of adaptability experiments conducted by the Rural Development Administration from 1978 to 2017. As for the weather variables, mean aerial temperature, accumulated precipitation, maximum wind speed, and sunshine duration, were collected from the Korean Meteorological Administration. The extreme weather was detected by the box plot, the DMY comparison was carried out by the t-test with a 5% significance level, and the relative contribution was estimated by R2 change in multiple regression modeling. The DMY of silage corn was reduced predominantly during the monsoon in summer and autumn, with DMY damage measuring 1,500-2,500 kg/ha and 1,800 kg/ha, respectively. Moreover, the relative contribution of the damage during the monsoons in summer and autumn was 40% and 60%, respectively. Therefore, the impact of autumn monsoon season should be taken into consideration when harvesting silage corn after late August. This study evaluated the effect of extreme weather on the yield damage of silage corn in Korea and estimated the relative contribution of this damage for the first time.

This study was conducted to estimate the damage of Whole Crop Corn (WCC; Zea Mays L.) according to abnormal climate using machine learning as the Representative Concentration Pathway (RCP) 4.5 and present the damage through mapping. The collected WCC data was 3,232. The climate data was collected from the Korea Meteorological Administration's meteorological data open portal. The machine learning model used DeepCrossing. The damage was calculated using climate data from the automated synoptic observing system (ASOS, 95 sites) by machine learning. The calculation of damage was the difference between the dry matter yield (DMY)normal and DMYabnormal. The normal climate was set as the 40-year of climate data according to the year of WCC data (1978-2017). The level of abnormal climate by temperature and precipitation was set as RCP 4.5 standard. The DMYnormal ranged from 13,845-19,347 kg/ha. The damage of WCC which was differed depending on the region and level of abnormal climate where abnormal temperature and precipitation occurred. The damage of abnormal temperature in 2050 and 2100 ranged from -263 to 360 and -1,023 to 92 kg/ha, respectively. The damage of abnormal precipitation in 2050 and 2100 was ranged from -17 to 2 and -12 to 2 kg/ha, respectively. The maximum damage was 360 kg/ha that the abnormal temperature in 2050. As the average monthly temperature increases, the DMY of WCC tends to increase. The damage calculated through the RCP 4.5 standard was presented as a mapping using QGIS. Although this study applied the scenario in which greenhouse gas reduction was carried out, additional research needs to be conducted applying an RCP scenario in which greenhouse gas reduction is not performed.

본 연구는 논과 밭에서 재배한 18개 사일리지용 옥수수 품종들 의 생육특성, 수량성 및 사료 가치를 비교 분석하기 위하여 수행하 였다. 논과 밭에서 출사일수는 조숙종인 신황옥이 78일로 가장 짧 았고, 강다옥이 92일로 가장 길었다. 그리고 논과 밭의 출사 일수 차이는 조숙종(6일)보다 중 ․ 만생종(10일)에서 더 크게 차이가 발생 하는 것을 확인하였다. 간장은 논에서 재배한 옥수수가 밭보다 5~10% 감소하였지만, 착수고율은 10~15% 증가되는 경향을 보여 주었다. 그러나 도복과 후기녹체성은 논과 밭에서의 큰 차이를 보이 지 않았다. 사일리지 사료가치를 증진시키는 옥수수의 암이삭 비율 은 신황옥이 논과 밭에서 55.5%, 47.8%로 가장 높았고, 대부분 품종들은 밭보다 논에서 10~30% 감소하는 것을 확인하였다. 또한 이삭길이도 10~25% 감소하였다. 생초수량은 다청옥이 밭에서 65,750 kg/ha, 논에서 33,880 kg/ha로 최고 수량을 보였다. 생초수 량과 유사하게 건물수량도 다청옥이 밭에서 26,910 kg/ha, 논에 서 21,670 kg/ha로, TDN수량은 밭에서 18,040 kg/ha, 논에서 14,390 kg/ha로 최고 수량을 보여주었다. 사일리지용 옥수수의 사 료 가치를 평가하기 위하여 조단백질, 전분을 종실에서 분석한 결 과 논과 밭에서 재배한 품종간의 차이는 보이지 않았다. 그리고 잎과 줄기, 종실을 이용하여 ADF와 NDF 함량을 분석한 결과 잎 과 줄기는 밭에서는 P3394, P1543 같은 수입종이, 논에서 재배할 때는 신광옥, 다안옥 같은 국산품종이 낮을 함량을 가지고 있었다. 또한 종실에서는 밭보다 논에서 ADF와 NDF 함량이 일부 품종에 서 감소하였지만, 대부분 품종에서는 큰 차이를 보이지 않았다. 따라서 논과 밭에서 재배한 옥수수 품종들의 사료 가치는 큰 차이 를 보이지 않으므로, 배수 관리 등을 통해 생육을 정상적으로 재배 한다면 논에서의 옥수수 수량성을 확보 할 수 있다고 판단된다

This study aimed to investigate the impacts of extreme weather on the dry matter yield (DMY) of silage maize in South Korea. The maize data (n=3,041) were collected from various reports of the new variety of adaptability experiments by the Rural Development Administration (1978-2017). Eight weather variables were collected: mean temperature, low temperature, high temperature, maximum precipitation, accumulated precipitation, maximum wind speed, mean wind speed, and sunshine duration. These variables were calculated based on ten days within seeding to harvesting period. The box plot detected an outlier to distinguish extreme weather from normal weather. The difference in DMY between extreme and normal weather was determined using a t-test with a 5% significance level. As a result, outliers of high-extreme precipitation were observed in July and August. Low-extreme mean temperature was remarkable in middle May, middle June, and late July. Moreover, the difference in DMY between extreme and normal weather was greatest (5,597.76 kg/ha) during the maximum precipitation in early July. This indicates that the impact of heavy rainfall during the Korean monsoon season was fatal to the DMY of silage maize. However, in this study, the frequency of extreme weather was too low and should not be generalize. Thus, in the future, we plan to compare DMY with statistical simulations based on extreme distributions.

This study was conducted to estimate the damage of Whole Crop Maize (WCM) according to abnormal climate using machine learning and present the damage through mapping. The collected WCM data was 3,232. The climate data was collected from the Korea Meteorological Administration's meteorological data open portal. Deep Crossing is used for the machine learning model. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The damage was calculated by difference between the Dry matter yield (DMY)normal and DMYabnormal. The normal climate was set as the 40-year of climate data according to the year of WCM data (1978~2017). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization(WMO) standard. The DMYnormal was ranged from 13,845~19,347 kg/ha. The damage of WCM was differed according to region and level of abnormal climate and ranged from -305 to 310, -54 to 89, and -610 to 813 kg/ha bnormal temperature, precipitation, and wind speed, respectively. The maximum damage was 310 kg/ha when the abnormal temperature was +2 level (+1.42 ℃), 89 kg/ha when the abnormal precipitation was -2 level (-0.12 mm) and 813 kg/ha when the abnormal wind speed was -2 level (-1.60 ㎧). The damage calculated through the WMO method was presented as an mapping using QGIS. When calculating the damage of WCM due to abnormal climate, there was some blank area because there was no data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).

The present study was conducted to examine the effect of soybean silage as a crude protein supplement for corn silage in the diet of Hanwoo steers. The first experiment was conducted to evaluate the effect of replacing corn silage with soybean silage at different levels on rumen fermentation characteristics in vitro. Commercially-purchased corn silage was replaced with 0, 4, 8, or 12% of soybean silage. Half gram of the substrate was added to 50 mL of buffer and rumen fluid from Hanwoo cows, and then incubated at 39°C for 0, 3, 6, 12, 24, and 48 h. At 24 h, the pH of the control (corn silage only) was lower (p<0.05) than that of soybeansupplemented silages, and the pH numerically increased along with increasing proportions of soybean silage. Other rumen parameters, including gas production, ammonia nitrogen, and total volatile fatty acids, were variable. However, they tended to increase with increasing proportions of soybean silage. In the second experiment, 60 Hanwoo steers were allocated to one of three dietary treatments, namely, CON (concentrate with Italian ryegrass), CS (concentrate with corn silage), CS4% (concentrate with corn silage and 4% of soybean silage). Animals were offered experimental diets for 110 days during the growing period and then finished with typified beef diets that were commercially available to evaluate the effect of soybean silage on animal performance and meat quality. With the soybean silage, the weight gain and feed efficiency of the animal were more significant than those of the other treatments during the growing period (p<0.05). However, the dietary treatments had little effect on meat quality except for meat color. In conclusion, corn silage mixed with soybean silage even at a lower level provided a greater ruminal environment and animal performances, particularly with increased carcass weight and feed efficiency during growing period.

The planting date of corn for silage has been delayed because of spring drought and double cropping system in Korea. This experiment was conducted to evaluate agronomic characteristics, forage production and feed value of corn at April and May in 2019. Experimental design was a split-plot with three replications. Planting dates (12 April and 10 May) were designated to the main plot, and corn hybrids (‘P0928’, ‘P1543’ and ‘P2088’) to the subplot. The silking days of the early planting date (12 April) was 79 days and that of the late planting date (10 May) was 66 days (p<0.0001), however, there were no significant differences among the corn hybrids. Ear height of the late planting date was higher than that of the early planting (p<0.05), while there were no significant differences in plant height of corn. Insect resistance at the early planting was lower than that of late planting (p<0.05), however, lodging resistance was no significant difference at planting date. The rice black streaked virus (RBSDV) infection of early planting was 3.7% and that of late planting was 0.3% (p<0.001). Dry matter (DM) contents of stover, ear and whole plant had significant difference at planting date (p<0.05). And differences in ear percentages were observed among the corn hybrids (p<0.01). And ear percentages of early maturing corn (‘P0928’) was higher than for other hybrids. Ear percentage at the early planting date was higher than that at the late planting date (p<0.01). DM and total digestible nutrients (TDN) yields had significant difference at planting date, however, there were no significant differences among the corn hybrids. DM and TDN yields at the late planting (21,678 kg/ha and 14,878 kg/ha) were higher than those of the early planting (13,732 kg/ha and 9,830 kg/ha). Crude protein content at the early planting date was higher than that of the late planting. Acid detergent fiber content of the late planting was lower than that of the early planting date (p<0.01), while there were no significant neutral detergent fiber content difference among the corn tested. Calculated net energy for lactation (NEL) and TDN at the early planting were higher than those of at the late planting (p<0.01). Results of this our study indicate that the late planting date (May) is better than early planting date (April) in forage yield and feed value of corn. Therefore, the delay of planting date by May was more suitable for use in cropping system.

본 연구는 기계학습을 통한 수량예측모델을 이용하여 이상기상에 따른 WCM의 DMY 피해량을 산출하기 위한 목적으로 수행하였다. 수량예측모델은 WCM 데이터 및 기상 데이터를 수집 후 가공하여 8가지 기계학습을 통해 제작하였으며 실험지역은 경기도로 선정하였다. 수량예측모델은 기계학습 기법 중 정확성이 가장 높은 DeepCrossing (R2=0.5442, RMSE=0.1769) 기법을 통해 제작하였다. 피해량은 정상기상 및 이상기상의 DMY 예측값 간 차이로 산출하였다. 정상기상에서 WCM의 DMY 예측값은 지역에 따라 차이가 있으나 15,003~17,517 kg/ha 범위로 나타났다. 이상기온, 이상강수량 및 이상풍속에서 WCM의 DMY 예측 값은 지역 및 각 이상기상 수준에 따라 차이가 있었으며 각각 14,947~17,571 kg/ha, 14,986~17,525 kg/ha 및 14,920~17,557 kg/ha 범위로 나타났다. 이상기온, 이상강수량 및 이상풍속에서 WCM의 피해량은 각각 –68~89 kg/ha, -17~17 kg/ha 및 – 112~121 kg/ha 범위로 피해로 판단할 수 없는 수준이었다. WCM의 정확한 피해량을 산출하기 위해서는 수량예측모델에 이용하는 이상기상 데이터 수의 증가가 필요하다.

This experiment was conducted to a comparison of the productivity according to variety and forage quality by plant parts of imported silage corn (Zea mays, L) in Pyeongchang. The corns evaluated in this experiment were 8 varieties (P1184, P1151, P1194, P1543, P1345, P1429, P1443, and P2105) introduced from the United States, Pioneer Hybrid Co. The harvested corn was divided into 5 plant parts (leaf, stem, cob, husk, and grain), and the ratio of each part was calculated using dry weight and the feed value was analyzed. The emergence rate of corn was generally good except for the P1151 and P2105 varieties. The average tasseling date was July 24th and the silking date was July 27th, but the P2105 variety was late to July 28th and August 1st, and the remaining varieties were similar. P1345 was the highest (289 and 123 cm), and P1151 varieties were the lowest (267 and 101 cm) in the plant and ear height. Disease resistance was low in P1184, P1443 and P1429, and P1197 and P1345 were high. In the case of stover, the dry matter (DM) content was the lowest at 19.6% in the P1151 and the highest at 24.9% in the P1429. DM content of ear was the highest in the P2105 (55.5%), and P1184 (54.2%) and P1345 (54.3%) were also significantly higher (p<0.05). The DM yield of stover of P2105, P1429 and P1194 varieties was significantly higher (p<0.05), and ear yield of P2105, P1345 and P1443 was higher. The proportions of each part of plants (leaf, stem, cob, husk, and grain) divided by 5 was high, with 50-60% of the ear(grain+cob) ratio. The ratio of husk and cob was roughly similar, and the leaf and stem part showed a ratio of about 20%. The crude protein (CP) content was highest in leaf, followed by grain. The CP content of the stem was the lowest, and the husk was not significantly different among the varieties (p>0.05). The acid detergent fiber (ADF) content was similar to the rest parts except grain, but the leaf part tended to be lower, and other parts except the stem and leaf showed no significant difference between varieties (p>0.05). There was no significant difference in NDF (neutral detergent fiber) content in husk, but there was a difference between varieties in other parts (p<0.05). In addition, there was a special difference by plant parts for each variety, P2015 on the stem, P1197 on the leaf, P1151 on the cob, P1197 on the husk, and P1197 on the grains with high NDF content. IVDMD (in vitro dry matter digestibility) was not significantly different between stems and grains, but there was a difference between varieties in cobs and husks. According to the results, DM yield of P2105 variety was the best in the experiment, and the ratio of grain was excellent in P1543 and P1345. In addition, it was found that the feed value was higher in the leaves and grains, and the leaf and stem had higher feed values than husk or cob.

This study aimed to discuss the optimal seeding and harvesting dates with growing degree days(GDD) via meta-data of whole crop maize(WCM). The raw data (n=3,152) contains cultivation year, cultivars, location, seeding and harvesting dates collected from various reports such as thesis, science journals and research reports (1982-2012). The processing was: recording, screening and modification of errors; Then, the final dataset (n=121) consists of seeding cases (n=29), and harvesting cases (n=92) which were used to detect the optimum. In addition, the optimal periods considering tolerance range and GDD also were estimated. As a result, the optimum seeding and harvesting periods were 14th April ~ 3rd May and 15th August ~ 4th September, respectively; where, their GDDs were 23.7~99.6℃ and 1,328.7~ 1,602.1℃, respectively. These GDDs could be used as a judge standard for selecting the seeding and harvesting dates.

This experiment was conducted to comparison study on the productivity for certified varieties of import adaptability of silage corn in Pyeongchang area. Total eight varieties (Gangpyeongok, 31N27, 32P75, 32W86, P3156, P3394, DK 689 및 DK 729) were evaluated. The experimental design was 8 treatment of randomized block with three replications. Corn varieties were cultivated in experimental field of Pyeongchang campus, SNU from 1 May to 2 September, 2015 and plot size was 15㎡. Plant height of 32W86 and ear height of Gwanpyeongok was the highest (p<0.05). Tasseling and silking date was 27 July-3 August and silking occurred after 1-3 day of tasseling. Average day to silking was 92 days and that of 31N27 variety was short (p<0.05). The varieties of DeKalbo Company (DK 689 and DK 729) required more times to silking. Average GDD (growth degree day) of eight varieties was 1,023℃ and P3352 was the lowest GDD. In the trials of resistance evaluation, P3394 was strong in disease, P3156 was the highest in insect. All varieties did not show the lodging and variety of DK 729 showed the highest stay green score (p<0.05). Average dry matter content was 30.77%, it showed higher trend in DM. 32W86 was the highest DM content among the varieties, but there was no significant difference among varieties (p>0.05). The weight per ear was the highest in 32W86 and the lowest in Gwanpyeongok. The ration of ear to whole plant was higher in 32W86 and P3394, but it was not found the significant difference (p>0.05). Average yield of fresh and DM was 59,017 and 13,476 kg/ha, respectively. DK 689 showed higher DM and TDN yield than others, but there was not significant difference (p>0.05). According to results, the difference of productivity was not found among certified variety of import adaptability of silage corn. The varieties Gwanpyeongok, 32W86 and 32P75 would be recommendable in Pyeongchang area for stable cultivation.

This study was conducted to determine the effect of mathematical transformation on near infrared spectroscopy (NIRS) calibrations for the prediction of chemical composition and fermentation parameters in corn silage. Corn silage samples (n=407) were collected from cattle farms and feed companies in Korea between 2014 and 2015. Samples of silage were scanned at 1 nm intervals over the wavelength range of 680~2,500 nm. The optical data were recorded as log 1/Reflectance (log 1/R) and scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with several spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation (R2 cv) and the lowest standard error of cross validation (SECV). Results of this study revealed that the NIRS method could be used to predict chemical constituents accurately (correlation coefficient of cross validation, R2 cv, ranging from 0.77 to 0.91). The best mathematical treatment for moisture and crude protein (CP) was first-order derivatives (1, 16, 16, and 1, 4, 4), whereas the best mathematical treatment for neutral detergent fiber (NDF) and acid detergent fiber (ADF) was 2, 16, 16. The calibration models for fermentation parameters had lower predictive accuracy than chemical constituents. However, pH and lactic acids were predicted with considerable accuracy (R2 cv 0.74 to 0.77). The best mathematical treatment for them was 1, 8, 8 and 2, 16, 16, respectively. Results of this experiment demonstrate that it is possible to use NIRS method to predict the chemical composition and fermentation quality of fresh corn silages as a routine analysis method for feeding value evaluation to give advice to farmers.

본 연구는 사일리지용 옥수수를 파종 한 후 배수로 깊이를 0 cm, 20 cm, 30 cm 그리고 50 cm로 처리하고 이에 따른 생육특성, 생산성 및 화학적 특성을 비교 검토하였다. 초장, 엽장, 엽폭, 착수고 및 하고엽은 배수로 깊이에 따라 유의적인 차이를 보이지 않았다. 알곡 충실도, 암이삭 길이 및 암이삭 둘레는 배수로 깊이가 깊을수록 유의적으로 커지는 것으로 나타났다(p<0.05). 그러나 경의 굵기 및 경경도는 처리구들 사이에 차이를 보이지 않았다. 당도에 있어서는 0 cm > 20 cm > 30 cm > 50 cm 구순으로 배수로 깊이가 낮을수록 높은 수치를 보였다(p<0.05). 생초수량, 건물수량 및 TDN 수량은 배수로 깊이가 깊을수록 증가하는 것으로 나타났다 (p<0.05). 조단백질함량은 50 cm구가 가장 높게 나타난 반면 0 cm 처리구가 가장 낮게 나타났다. 그러나 조지방, NDF, ADF 및 조섬유 함량은 처리구들간 유의적인 차이를 보이지 않았다. 조회분 함량은 50 cm 구에서 높게 나타났다(p<0.05). 총무기물함량은 0 cm (5,690.14) > 30 cm(5,397.02) > 20 cm (4,853.21) > 50 cm구(4,660.18 mg / 100 g) 순으로 높게 나타났다(p<0.05). 그리고 유리당 함량은 20 cm구에서 가장 높게 나타났다(p<0.05). 구성아미노산 함량은 50 cm구가 다른 처리구 보다 높게 나타났지만(p<0.05), 0 cm, 20 cm 및 30 cm 처리구 사이에는 유의적인 차가 없었다. 이상의 결과를 종합해 볼 때, 저지대 논 토양에서 수량을 확보하기 위해서는 최소한 배수로 깊이를 30 cm 이상을 확보 하는 것이 바람직한 것으로 판단된다.