Determination of Trend in Dry Matter Yield of Sorghum-sudangrass Hybrid (Sorghum bicolor L.) in Central Inland of Korea via Time Series Analysis

2021 ◽  
Vol 32 (2) ◽  
pp. 31-39
Author(s):  
Moonju Kim ◽  
Mu Hwan Jo ◽  
Befekadu Chemere ◽  
Kyung Il Sung
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Sorghum Bicolor ◽  
Dry Matter ◽  
Dry Matter Yield ◽  
Series Analysis ◽  
Sorghum Sudangrass ◽  
Sorghum Bicolor L

scholarly journals Detecting Long-Term Dry Matter Yield Trend of Sorghum-Sudangrass Hybrid and Climatic Factors Using Time Series Analysis in the Republic of Korea

Agriculture ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. 197 ◽  
Author(s):  
Befekadu Chemere ◽  
Jiyung Kim ◽  
Baehun Lee ◽  
Moonju Kim ◽  
Byongwan Kim ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Dry Matter ◽  
Climatic Factors ◽  
Climatic Conditions ◽  
Republic Of Korea ◽  
Dry Matter Yield ◽  
The Republic ◽  
Sorghum Sudangrass

Despite the gradual increase in livestock feed demands, the supply faces enormous challenges due to extreme climatic conditions. As the presence of these climatic condition has the potential to affect the yield of sorghum-sudangrass hybrid (SSH), understanding the yield variation in relation to the climatic conditions provides the ability to come up with proper mitigation strategies. This study was designed to detect the effect of climatic factors on the long-term dry matter yield (DMY) trend of SSH using time series analysis in the Republic of Korea. The collected data consisted of DMY, seeding-harvesting dates, the location where the cultivation took place, cultivars, and climatic factors related to cultivation of SSH. Based on the assumption of normality, the final data set (n = 420) was generated after outliers had been removed using Box-plot analysis. To evaluate the seasonality of DMY, an augmented Dickey Fuller (ADF) test and a correlogram of Autocorrelation Function (ACF) were used. Prior to detecting the effect of climatic factors on the DMY trend, the Autoregressive Integrated Moving Average (ARIMA) model was fitted to non-seasonal DMY series, and ARIMA (2, 1, 1) was found to be the optimal model to describe the long-term DMY trend of SSH. ARIMA with climatic factors (ARIMAX) detected significance (p < 0.05) of Seeding-Harvesting Precipitation Amount (SHPA) and Seeding-Harvesting Accumulated Temperature (SHAMT) on DMY trend. This does not mean that the average temperature and duration of exposure to sunshine do not affect the growth and development of SSH. The result underlines the impact of the precipitation model as a major factor for the seasonality of long-term DMY of SSH in the Republic of Korea.

scholarly journals Soil respiration, root traits and dry matter yield of sorghum (Sorghum bicolor L.) as affected by biochar application under different cropping patterns and irrigation method

2020 ◽  
Vol 34 (4) ◽  
pp. 495-502
Author(s):  
Sara Darvishi Aghajani ◽  
Mojtaba Alavifazel ◽  
Ghorban Nurmohammadi ◽  
Mohammad Reza Ardakani ◽  
Mansur Sarajughi
Keyword(s):  
Soil Respiration ◽  
Sorghum Bicolor ◽  
Dry Matter ◽  
Root Traits ◽  
Dry Matter Yield ◽  
Cropping Patterns ◽  
Irrigation Method ◽  
Sorghum Bicolor L

DETERMINATION OF THE FREQUENCY OF PULSATILE LUTEINIZING HORMONE SECRETION BY TIME SERIES ANALYSIS

1985 ◽  
Vol 22 (3) ◽  
pp. 341-346 ◽  
Author(s):  
A. P. MURDOCH ◽  
P. J. DIGGLE ◽  
W. DUNLOP ◽  
P. KENDALL-TAYLOR
Keyword(s):  
Time Series ◽  
Luteinizing Hormone ◽  
Time Series Analysis ◽  
Hormone Secretion ◽  
Luteinizing Hormone Secretion ◽  
Series Analysis
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