Due to the recent impact of global warming, heavy rainfall and droughts have been occurring regardless of the season, affecting the growth of Italian ryegrass (IRG), a winter forage crop. Particularly, delayed sowing due to frequent heavy rainfall or autumn droughts leads to poor growth and reduced winter survival rates. Therefore, techniques to improve yield through additional sowing in spring have been implemented. In this study, the growth of IRG sown in Spring and Autumn was compared and analyzed using vegetation indices during the months of April and May. Spectral data was collected using an Unmanned Aerial Vehicle (UAV) equipped with a hyperspectral sensor, and the following vegetation indices were utilized: Normalized Difference Vegetation Index; NDVI, Normalized Difference Red Edge Index; NDRE (I), Chlorophyll Index, Red Green Ratio Index; RGRI, Enhanced Vegetation Index; EVI and Carotenoid Reflectance Index 1; CRI1. Indices related to chlorophyll concentration exhibited similar trends. RGRI of IRG sown in autumn increased during the experimental period, while IRG sown in spring showed a decreasing trend. The results of RGRI in IRG indicated differences in optical characteristics by sowing seasons compared to the other vegetation indices. Our findings showed that the timing of sowing influences the optical growth characteristics of crops by the results of various vegetation indices presented in this study. Further research, including the development of optimal vegetation indices related to IRG growth, is necessary in the future.

This study was carried out to evaluate the growth characteristics and forage yield potential for warm season grass as emergency forages. The experimental design was a randomized block design (RBD) with three replications. Two barnyard millet (Echinochloa species cv. Shirohie and Jeju native), a pearl millet (Pennisetum glaucum cv Feed milk 2) a proso millet (Panicum miliaceum cv Native), a teffgrass (Eragrostis tef cv. Tiffany) and a kleingrass (Panicum coloratum cv. Selection 75) were compared for forage production and quality at the Mid regions of Korea. Warm season forage crops were sown on May 21 and June 23 respectively, and in 2021, it was sown twice on May 21 and June 21 The number of days to seedling emergence for barnyard millet and teffgrass was observed approximately 10 and 3 days after seeding, respectively. The cultivation period from seeding to harvest was within 60 days for all entry spices except for the late-heading type barnyard millet (within 84 days). As for the dry matter yield by seeding date, the dry matter yield of the late-heading type barnyard millet in May seeding was the highest at 23,872 kg/ha, and the kleingrass was the lowest at 3,888 kg/ha. For the June seeding, the dry matter yield of the late-heading type barnyard millet was 17,032 kg/ha, the highest, and the proso millet, teffgrass and kleingrass showed the lowest at 5,468, 5,442, and 5,197 kg/ha, respectively. The crude protein (CP) content was varied by warm season grass species, but the early-heading type barnyard millet, teffgrass, and kleingrass showed the highest tendency, and the late-heading type barnyard millet showed the lowest at 5.7~5.9%. Neutral detergent fiber (NDF) and acid detergent fiber (ADF) content did not show a significant difference between the seeding in May, but kleingrass in June sowed lower than the others.

This study was carried out the estimation on consumption patterns and consciousness of domestic forage for improvement of the quality of domestic forage. Although the cultivated area in South Korea of forage has increased significantly compared to the past, the self-sufficiency rate of domestic forage has increased to around 80% since 2010. Also, livestock farmers prefer to use import forage than domestic due to convenience of use. In Korean beef farms, the ratio of import to domestic forage was higher in domestic forage (import forage 3 : domestic forage 7). In the method of securing domestic forage, purchase of forage (55.6%) was higher than self-cultivation of forage (44.4%). The ratio of use by bailing type was shown in the order of rice staw rice straw (50.5%), domestic hay (15%), imported hay (12.5%), and total mixed ratio (10.7%). The preference of forage was in the order of amount of foreign matter, moisture content, price, feed value in Korean native cattle farm. The result of satisfaction with domestic and import forage showed that the satisfaction of domestic forage price was higher than import forage, while the moisture content and foreign matter of forage were lower than import forage. In addition, in the results of the satisfaction and importance of domestic roughage compared to imported roughage, satisfaction with imported roughage was generally high in all items except for price. As a result, in order to improve the satisfaction of domestic forage in Korean native cattle farm, it is necessary to minimize foreign matter in forage and increase hay production for moisture content uniform in forage.

본 연구는 무인기를 이용한 동계사료의 수량조사시 필요한 검량식의 작성을 위한 식생조사 및 분광측정의 적정 시기와, 작성된 검량식의 적용이 적절한 시기를 판단하기 위하여 고정식 자동 분광 측정장치를 개발하여 호밀, 총체보리, IRG를 대상으로 NDVI 를 장기간 측정하였다. 그리고 NDVI가 최댓값이 되는 날을 기준 으로 증가기간과 감소시간으로 기간을 나누어 건물수량 예측을 위한 검량식을 작성하고 검량식의 예측정확도를 각각 비교하였다. 조사결과 호밀, 총체보리, IRG는 각각 4월 8일, 4월 9일, 4월 5일에 NDVI가 최대치가 되었으며 NDVI 증가기간의 검량식은 결정계수(R2)는 각각 0.84, 0.84, 0.78로 높은 상관관계를 보였고 NDVI 감소기간에는 각각 0.00, 0.02, 0.27로 매우 낮게 나타났다. 따라서 NDVI 측정을 통한 건물수량 예측을 효율적으로 하기 위해서는 NDVI 변화를 정확히 측정할 필요가 있으며 고정식 자동 분광 측정 방법은 생육에 따른 NDVI의 정밀 측정에 효과적인 것으로 판단된다.

Rye, whole-crop barley and Italian Ryegrass are major winter forage species in Korea, and yield monitoring of winter forage species is important to improve forage productivity by precision management of forage. Forage monitoring using Unmanned Aerial Vehicle (UAV) has offered cost effective and real-time applications for site-specific data collection. To monitor forage crop by multispectral camera with UAV, we tested four types of vegetation index (Normalized Difference Vegetation Index; NDVI, Green Normalized Difference Vegetation Index; GNDVI, Normalized Green Red Difference Index; NGRDI and Normalized Difference Red Edge Index; NDREI). Field measurements were conducted on paddy field at Naju City, Jeollanam-do, Korea between February to April 2019. Aerial photos were obtained by an UAV system and NDVI, GNDVI, NGRDI and NDREI were calculated from aerial photos. About rye, whole-crop barley and Italian Ryegrass, regression analysis showed that the correlation coefficients between dry matter and NDVI were 0.91∼0.92, GNDVI were 0.92∼0.94, NGRDI were 0.71∼0.85 and NDREI were 0.84∼0.91. Therefore, GNDVI were the best effective vegetation index to predict dry matter of rye, wholecrop barley and Italian Ryegrass by UAV system.

This study was carried out to explore the accuracy of near infrared spectroscopy(NIRS) for the prediction of moisture content and chemical parameters on winter annual forage crops. A population of 2454 winter annual forages representing a wide range in chemical parameters was used in this study. Samples of forage were scanned at 1nm intervals over the wavelength range 680-2500nm and the optical data was recorded as log 1/Reflectance(log 1/R), which 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 spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation(R2) and the lowest standard error of cross-validation(SECV). The results of this study showed that NIRS calibration model to predict the moisture contents and chemical parameters had very high degree of accuracy except for barely. The R2 and SECV for integrated winter annual forages calibration were 0.99(SECV 1.59%) for moisture, 0.89(SECV 1.15%) for acid detergent fiber, 0.86(SECV 1.43%) for neutral detergent fiber, 0.93(SECV 0.61%) for crude protein, 0.90(SECV 0.45%) for crude ash, and 0.82(SECV 3.76%) for relative feed value on a dry matter(%), respectively. Results of this experiment showed the possibility of NIRS method to predict the moisture and chemical composition of winter annual forage for routine analysis method to evaluate the feed value.