• Title/Summary/Keyword: GDD(Growing Degree Days)

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Utilization of Growing Degree Days as an Index of Growth Duration of Rice Varieties (Growing Degree Days를 이용한 수도품종의 생육기간 측정방법과 이용)

  • 이석순
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.28 no.2
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    • pp.173-183
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    • 1983
  • To evaluate growing degree days(GDD) as an index of growth duration of rice plants, 30 days old seedlings of 16 japonica and 14 indica/japonica varieties were transplanted six times from May 10 at the 10-day intervals at Gyeongsan in 1982. The number of days from transplanting to heading decreased as transplanting dates delayed in all japonica varietie and 4 indica/japonica varieties but that of 10 indica/japonica varieties decreased up to June 9 or June 19 transplantings and then it levelled off or increased with further delay of transplanting. However, GDD requirement was similar among transplanting dates at appropriate base temperatures; GDD could be better than calendar day system to classify maturity of varieties especially grown in a wide range of climatic conditions. Required GDD from transplanting to heading of all indica/japonica and early japonica varieties showened a smaller coefficient of variation (CV) compared to longer season japonica varieties. Among GDD methods, an accumulation of daily Max + Min temp./2 -$l0^{\circ}C$ showed the smallest CV for the duration from transplanting to heading, but for ripening period GDD calculated with adjusted maximum temperature when it was higher than $30^{\circ}C$ showed the best results. Heading date did not affect required GDD for maturity of japonica varieties, but in indica/japonica varieties GDD decreased as heading date delayed; at late transplantings ripening period of indica/japonica varieties was less extended compared to japonica varietes due to a decrease in grain weight.

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Relationship Between Heat Unit Requirement and Growth and Yield of Mulberry, Morns indica L.

  • Sarkar A.;Rekha M.;Keshavacharyulu K.
    • International Journal of Industrial Entomology and Biomaterials
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    • v.10 no.1
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    • pp.65-68
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    • 2005
  • Growth and development of a plant over a growing season is closely related to the daily accumulation of heat. Heat unit measured by accumulated growing degree days (GDD) is becoming increasingly popular to estimate the growth of a plant or even in insect. GDD or heat accumulation per day is measured by calculating average daily temperature and then subtracting the base temperature below which growth does not occur. Heat accumulation per day is added for the desired period and accumulated GDD is determined. The present study was conducted in five seasons in an established garden with K-2, S-36 and V-1 mulberry varieties belonging to Morus indica L. grown under completely irrigated condition at the farm of CSRTI, Mysore during 2001 - 2002. Plants were pruned in each season and the growth of the plant measured by total shoot length and fresh leaf yield was recorded at an interval of 5 days starting from 30 days of pruning (DAP) to 70 days when all the plants were pruned. The accumulated GDD for the corresponding days were recorded and used for analysis. Accumulated growing degree days (GDD) have been found to be perfectly correlated with both growth and yield in all the seasons in all the varieties studied. The high $R^2$ values indicated a strong relationship between the accumulated GDD and, growth and yield of mulberry.

Methods of Estimating Growing Degree Days to Predict Growth Duration in Maize (옥수수의 생육기간 예측을 위한 Growing Degree Days의 계산방법)

  • Jong, Seung-Keun;Lee, Suk-Soon;Park, Keun-Yong
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.31 no.2
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    • pp.186-194
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    • 1986
  • In an attempt to find better ways to relate growth with temperature and to estimate maturity differences in corn (Zea mays L.), various formulas of computing Growing Degree Days (GDD) were evaluated. Utilizing data from 17 plantings of a single cross, Suweon 19, over a 3 year period, 24 different methods of computing GDD were compared for their ability to reduce variations over different plantings. The best equation was to compute GDD with a base temperature of 10$^{\circ}C$ and an optimum of 30$^{\circ}C$. The excess temperature above 30$^{\circ}C$ was subtracted to account for high temperature stress. GDDs required for emergence and silking of Suweon 19 were 64${\pm}$12$^{\circ}$ and 794${\pm}$19$^{\circ}$, respectively. Based on these GDD values, emergence and silking dates could be estimated with a variation less than 3 days. The observed and estimated number of days from planting to emergence and silking were not significantly different.

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Temporal and Spatial Distribution of Growing Degree Days for Maize in Northeast District of China (중국 동북지역에서 옥수수 유효적산온도의 시공간적 분포)

  • Jung, Myung-Pyo;Park, Hye-Jin;Shim, Kyo-Moon;Ahn, Joong-Bae
    • Korean Journal of Environmental Agriculture
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    • v.35 no.4
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    • pp.302-305
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    • 2016
  • BACKGROUND: The northeast district of China, especially Liaoning province, Jilin province, and Heilongjiang province, is one of the largest agricultural production regions in China. These regions play a significant role in ensuring food security. Accumulated temperature such as growing degree days (GDD) is an important environmental factor for plant growth and yield. Therefore, in this study, temporal and spatial distribution of GDD for maize was examined as a basis to estimate the growth and yield of maize in these regions. METHODS AND RESULTS: Meteorological date produced by NASA (MERRA-2) was used to estimate GDD of maize at this study sites. The GDD was calculated from sowing (May 1) to harvesting (Sep. 30). The average GDD of this region between 2010 and 2015 was $1323.0^{\circ}C$ day (595.3-1838.9). The spatial distribution of GDD showed a similar pattern during the different years surveyed. Double cropping for maize could be in only Liaoning province, northwestern Jilin province, and western and eastern Heilongjiang province where the GDD was over $1600^{\circ}C$day. However, The GDD in eastern Heilongjiang province was varied by year. CONCLUSION: The GDD of maize in northeast district of China was varied spatially, but similar among recent six years at the same region. This result can be used to predict growth stage and yield of maize at these regions.

Predicting Harvest Date of 'Niitaka' Pear by Using Full Bloom Date and Growing Season Weather (배 '신고'의 만개일 및 생육기 기상을 이용한 수확일 예측)

  • Han, Jeom-Hwa;Son, In-Chang;Choi, In-Myeong;Kim, Seung-Heui;Cho, Jung-Gun;Yun, Seok-Kyu;Kim, Ho-Cheol;Kim, Tae-Choon
    • Horticultural Science & Technology
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    • v.29 no.6
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    • pp.549-554
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    • 2011
  • The effect of full bloom date and growing season weather on harvesting date of 'Niitaka' pear (Pyrus pyrifolia) in Naju province and the model of multiple linear regression for predicting the fruit growing days was studied. Earlier year in full bloom date, the harvesting date tended earlier but fruit growing days tended longer. Mean and coefficient of variation of fruit growing degree days (GDD) accumulated daily mean and maximum temperature at the base of $0^{\circ}C$ from full bloom date to harvesting date was 3,565, 2.9% and 4,463, 2.5%, respectively. Fruit growing days was not correlated with the fruit GDD accumulated daily mean and maximum temperature at the base of $0^{\circ}C$ in each month but highly correlated with GDD accumulated daily meteorological factors at days after full bloom date. Especially, it was highly negatively correlated with GDD accumulated daily mean and maximum temperature at the base of $0^{\circ}C$ from $1^{st}$ day after full bloom to $60^{th}$ day. The determination coefficient ($r^2$) of multiple linear regression model by full bloom date, GDD accumulated daily mean and maximum temperature from $1^{st}$ day after full bloom to $60^{th}$ day for predicting fruit growing days was 0.7212. As a result, the fruit growing days of 'Niitaka' pear in Naju province can predict with 72% accuracy by the model of multiple linear regression.

On Mapping Growing Degree-Days (GDD) from Monthly Digital Climatic Surfaces for South Korea (월별 전자기후도를 이용한 생장도일 분포도 제작에 관하여)

  • Kim, Jin-Hee;Yun, Jin-I.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.10 no.1
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    • pp.1-8
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    • 2008
  • The concept of growing degree-days (GDD) is widely accepted as a tool to relate plant growth, development, and maturity to temperature. Information on GDD can be used to predict the yield and quality of several crops, flowering date of fruit trees, and insect activity related to agriculture and forestry. When GDD is expressed on a spatial basis, it helps identify the limits of geographical areas suitable for production of various crops and to evaluate areas agriculturally suitable for new or nonnative plants. The national digital climate maps (NDCM, the fine resolution, gridded climate data for climatological normal years) are not provided on a daily basis but on a monthly basis, prohibiting GDD calculation. We applied a widely used GDD estimation method based on monthly data to a part of the NDCM (for Hapcheon County) to produce the spatial GDD data for each month with three different base temperatures (0, 5, and $10^{\circ}C$). Synthetically generated daily temperatures from the NCDM were used to calculate GDD over the same area and the deviations were calculated for each month. The monthly-data based GDD was close to the reference GDD using daily data only for the case of base temperature $0^{\circ}C$. There was a consistent overestimation in GDD with other base temperatures. Hence, we estimated spatial GDD with base temperature $0^{\circ}C$ over the entire nation for the current (1971-2000, observed) and three future (2011-2040, 2041-2070, and 2071-2100, predicted) climatological normal years. Our estimation indicates that the annual GDD in Korea may increase by 38% in 2071-2100 compared with that in 1971-2000.

Effects of Seeding Date on Growth and Yield in Oats (파종기가 귀리의 생육 및 수량에 미치는 영향)

  • 현승원;박양문;고무수;강영길
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.39 no.4
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    • pp.359-365
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    • 1994
  • A oat (Avena sativa) cultivar, 'Guiri 16', was seeded on Oct. 9, Oct. 24, Nov. 9, Nov. 24, Dec. 9 of 1991 and 1992 to determine usefulness of growing degree days (GDD) for predicting growth duration and the optimum seeding date of oats for grains in Cheju province. The later the seeding, the greater the number of days to emergence but the fewer the number of days to heading and maturity. As seeding was delayed, accumulated GDD from seeding to emergence generally tended to decrease but was less subjective to a constant downward tend over seeding date than the number of days. Accumulated GDD from emergence ot heading decreased with delaying seeding and accumulated GDD from heading to maturity decreased as seeding was delayed up to Nov. 24. As seeding was delayed from Oct. 9 to Dec. 9, to Dec. 9, leaf area index at heading decreased from 7.7 to 5.1 and dry matter yield at maturity from 1920 to 823 kg /10a in 1992-1993, and culm length 120 to 89cm on an average of 1991-1992 and 1992-1993. While the number of grains per panicle and test weight were not affected by seeding date in 1991-1992 and 1992-1993, the number of panicles per m$^2$ and grain yield were decreased when oats were seeded earlier or later than Nov. 9. 1000 grain weight was not affected by seeding date in 1991-1992 but greatest at Nov. 9 seeding in 1992-1993. The results indicate that optimum seeding date of oats in Cheju province would be early November. November.

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Effect of Yearly Changes in Growing Degree Days on the Potential Distribution and Growth of Quercus mongolica in Korea (연도별 생장도일의 변화가 신갈나무의 잠재분포와 생장에 미치는 영향)

  • Lim, Jong Hwan;Park, Ko Eun;Shin, Man Yong
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.18 no.3
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    • pp.109-119
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    • 2016
  • This study was conducted to analyze the effect of yearly changes in growing degree days (GDD) on the potential distribution and growth of Quercus mongolica in Korea. Annual tree-ring growth data of Quercus mongolica collected by the $5^{th}$ National Forest Inventory were first organized to identify the range of current distribution for the species. Yearly GDD was calculated based on daily mean temperature data from 1951 to 2010 for counties with current distribution of Q. monglica. When tree-ring growth data were analyzed through cluster analysis based on similarity of climatic conditions, seven clusters were identified. Yearly GDD based on daily mean temperature data of each county were calculated for each of the cluster to predict the change of potential distribution. Temperature effect indices were estimated to predict the effect of GDD on the growth patterns. In addition, RCP 4.5 and RCP 8.5 of climate change scenarios were adopted to estimate yearly GDD and temperature effect indices from 2011 to 2100. The results indicate that the areas with low latitude and elevation exceed the upper threshold of GDD for the species due to the increase of mean temperature with climate change. It was also predicted that the steep increase of temperature will have negative influences on tree-ring growth, and will move the potential distribution of the species to areas with higher latitude or higher elevation, especially after the year of 2050. The results of this study are expected to provide valuable information necessary for estimating local growth characteristics and for predicting changes in the potential distribution of Q. mongolica caused by climate change.

Detecting on Optimal Seeding and Harvesting Dates of Whole Crop Maize via Meta Data (사일리지용 옥수수의 메타자료를 이용한 적정 파종 및 수확시기의 탐색)

  • Jo, Hyun Wook;Kim, Si Chul;Kim, Moon Ju;Kim, Ji Yung;Jo, Mu Hwan;Kim, Byong Wan;Sung, Kyung Il
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.40 no.1
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    • pp.66-72
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    • 2020
  • 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.